From 84c04d2ad3e559a1da4b9772dd7b3472fbf35ce8 Mon Sep 17 00:00:00 2001 From: cristinamullin Date: Tue, 18 Oct 2022 11:11:00 -0400 Subject: [PATCH 01/10] update github pages --- docs/articles/CONTRIBUTING.html | 2 +- docs/articles/WQPDataHarmonization.html | 2 +- docs/pkgdown.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/articles/CONTRIBUTING.html b/docs/articles/CONTRIBUTING.html index 2161e3b5..fd22ab8c 100644 --- a/docs/articles/CONTRIBUTING.html +++ b/docs/articles/CONTRIBUTING.html @@ -71,7 +71,7 @@

Contributing

-

2022-10-13

+

2022-10-17

Source: vignettes/CONTRIBUTING.Rmd
CONTRIBUTING.Rmd
diff --git a/docs/articles/WQPDataHarmonization.html b/docs/articles/WQPDataHarmonization.html index d95f70e7..09fe4bc5 100644 --- a/docs/articles/WQPDataHarmonization.html +++ b/docs/articles/WQPDataHarmonization.html @@ -73,7 +73,7 @@

Cristina A. Mullin

-

2022-10-13

+

2022-10-17

Source: vignettes/WQPDataHarmonization.Rmd
WQPDataHarmonization.Rmd
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 400b8c04..cedff263 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -4,7 +4,7 @@ pkgdown_sha: ~ articles: CONTRIBUTING: CONTRIBUTING.html WQPDataHarmonization: WQPDataHarmonization.html -last_built: 2022-10-13T20:39Z +last_built: 2022-10-17T18:24Z urls: reference: usepa.github.io/tada/reference article: usepa.github.io/tada/articles From dc662f9f6a5212d412b25366cf964739a0fa3373 Mon Sep 17 00:00:00 2001 From: cristinamullin Date: Tue, 18 Oct 2022 11:56:03 -0400 Subject: [PATCH 02/10] fixed note added importFrom(rlang,":=") to depth profile function. Added rlang as import in description file --- DESCRIPTION | 2 +- NAMESPACE | 1 + R/ResultFlagsDependent.R | 2 ++ 3 files changed, 4 insertions(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index 5853d513..e212f7bb 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -39,12 +39,12 @@ Imports: utils, RColorBrewer, stats, + rlang, lubridate Depends: R (>= 3.5.0) Suggests: remotes, - rlang, tidyverse, knitr, rmarkdown, diff --git a/NAMESPACE b/NAMESPACE index 3ee28e33..eb6d9e8a 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -30,3 +30,4 @@ export(TransformCensoredData) export(WQXTargetUnits) export(readWQPwebservice) importFrom(magrittr,"%>%") +importFrom(rlang,":=") diff --git a/R/ResultFlagsDependent.R b/R/ResultFlagsDependent.R index 8f5e3491..37e8579e 100644 --- a/R/ResultFlagsDependent.R +++ b/R/ResultFlagsDependent.R @@ -325,6 +325,8 @@ InvalidResultUnit <- function(.data, clean = TRUE) { #' When transform = FALSE, the output is the full dataset with 'Conversion Factor' #' columns and a 'Depth Target Unit' column. #' +#' @importFrom rlang := +#' #' @export #' From 76beba52d2f9cd8e7f64184d088b46f2b4f7dbe6 Mon Sep 17 00:00:00 2001 From: cristinamullin Date: Tue, 18 Oct 2022 12:08:28 -0400 Subject: [PATCH 03/10] updated internal WQX ref files --- inst/extdata/WQXunitRef.csv | 3 +++ 1 file changed, 3 insertions(+) diff --git a/inst/extdata/WQXunitRef.csv b/inst/extdata/WQXunitRef.csv index 9904c4f5..f67c2ac6 100644 --- a/inst/extdata/WQXunitRef.csv +++ b/inst/extdata/WQXunitRef.csv @@ -129,6 +129,8 @@ "Measurement Unit(MeasureUnitCode)",117,"cm3/min","Flow, Cubic centimeters per minute","7/26/2006 10:57:47 AM","cfs",5.885777786e-07,0 "Measurement Unit(MeasureUnitCode)",116,"cm3/sec","Flow, Cubic centimeters per second","7/26/2006 10:57:47 AM","cfs",3.531467e-05,0 "Measurement Unit(MeasureUnitCode)",355,"code","Picklist or Choicelist, Please see http://waterdata.usgs.gov/nwis/qwdata?codes_table26_help#62955","9/10/2014 12:00:00 AM","code",1,0 +"Measurement Unit(MeasureUnitCode)",728,"copies","Concentration Solution, copies (ie viral load)","10/3/2022 12:00:00 AM","pct modern",1,0 +"Measurement Unit(MeasureUnitCode)",727,"copies/ml","Concentration Solution, copies per milliliters (ie viral load)","10/3/2022 12:00:00 AM","pct modern",1,0 "Measurement Unit(MeasureUnitCode)",145,"count","Quantity, Count","7/26/2006 10:57:47 AM","count",1,0 "Measurement Unit(MeasureUnitCode)",356,"counts/sec","Concentration Solution, Counts per second","9/10/2014 12:00:00 AM","counts/sec",1,0 "Measurement Unit(MeasureUnitCode)",286,"d/h/m/s","Time, Days/hours/minutes/seconds","7/19/2010 3:16:29 PM","d/h/m/s",1,0 @@ -232,6 +234,7 @@ "Measurement Unit(MeasureUnitCode)",108,"lm/ft2","Light Intensity, lumens per square foot","7/26/2006 10:57:47 AM","lm/m2",10.763910417,0 "Measurement Unit(MeasureUnitCode)",325,"lm/m2","Light Intensity, lumens per square meter","1/11/2012 3:59:08 PM","lm/m2",1,0 "Measurement Unit(MeasureUnitCode)",372,"loc-sec","Direction or angle, Locational seconds (latitude/longitude)","3/1/2016 7:39:07 AM","loc-sec",1,0 +"Measurement Unit(MeasureUnitCode)",729,"log10 copies","Concentration Solution, Log10 copies (If Loga b = x, then a^x=b)","10/3/2022 12:00:00 AM","pct modern",1,0 "Measurement Unit(MeasureUnitCode)",106,"lumens","Light Intensity, lumens","7/26/2006 10:57:47 AM","lm/m2",10.763910417,0 "Measurement Unit(MeasureUnitCode)",137,"m","Length Distance, Meters","7/26/2006 10:57:47 AM","in",39.3700787401575,0 "Measurement Unit(MeasureUnitCode)",367,"m-1","Concentration Solution, Inverse meters or per meters","1/19/2016 11:12:28 AM","per in",0.0254,0 From 9fef48c87d618ffc1d75f1e890cada740171cc6d Mon Sep 17 00:00:00 2001 From: Mullin Date: Tue, 18 Oct 2022 17:28:46 -0400 Subject: [PATCH 04/10] depth profile bug fix added test as well for changing "meters" to "m" --- R/DataDiscoveryRetrieval.R | 34 +++- R/ResultFlagsDependent.R | 199 +++++++++++-------- R/Transformations.R | 2 +- docs/articles/CONTRIBUTING.html | 2 +- docs/articles/WQPDataHarmonization.html | 151 +------------- docs/index.html | 4 +- docs/pkgdown.yml | 2 +- docs/readme.html | 4 +- docs/reference/DepthProfileData.html | 40 ++-- docs/reference/HarmonizationRefTable.html | 6 +- docs/reference/TADAprofileCheck.html | 52 +++-- docs/reference/index.html | 2 +- docs/search.json | 2 +- man/DepthProfileData.Rd | 20 +- man/HarmonizationRefTable.Rd | 2 +- man/TADAprofileCheck.Rd | 31 ++- readme.md | 4 +- tests/testthat/test-DataDiscoveryRetrieval.R | 10 + vignettes/WQPDataHarmonization.Rmd | 68 ++++--- 19 files changed, 322 insertions(+), 313 deletions(-) diff --git a/R/DataDiscoveryRetrieval.R b/R/DataDiscoveryRetrieval.R index 55e6366c..02e09e41 100644 --- a/R/DataDiscoveryRetrieval.R +++ b/R/DataDiscoveryRetrieval.R @@ -271,11 +271,43 @@ autoclean <- function(.data) { # run MeasureValueSpecialCharacters function .data <- MeasureValueSpecialCharacters(.data) - + + #convert 'meters' to 'm' + .data$ActivityDepthHeightMeasure.MeasureUnitCode[.data$ActivityDepthHeightMeasure.MeasureUnitCode == 'meters'] <- 'm' + .data$ActivityTopDepthHeightMeasure.MeasureUnitCode[.data$ActivityTopDepthHeightMeasure.MeasureUnitCode == 'meters'] <- 'm' + .data$ActivityBottomDepthHeightMeasure.MeasureUnitCode[.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode == 'meters'] <- 'm' + .data$ResultDepthHeightMeasure.MeasureUnitCode[.data$ResultDepthHeightMeasure.MeasureUnitCode == 'meters'] <- 'm' + .data$ResultMeasure.MeasureUnitCode[.data$ResultMeasure.MeasureUnitCode == 'meters'] <- 'm' + return(.data) } +#' autoclean +#' +#' Removes complex biological data. Removes non-water media samples. +#' Removes rows of data that are true duplicates. Capitalizes fields to harmonize +#' data. This function includes and runs the TADA "MeasureValueSpecialCharacters" +#' function as well. +#' +#' Within "BiologicalIntentName", only the allowable values "tissue", "toxicity", +#' and "NA" apply to non-biological data (the function removes all others). +#' Toxicity and fish tissue data will be kept, but other types of biological +#' monitoring data will not. +#' +#' We decided to make some fields uppercase that way they're more compatible +#' with the WQX validation reference tables and to avoid any issues with +#' case-sensitivity when joining data. Therefore, we might need to tack on any +#' immediate QA steps (removing true duplicates, converting result values to numeric, +#' capitalizing letters, etc.) to this function, as well as the other retrieval functions. +#' +#' @param .data TADA dataframe +#' +#' @return cleaned TADA data profile +#' + + + #' TADA Profile Check #' #' This function checks if the column names in a dataframe include the TADA diff --git a/R/ResultFlagsDependent.R b/R/ResultFlagsDependent.R index 37e8579e..9a76594a 100644 --- a/R/ResultFlagsDependent.R +++ b/R/ResultFlagsDependent.R @@ -59,7 +59,7 @@ InvalidFraction <- function(.data, clean = TRUE) { col.order <- colnames(.data) # add WQX.SampleFractionValidity column to the list col.order <- append(col.order, "WQX.SampleFractionValidity") - # reorder columns in flag.data + # reorder columns in check.data check.data <- check.data[, col.order] # place flag column next to relevant fields check.data <- check.data %>% @@ -156,7 +156,7 @@ InvalidSpeciation <- function(.data, clean = TRUE) { col.order <- colnames(.data) # add WQX.MethodSpeciationValidity column to the list col.order <- append(col.order, "WQX.MethodSpeciationValidity") - # reorder columns in flag.data + # reorder columns in check.data check.data <- check.data[, col.order] # place flag columns next to relevant fields check.data <- check.data %>% @@ -254,7 +254,7 @@ InvalidResultUnit <- function(.data, clean = TRUE) { col.order <- colnames(.data) # add WQX.ResultUnitValidity column to the list col.order <- append(col.order, "WQX.ResultUnitValidity") - # reorder columns in flag.data + # reorder columns in check.data check.data <- check.data[, col.order] # place flag columns next to relevant fields check.data <- check.data %>% @@ -294,14 +294,14 @@ InvalidResultUnit <- function(.data, clean = TRUE) { #' Depth Profile Flag & Unit Conversion #' #' Function checks dataset for depth profile data. Where depth profile columns -#' are populated, the function appends 'Conversion Factor' columns +#' are populated, the function appends 'Conversion.Factor' columns #' and populates those columns based on the original unit (MeasureUnitCode #' columns) and the target unit, which is defined in the 'unit' argument. A -#' 'Depth Target Unit' column is also appended, indicating the unit all selected +#' 'WQX.Depth.TargetUnit' column is also appended, indicating the unit all selected #' depth data is converted to. When transform = FALSE, the output includes all -#' 'Conversion Factor' columns and the 'Depth Target Unit' column. When transform -#' = TRUE, the output includes converted depth data and the 'Depth Target -#' Unit' column, which acts as a flag indicating which rows have been converted. +#' 'Conversion.Factor' columns and the 'WQX.Depth.TargetUnit' column. When transform +#' = TRUE, the output includes converted depth data and the 'WQX.Depth.TargetUnit' +#' column, which acts as a flag indicating which rows have been converted. #' Default is transform = TRUE. #' #' @param .data TADA dataframe @@ -315,15 +315,15 @@ InvalidResultUnit <- function(.data, clean = TRUE) { #' 'ActivityBottomDepthHeightMeasure,' and 'ResultDepthHeightMeasure.'. Default #' is to include all allowable values. #' @param transform Boolean argument; When transform = FALSE, the output includes -#' all Conversion Factor' columns and the 'Depth Target Unit' column. When +#' all 'Conversion.Factor' columns and the 'WQX.Depth.TargetUnit' column. When #' transform = TRUE, the output includes converted depth data and the 'Depth #' Target Unit' column, which acts as a flag indicating which rows have been #' converted. Default is transform = TRUE. #' -#' @return Full dataset with converted uniform depth units and a 'Depth Target -#' Unit' column, which acts as a flag indicating which rows have been converted. -#' When transform = FALSE, the output is the full dataset with 'Conversion Factor' -#' columns and a 'Depth Target Unit' column. +#' @return Full dataset with converted uniform depth units and a 'WQX.Depth.TargetUnit' +#' column, which acts as a flag indicating which rows have been converted. +#' When transform = FALSE, the output is the full dataset with 'Conversion.Factor' +#' columns and a 'WQX.Depth.TargetUnit' column. #' #' @importFrom rlang := #' @@ -351,7 +351,7 @@ DepthProfileData <- function(.data, "ActivityDepthHeightMeasure.MeasureValue", "ActivityDepthHeightMeasure.MeasureUnitCode", "ActivityTopDepthHeightMeasure.MeasureValue", "ActivityTopDepthHeightMeasure.MeasureUnitCode", "ActivityBottomDepthHeightMeasure.MeasureValue", "ActivityBottomDepthHeightMeasure.MeasureUnitCode", - "ResultDepthHeightMeasure.MeasureValue", "ResultDepthHeightMeasure.MeasureUnitCode" + "ResultDepthHeightMeasure.MeasureValue", "ResultDepthHeightMeasure.MeasureUnitCode", "ActivityEndTime.TimeZoneCode" ) %in% colnames(.data)) == FALSE) { stop("The dataframe does not contain the required fields to use TADA. Use either the full physical/chemical profile downloaded from WQP or download the TADA profile template available on the EPA TADA webpage.") @@ -458,8 +458,8 @@ DepthProfileData <- function(.data, col.order <- append(col.order, appCol) } } - # reorder columns in flag.data - flag.data <- check.data[, col.order] + # reorder columns in check.data + check.data <- check.data[, col.order] # place flag columns next to relevant fields if ((appCols[1] %in% colnames(check.data)) == TRUE) { check.data <- check.data %>% @@ -491,92 +491,127 @@ DepthProfileData <- function(.data, .after = "ActivityEndTime.TimeZoneCode" ) } - # if transform = FALSE, output data - if (transform == FALSE) { - return(flag.data) - } + + #function should always run all code above + } + + # if transform = FALSE, output data + if (transform == FALSE) { + return(check.data) + } + # if transform = TRUE, apply conversion - if (transform == TRUE) { - # define clean.data - clean.data <- flag.data + if (transform == TRUE) { + # define clean.data + clean.data <- check.data # if WQX.ActDepth.ConversionFactor exists... if (("WQX.ActDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { # multiply ActivityDepthHeightMeasure.MeasureValue by WQX.ActDepth.ConversionFactor - suppressWarnings( - clean.data$ActivityDepthHeightMeasure.MeasureValue == - as.numeric(clean.data$ActivityDepthHeightMeasure.MeasureValue) * - clean.data$WQX.ActDepth.ConversionFactor - ) + clean.data$ActivityDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityDepthHeightMeasure.MeasureValue) * (clean.data$WQX.ActDepth.ConversionFactor)) + # replace ActivityDepthHeightMeasure.MeasureUnitCode values with unit argument + clean.data$ActivityDepthHeightMeasure.MeasureUnitCode.Original <- clean.data$ActivityDepthHeightMeasure.MeasureUnitCode + clean.data <- clean.data %>% + dplyr::relocate("ActivityDepthHeightMeasure.MeasureUnitCode.Original", + .after = "WQX.ActDepth.ConversionFactor" + ) + clean.data$ActivityDepthHeightMeasure.MeasureUnitCode[which( !is.na(clean.data$ActivityDepthHeightMeasure.MeasureUnitCode) )] <- unit - # delete ActDepth.Conversion.Unit column - clean.data <- dplyr::select(clean.data, -"WQX.ActDepth.ConversionFactor") - } - - # if WQX.ActTopDepth.ConversionFactor exists... - if (("WQX.ActTopDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { - # multiply ActivityTopDepthHeightMeasure.MeasureValue by WQX.ActTopDepth.ConversionFactor - suppressWarnings( - clean.data$ActivityTopDepthHeightMeasure.MeasureValue == - as.numeric(clean.data$ActivityTopDepthHeightMeasure.MeasureValue) * - clean.data$WQX.ActTopDepth.ConversionFactor - ) - # replace ActivityTopDepthHeightMeasure.MeasureUnitCode values with unit argument - clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode[which( - !is.na(clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode) - )] <- unit - # delete ActDepth.Conversion.Unit column - clean.data <- dplyr::select(clean.data, -"WQX.ActTopDepth.ConversionFactor") - } - - # if WQX.ActBottomDepth.ConversionFactor exists... - if (("WQX.ActBottomDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { - # multiply ActivityBottomDepthHeightMeasure.MeasureValue by WQX.ActBottomDepth.ConversionFactor - suppressWarnings( - clean.data$ActivityBottomDepthHeightMeasure.MeasureValue == - as.numeric(clean.data$ActivityBottomDepthHeightMeasure.MeasureValue) * - clean.data$WQX.ActBottomDepth.ConversionFactor - ) - # replace ActivityBottomDepthHeightMeasure.MeasureUnitCode values with unit argument - clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode[which( - !is.na(clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode) - )] <- unit - # delete ActBottomDepth.Conversion.Unit column - clean.data <- dplyr::select(clean.data, -"WQX.ActBottomDepth.ConversionFactor") - } - - # if WQX.ResultDepth.ConversionFactor exists... - if (("WQX.ResultDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { - # multiply ResultDepthHeightMeasure.MeasureValue by WQX.ResultDepth.ConversionFactor - suppressWarnings( - clean.data$ResultDepthHeightMeasure.MeasureValue == - as.numeric(clean.data$ResultDepthHeightMeasure.MeasureValue) * - clean.data$WQX.ResultDepth.ConversionFactor - ) - # replace ResultDepthHeightMeasure.MeasureUnitCode values with unit argument - clean.data$ResultDepthHeightMeasure.MeasureUnitCode[which( - !is.na(clean.data$ResultDepthHeightMeasure.MeasureUnitCode) - )] <- unit - # delete ResultDepth.Conversion.Unit column - clean.data <- dplyr::select(clean.data, -"WQX.ResultDepth.ConversionFactor") + + clean.data <- clean.data %>% + dplyr::relocate("ActivityDepthHeightMeasure.MeasureUnitCode", + .after = "ActivityDepthHeightMeasure.MeasureValue" + ) + # uncoment below to delete ActDepth.Conversion.Unit column + #clean.data <- dplyr::select(clean.data, -"WQX.ActDepth.ConversionFactor") } - # delete WQX.Depth.TargetUnit column - clean.data <- dplyr::select(clean.data, -"WQX.Depth.TargetUnit") + #WQX.ActTopDepth.ConversionFactor exists... + if (("WQX.ActTopDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { + # multiply ActivityTopDepthHeightMeasure.MeasureValue by WQX.ActTopDepth.ConversionFactor + clean.data$ActivityTopDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityTopDepthHeightMeasure.MeasureValue) * (clean.data$WQX.ActTopDepth.ConversionFactor)) + + # replace ActivityTopDepthHeightMeasure.MeasureUnitCode values with unit argument + clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode.Original <- clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode + clean.data <- clean.data %>% + dplyr::relocate("ActivityTopDepthHeightMeasure.MeasureUnitCode.Original", + .after = "WQX.ActTopDepth.ConversionFactor" + ) + + clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode[which( + !is.na(clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode) + )] <- unit + + clean.data <- clean.data %>% + dplyr::relocate("ActivityTopDepthHeightMeasure.MeasureUnitCode", + .after = "ActivityTopDepthHeightMeasure.MeasureValue" + ) + # uncoment below to delete ActTopDepth.Conversion.Unit column + #clean.data <- dplyr::select(clean.data, -"WQX.ActTopDepth.ConversionFactor") + } + + #WQX.ActBottomDepth.ConversionFactor exists... + if (("WQX.ActBottomDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { + # multiply ActivityBottomDepthHeightMeasure.MeasureValue by WQX.ActBottomDepth.ConversionFactor + clean.data$ActivityBottomDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityBottomDepthHeightMeasure.MeasureValue) * (clean.data$WQX.ActBottomDepth.ConversionFactor)) + + # replace ActivityTopDepthHeightMeasure.MeasureUnitCode values with unit argument + clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode.Original <- clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode + clean.data <- clean.data %>% + dplyr::relocate("ActivityBottomDepthHeightMeasure.MeasureUnitCode.Original", + .after = "WQX.ActBottomDepth.ConversionFactor" + ) + + clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode[which( + !is.na(clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode) + )] <- unit + + clean.data <- clean.data %>% + dplyr::relocate("ActivityBottomDepthHeightMeasure.MeasureUnitCode", + .after = "ActivityBottomDepthHeightMeasure.MeasureValue" + ) + # uncoment below to delete ActBottomDepth.Conversion.Unit column + #clean.data <- dplyr::select(clean.data, -"WQX.ActBottomDepth.ConversionFactor") + } + + #WQX.ResultDepth.ConversionFactor exists... + if (("WQX.ResultDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { + # multiply ResultDepthHeightMeasure.MeasureValue by WQX.ResultDepth.ConversionFactor + clean.data$ResultDepthHeightMeasure.MeasureValue <- ((clean.data$ResultDepthHeightMeasure.MeasureValue) * (clean.data$WQX.ResultDepth.ConversionFactor)) + + # replace ResultDepthHeightMeasure.MeasureUnitCode values with unit argument + clean.data$ResultDepthHeightMeasure.MeasureUnitCode.Original <- clean.data$ResultDepthHeightMeasure.MeasureUnitCode + clean.data <- clean.data %>% + dplyr::relocate("ResultDepthHeightMeasure.MeasureUnitCode.Original", + .after = "WQX.ResultDepth.ConversionFactor" + ) + + clean.data$ResultDepthHeightMeasure.MeasureUnitCode[which( + !is.na(clean.data$ResultDepthHeightMeasure.MeasureUnitCode) + )] <- unit + + clean.data <- clean.data %>% + dplyr::relocate("ResultDepthHeightMeasure.MeasureUnitCode", + .after = "ResultDepthHeightMeasure.MeasureUnitCode" + ) + # uncoment below to delete WQX.ResultDepth.ConversionFactor column + #clean.data <- dplyr::select(clean.data, -"WQX.ResultDepth.ConversionFactor") + } + + # uncomment below to delete WQX.Depth.TargetUnit column + # clean.data <- dplyr::select(clean.data, -"WQX.Depth.TargetUnit") return(clean.data) } else { stop("'transform' argument must be Boolean (TRUE or FALSE)") - } } } - #' Check for Special Characters in Measure Value Fields #' #' Function checks for special characters and non-numeric values in the diff --git a/R/Transformations.R b/R/Transformations.R index 5aafe84a..018a3b2d 100644 --- a/R/Transformations.R +++ b/R/Transformations.R @@ -312,7 +312,7 @@ WQXTargetUnits <- function(.data, transform = TRUE) { #' Function generates a harmonization reference table that is specific to #' the input dataset. Users can review how their input data relates to standard #' TADA values for CharacteristicName, ResultSampleFractionText, -#' MethodSpecicationName, and ResultMeasure.MeasureUnitCode and they can optionally +#' MethodSpecificationName, and ResultMeasure.MeasureUnitCode and they can optionally #' edit the reference file to meet their needs. #' #' @param .data TADA dataframe diff --git a/docs/articles/CONTRIBUTING.html b/docs/articles/CONTRIBUTING.html index fd22ab8c..0d374c16 100644 --- a/docs/articles/CONTRIBUTING.html +++ b/docs/articles/CONTRIBUTING.html @@ -71,7 +71,7 @@

Contributing

-

2022-10-17

+

2022-10-18

Source: vignettes/CONTRIBUTING.Rmd
CONTRIBUTING.Rmd
diff --git a/docs/articles/WQPDataHarmonization.html b/docs/articles/WQPDataHarmonization.html index 09fe4bc5..18782d7f 100644 --- a/docs/articles/WQPDataHarmonization.html +++ b/docs/articles/WQPDataHarmonization.html @@ -73,7 +73,7 @@

Cristina A. Mullin

-

2022-10-17

+

2022-10-18

Source: vignettes/WQPDataHarmonization.Rmd
WQPDataHarmonization.Rmd
@@ -113,28 +113,13 @@

Install and load packages 
 # remotes::install_github("USGS-R/dataRetrieval", dependencies=TRUE)
-# remotes::install_github("USEPA/TADA", dependencies=TRUE)
+remotes::install_github("USEPA/TADA", dependencies=TRUE)

Load the required libraries to run this vignette into your R session

 library(plyr)
 library(data.table)
 library(dplyr)
-#> 
-#> Attaching package: 'dplyr'
-#> The following objects are masked from 'package:data.table':
-#> 
-#>     between, first, last
-#> The following objects are masked from 'package:plyr':
-#> 
-#>     arrange, count, desc, failwith, id, mutate, rename, summarise,
-#>     summarize
-#> The following objects are masked from 'package:stats':
-#> 
-#>     filter, lag
-#> The following objects are masked from 'package:base':
-#> 
-#>     intersect, setdiff, setequal, union
 library(ggplot2)
 library(grDevices)
 library(magrittr)
@@ -143,137 +128,14 @@ 
Install and load packageslibrary(RColorBrewer)
 library(stats)
 library(lubridate)
-#> 
-#> Attaching package: 'lubridate'
-#> The following objects are masked from 'package:data.table':
-#> 
-#>     hour, isoweek, mday, minute, month, quarter, second, wday, week,
-#>     yday, year
-#> The following objects are masked from 'package:base':
-#> 
-#>     date, intersect, setdiff, union
 library(rlang)
-#> 
-#> Attaching package: 'rlang'
-#> The following object is masked from 'package:magrittr':
-#> 
-#>     set_names
-#> The following object is masked from 'package:data.table':
-#> 
-#>     :=
 library(tidyverse)
-#> ── Attaching packages
-#> ───────────────────────────────────────
-#> tidyverse 1.3.2 ──
-#> ✔ tibble  3.1.8     ✔ purrr   0.3.4
-#> ✔ tidyr   1.2.1     ✔ forcats 0.5.2
-#> ✔ readr   2.1.3     
-#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
-#> ✖ purrr::%@%()             masks rlang::%@%()
-#> ✖ rlang:::=()              masks data.table:::=()
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-#> ✖ lubridate::as.difftime() masks base::as.difftime()
-#> ✖ purrr::as_function()     masks rlang::as_function()
-#> ✖ dplyr::between()         masks data.table::between()
-#> ✖ purrr::compact()         masks plyr::compact()
-#> ✖ dplyr::count()           masks plyr::count()
-#> ✖ lubridate::date()        masks base::date()
-#> ✖ tidyr::extract()         masks magrittr::extract()
-#> ✖ dplyr::failwith()        masks plyr::failwith()
-#> ✖ dplyr::filter()          masks stats::filter()
-#> ✖ dplyr::first()           masks data.table::first()
-#> ✖ purrr::flatten()         masks rlang::flatten()
-#> ✖ purrr::flatten_chr()     masks rlang::flatten_chr()
-#> ✖ purrr::flatten_dbl()     masks rlang::flatten_dbl()
-#> ✖ purrr::flatten_int()     masks rlang::flatten_int()
-#> ✖ purrr::flatten_lgl()     masks rlang::flatten_lgl()
-#> ✖ purrr::flatten_raw()     masks rlang::flatten_raw()
-#> ✖ lubridate::hour()        masks data.table::hour()
-#> ✖ dplyr::id()              masks plyr::id()
-#> ✖ lubridate::intersect()   masks base::intersect()
-#> ✖ purrr::invoke()          masks rlang::invoke()
-#> ✖ lubridate::isoweek()     masks data.table::isoweek()
-#> ✖ dplyr::lag()             masks stats::lag()
-#> ✖ dplyr::last()            masks data.table::last()
-#> ✖ lubridate::mday()        masks data.table::mday()
-#> ✖ lubridate::minute()      masks data.table::minute()
-#> ✖ lubridate::month()       masks data.table::month()
-#> ✖ dplyr::mutate()          masks plyr::mutate()
-#> ✖ lubridate::quarter()     masks data.table::quarter()
-#> ✖ dplyr::rename()          masks plyr::rename()
-#> ✖ lubridate::second()      masks data.table::second()
-#> ✖ purrr::set_names()       masks rlang::set_names(), magrittr::set_names()
-#> ✖ lubridate::setdiff()     masks base::setdiff()
-#> ✖ purrr::splice()          masks rlang::splice()
-#> ✖ dplyr::summarise()       masks plyr::summarise()
-#> ✖ dplyr::summarize()       masks plyr::summarize()
-#> ✖ purrr::transpose()       masks data.table::transpose()
-#> ✖ lubridate::union()       masks base::union()
-#> ✖ lubridate::wday()        masks data.table::wday()
-#> ✖ lubridate::week()        masks data.table::week()
-#> ✖ lubridate::yday()        masks data.table::yday()
-#> ✖ lubridate::year()        masks data.table::year()
 library(knitr)
 library(rmarkdown)
 library(testthat)
-#> 
-#> Attaching package: 'testthat'
-#> 
-#> The following object is masked from 'package:purrr':
-#> 
-#>     is_null
-#> 
-#> The following objects are masked from 'package:readr':
-#> 
-#>     edition_get, local_edition
-#> 
-#> The following object is masked from 'package:tidyr':
-#> 
-#>     matches
-#> 
-#> The following objects are masked from 'package:rlang':
-#> 
-#>     is_false, is_null, is_true
-#> 
-#> The following objects are masked from 'package:magrittr':
-#> 
-#>     equals, is_less_than, not
-#> 
-#> The following object is masked from 'package:dplyr':
-#> 
-#>     matches
 library(usethis)
-#> 
-#> Attaching package: 'usethis'
-#> 
-#> The following object is masked from 'package:remotes':
-#> 
-#>     git_credentials
 library(devtools)
-#> 
-#> Attaching package: 'devtools'
-#> 
-#> The following object is masked from 'package:testthat':
-#> 
-#>     test_file
-#> 
-#> The following objects are masked from 'package:remotes':
-#> 
-#>     dev_package_deps, install_bioc, install_bitbucket, install_cran,
-#>     install_deps, install_dev, install_git, install_github,
-#>     install_gitlab, install_local, install_svn, install_url,
-#>     install_version, update_packages
 library(pkgdown)
-#> 
-#> Attaching package: 'pkgdown'
-#> 
-#> The following object is masked from 'package:devtools':
-#> 
-#>     build_site
-#> 
-#> The following object is masked from 'package:rmarkdown':
-#> 
-#>     clean_site
 library(Rcpp)
 library(spelling)
 library(dataRetrieval)
@@ -399,7 +261,7 @@ 
Retrieve WQP data
-# new_fullphyschem <- data.table::fread("https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET")
+# New_Draft_fullphyschem <- data.table::fread("https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET")

Option 3: If you need to download a large amount of data from across a large area, and the TADAdataRetrieval function is not working due to WQP timeout issues, then the TADABigdataRetrieval function may work @@ -564,7 +426,12 @@

Depth unit conversions +TADAProfileClean1 <- DepthProfileData(TADAProfile, unit = "m", transform = TRUE) +#> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: +#> provided 2 variables to replace 1 variables + +#> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: +#> provided 2 variables to replace 1 variables

Result unit conversions diff --git a/docs/index.html b/docs/index.html index ef555116..6b77e1a7 100644 --- a/docs/index.html +++ b/docs/index.html @@ -70,9 +70,9 @@

Welcome to TADA!

-

We encourage you to read this package’s CONTRIBUTING file, LICENSE, and README (you are here).

+

We encourage you to read this package’s CONTRIBUTING, LICENSE, and [README] information (https://usepa.github.io/TADA/index.html) (you are here).

TADA is a draft R package being developed to help States, Tribes, Tribal Nations, Pueblos, and other stakeholders more efficiently compile and evaluate Water Quality Portal (WQP) data collected from surface water monitoring sites. TADA is a building block to support future development of the TADA R Shiny application.

-

We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the CONTRIBUTING file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time.

+

We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the CONTRIBUTING file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time.

Water Quality Portal diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index cedff263..b7eefd98 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -4,7 +4,7 @@ pkgdown_sha: ~ articles: CONTRIBUTING: CONTRIBUTING.html WQPDataHarmonization: WQPDataHarmonization.html -last_built: 2022-10-17T18:24Z +last_built: 2022-10-18T21:13Z urls: reference: usepa.github.io/tada/reference article: usepa.github.io/tada/articles diff --git a/docs/readme.html b/docs/readme.html index 01aa9023..5985d50e 100644 --- a/docs/readme.html +++ b/docs/readme.html @@ -52,9 +52,9 @@

Welcome to TADA!

-

We encourage you to read this package’s CONTRIBUTING file, LICENSE, and README (you are here).

+

We encourage you to read this package’s CONTRIBUTING, LICENSE, and [README] information (https://usepa.github.io/TADA/index.html) (you are here).

TADA is a draft R package being developed to help States, Tribes, Tribal Nations, Pueblos, and other stakeholders more efficiently compile and evaluate Water Quality Portal (WQP) data collected from surface water monitoring sites. TADA is a building block to support future development of the TADA R Shiny application.

-

We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the CONTRIBUTING file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time.

+

We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the CONTRIBUTING file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time.

Water Quality Portal

diff --git a/docs/reference/DepthProfileData.html b/docs/reference/DepthProfileData.html index f1e0357e..e9494bd0 100644 --- a/docs/reference/DepthProfileData.html +++ b/docs/reference/DepthProfileData.html @@ -1,22 +1,22 @@ Depth Profile Flag & Unit Conversion — DepthProfileData • TADAGenerate Unique Harmonization Reference Table — HarmonizationRefTable • TADATADA Profile Check — TADAprofileCheck • TADAautoclean — TADAprofileCheck • TADA @@ -52,17 +50,16 @@
-

TADA Profile Check

+

autoclean

Source: R/DataDiscoveryRetrieval.R
TADAprofileCheck.Rd
-

This function checks if the column names in a dataframe include the TADA -profile fields. It is used at the beginning of TADA functions to ensure the -input data frame is suitable (i.e. is either the full physical/chemical -results profile downloaded from WQP or the TADA profile template downloaded -from the EPA TADA webpage.)

+

Removes complex biological data. Removes non-water media samples. +Removes rows of data that are true duplicates. Capitalizes fields to harmonize +data. This function includes and runs the TADA "MeasureValueSpecialCharacters" +function as well.

@@ -80,9 +77,34 @@

ArgumentsValue

+

cleaned TADA data profile

+ + +

TADA Profile Check

+ + +

This function checks if the column names in a dataframe include the TADA +profile fields. It is used at the beginning of TADA functions to ensure the +input data frame is suitable (i.e. is either the full physical/chemical +results profile downloaded from WQP or the TADA profile template downloaded +from the EPA TADA webpage.)

+ +

Boolean result indicating whether or not the input dataframe contains all of the TADA profile fields.

+
+

Details

+

Within "BiologicalIntentName", only the allowable values "tissue", "toxicity", +and "NA" apply to non-biological data (the function removes all others). +Toxicity and fish tissue data will be kept, but other types of biological +monitoring data will not.

+

We decided to make some fields uppercase that way they're more compatible +with the WQX validation reference tables and to avoid any issues with +case-sensitivity when joining data. Therefore, we might need to tack on any +immediate QA steps (removing true duplicates, converting result values to numeric, +capitalizing letters, etc.) to this function, as well as the other retrieval functions.

+
diff --git a/docs/reference/index.html b/docs/reference/index.html index 5fde3e9f..1fa37d86 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -218,7 +218,7 @@

All functionsTADAprofileCheck() -
TADA Profile Check
+
autoclean
TransformCensoredData() diff --git a/docs/search.json b/docs/search.json index 0135afe0..535c8e66 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contribute-to-tada","dir":"Articles","previous_headings":"","what":"Contribute to TADA!","title":"Contributing","text":"encourage read project’s CONTRIBUTING policy (), LICENSE, README. ’re glad ’re thinking contributing EPA open source project! ’re unsure anything, just ask — submit issue pull request anyway. worst can happen ’ll politely ask change something. appreciate friendly contributions. matter , spot error, omission, bug, ’re welcome open issue repo!","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"package-development","dir":"Articles","previous_headings":"","what":"Package Development","title":"Contributing","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"what-is-github","dir":"Articles","previous_headings":"","what":"What is GitHub?","title":"Contributing","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"required-installations","dir":"Articles","previous_headings":"","what":"Required Installations","title":"Contributing","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"issues","dir":"Articles","previous_headings":"","what":"Issues","title":"Contributing","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"branches","dir":"Articles","previous_headings":"","what":"Branches","title":"Contributing","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"additional-references","dir":"Articles","previous_headings":"","what":"Additional References","title":"Contributing","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"open-source-code-policy","dir":"Articles","previous_headings":"","what":"Open-Source Code Policy","title":"Contributing","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"license","dir":"Articles","previous_headings":"","what":"License","title":"Contributing","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"disclaimer","dir":"Articles","previous_headings":"","what":"Disclaimer","title":"Contributing","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contact","dir":"Articles","previous_headings":"","what":"Contact","title":"Contributing","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"WQP Data Harmonization","text":"vignette walk discover, wrangle, harmonize Water Quality Portal (WQP) data multiple organizations.","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"install-and-load-packages","dir":"Articles","previous_headings":"","what":"Install and load packages","title":"WQP Data Harmonization","text":"install TADA, currently need install GitHub using remotes (shown) devtools. dataRetrieval downloaded CRAN, development version can downloaded directly GitHub (un-comment). following code also install packages , load packages required run vignette R session. Load remotes library installing TADA dataRetrieval GitHub Uncomment lines install latest version TADA dataRetrieval GitHub. Load required libraries run vignette R session","code":"list.of.packages <- c(\"plyr\", \"data.table\", \"dataRetrieval\", \"dplyr\", \"ggplot2\", \"grDevices\", \"magrittr\", \"stringr\", \"utils\", \"RColorBrewer\", \"stats\", \"lubridate\", \"remotes\", \"rlang\", \"tidyverse\", \"knitr\", \"rmarkdown\", \"testthat\", \"usethis\", \"devtools\", \"pkgdown\", \"Rcpp\", \"spelling\") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,\"Package\"])] if(length(new.packages)) install.packages(new.packages) # If you have any issues loading the remotes library, uncomment the line below to install the \"remotes\" package specifying the repo # install.packages(\"remotes\", repos = \"http://cran.us.r-project.org\") library(remotes) # remotes::install_github(\"USGS-R/dataRetrieval\", dependencies=TRUE) # remotes::install_github(\"USEPA/TADA\", dependencies=TRUE) library(plyr) library(data.table) library(dplyr) #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:data.table': #> #> between, first, last #> The following objects are masked from 'package:plyr': #> #> arrange, count, desc, failwith, id, mutate, rename, summarise, #> summarize #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union library(ggplot2) library(grDevices) library(magrittr) library(stringr) library(utils) library(RColorBrewer) library(stats) library(lubridate) #> #> Attaching package: 'lubridate' #> The following objects are masked from 'package:data.table': #> #> hour, isoweek, mday, minute, month, quarter, second, wday, week, #> yday, year #> The following objects are masked from 'package:base': #> #> date, intersect, setdiff, union library(rlang) #> #> Attaching package: 'rlang' #> The following object is masked from 'package:magrittr': #> #> set_names #> The following object is masked from 'package:data.table': #> #> := library(tidyverse) #> ── Attaching packages #> ─────────────────────────────────────── #> tidyverse 1.3.2 ── #> ✔ tibble 3.1.8 ✔ purrr 0.3.4 #> ✔ tidyr 1.2.1 ✔ forcats 0.5.2 #> ✔ readr 2.1.3 #> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── #> ✖ purrr::%@%() masks rlang::%@%() #> ✖ rlang:::=() masks data.table:::=() #> ✖ dplyr::arrange() masks plyr::arrange() #> ✖ lubridate::as.difftime() masks base::as.difftime() #> ✖ purrr::as_function() masks rlang::as_function() #> ✖ dplyr::between() masks data.table::between() #> ✖ purrr::compact() masks plyr::compact() #> ✖ dplyr::count() masks plyr::count() #> ✖ lubridate::date() masks base::date() #> ✖ tidyr::extract() masks magrittr::extract() #> ✖ dplyr::failwith() masks plyr::failwith() #> ✖ dplyr::filter() masks stats::filter() #> ✖ dplyr::first() masks data.table::first() #> ✖ purrr::flatten() masks rlang::flatten() #> ✖ purrr::flatten_chr() masks rlang::flatten_chr() #> ✖ purrr::flatten_dbl() masks rlang::flatten_dbl() #> ✖ purrr::flatten_int() masks rlang::flatten_int() #> ✖ purrr::flatten_lgl() masks rlang::flatten_lgl() #> ✖ purrr::flatten_raw() masks rlang::flatten_raw() #> ✖ lubridate::hour() masks data.table::hour() #> ✖ dplyr::id() masks plyr::id() #> ✖ lubridate::intersect() masks base::intersect() #> ✖ purrr::invoke() masks rlang::invoke() #> ✖ lubridate::isoweek() masks data.table::isoweek() #> ✖ dplyr::lag() masks stats::lag() #> ✖ dplyr::last() masks data.table::last() #> ✖ lubridate::mday() masks data.table::mday() #> ✖ lubridate::minute() masks data.table::minute() #> ✖ lubridate::month() masks data.table::month() #> ✖ dplyr::mutate() masks plyr::mutate() #> ✖ lubridate::quarter() masks data.table::quarter() #> ✖ dplyr::rename() masks plyr::rename() #> ✖ lubridate::second() masks data.table::second() #> ✖ purrr::set_names() masks rlang::set_names(), magrittr::set_names() #> ✖ lubridate::setdiff() masks base::setdiff() #> ✖ purrr::splice() masks rlang::splice() #> ✖ dplyr::summarise() masks plyr::summarise() #> ✖ dplyr::summarize() masks plyr::summarize() #> ✖ purrr::transpose() masks data.table::transpose() #> ✖ lubridate::union() masks base::union() #> ✖ lubridate::wday() masks data.table::wday() #> ✖ lubridate::week() masks data.table::week() #> ✖ lubridate::yday() masks data.table::yday() #> ✖ lubridate::year() masks data.table::year() library(knitr) library(rmarkdown) library(testthat) #> #> Attaching package: 'testthat' #> #> The following object is masked from 'package:purrr': #> #> is_null #> #> The following objects are masked from 'package:readr': #> #> edition_get, local_edition #> #> The following object is masked from 'package:tidyr': #> #> matches #> #> The following objects are masked from 'package:rlang': #> #> is_false, is_null, is_true #> #> The following objects are masked from 'package:magrittr': #> #> equals, is_less_than, not #> #> The following object is masked from 'package:dplyr': #> #> matches library(usethis) #> #> Attaching package: 'usethis' #> #> The following object is masked from 'package:remotes': #> #> git_credentials library(devtools) #> #> Attaching package: 'devtools' #> #> The following object is masked from 'package:testthat': #> #> test_file #> #> The following objects are masked from 'package:remotes': #> #> dev_package_deps, install_bioc, install_bitbucket, install_cran, #> install_deps, install_dev, install_git, install_github, #> install_gitlab, install_local, install_svn, install_url, #> install_version, update_packages library(pkgdown) #> #> Attaching package: 'pkgdown' #> #> The following object is masked from 'package:devtools': #> #> build_site #> #> The following object is masked from 'package:rmarkdown': #> #> clean_site library(Rcpp) library(spelling) library(dataRetrieval) library(TADA)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"retrieve-wqp-data","dir":"Articles","previous_headings":"","what":"Retrieve WQP data","title":"WQP Data Harmonization","text":"WQP data retrieved processed compatibility TADA. function, TADAdataRetrieval builds USGS dataRetrieval package functions. joins three WQP profiles (.e., station, narrow, phys/chem), changes data Characteristic, Speciation, Fraction, Unit fields uppercase, removes true duplicates, removes data non-water media types, cleans results special characters. function uses inputs dataRetrieval readWQPdata function. readWQPdata restrict characteristics pulled Water Quality Portal (WQP). may specify desired characteristics using, instance: characteristicName = “pH”. Data retrieval filters include: statecode endDate startDate countycode siteid siteType characteristicName ActivityMediaName Please aware TADAdataRetrieval function automatically runs TADA autoclean MeasureValueSpecialCharacters functions well, required subsequent functions within TADA R package run. functions alter /add following WQP columns (enter ?MeasureValueSpecialCharacters ?autoclean console details): Alters (e.g., ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric) ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue Adds (data cleaning transformations done directly “ResultMeasureValue” “DetectionLimitMeasureValue” columns, however original “ResultMeasureValue” “DetectionLimitMeasureValue” columns values WQP preserved new fields, “ResultMeasureValue.Original” “DetectionLimitMeasureValue.Original”. Additionally, “TADA.ResultMeasureValue.Flag” “TADA.DetectionLimitMeasureValue.Flag” created track changes made “ResultMeasureValue” “DetectionLimitMeasureValue” columns; provide information result values needed address censored data later (.e., nondetections). Specifically, new columns flag special characters included result values, specifies special characters . ResultMeasureValue.Original TADA.ResultMeasureValue.Flag DetectionLimitMeasureValue.Original TADA.DetectionLimitMeasureValue.Flag Downloads using TADAdataRetrieval columns time, aware data uploaded Water Quality Portal individual organizations, may may follow conventions. Data metadata quality guaranteed! Make sure carefully explore data make conservative quality assurance decisions information limited. Tips: query filters WQP work within fields ORs. example: Characteristics: choose pH & - ’s . means retrieve pH data available. States: Similarly, choose VA IL, ’s . means retrieve VA IL data available. Combinations fields ANDs, State/VA Characteristic/”. means receive data available VA. “Characteristic” “Characteristic Type” also work . means Characteristic must fall within CharacteristicGroup filters used, get error. “siteid” general term WQP uses describe Site IDs USGS databases Monitoring Location Identifiers (Water Quality Portal). monitoring location Water Quality Portal (WQP) unique Monitoring Location Identifier, regardless database derives. Monitoring Location Identifier WQP concatenated Organization Identifier plus Site ID number. Site IDs include number unique identifiers monitoring locations within USGS NWIS EPA’s WQX databases separately. Additional resources: Review function documentation entering following code console: ?TADAdataRetrieval Introduction dataRetrieval package General Data Import Water Quality Portal Water Quality Portal Web Services Guide dataRetrieval Tutorial Option 1: Use TADAdataRetrieval function. Option 2: Alternatively, can use data.table::fread function read web service call WQP profile (un-comment). Option 3: need download large amount data across large area, TADAdataRetrieval function working due WQP timeout issues, TADABigdataRetrieval function may work better. function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested. See ?TADABigdataRetrieval details. WARNING, can take multiple hours run. total run time depends query inputs. Review column names TADA Profile","code":"#You can edit this to define your own WQP query inputs below TADAProfile <- TADAdataRetrieval(statecode = \"UT\", characteristicName = c(\"Ammonia\", \"Nitrate\", \"Nitrogen\"), startDate = \"01-01-2021\") # new_fullphyschem <- data.table::fread(\"https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET\") #AllWaterTempData <- TADABigdataRetrieval(startDate = \"2019-01-01\", endDate = \"2021-12-31\", characteristicName = \"Temperature, water\", siteType = \"Stream\") colnames(TADAProfile) #> [1] \"OrganizationIdentifier\" #> [2] \"OrganizationFormalName\" #> [3] \"ActivityIdentifier\" #> [4] \"ActivityTypeCode\" #> [5] \"ActivityMediaName\" #> [6] \"ActivityMediaSubdivisionName\" #> [7] \"ActivityStartDate\" #> [8] \"ActivityStartTime.Time\" #> [9] \"ActivityStartTime.TimeZoneCode\" #> [10] \"ActivityEndDate\" #> [11] \"ActivityEndTime.Time\" #> [12] \"ActivityEndTime.TimeZoneCode\" #> [13] \"ActivityDepthHeightMeasure.MeasureValue\" #> [14] \"ActivityDepthHeightMeasure.MeasureUnitCode\" #> [15] \"ActivityDepthAltitudeReferencePointText\" #> [16] \"ActivityTopDepthHeightMeasure.MeasureValue\" #> [17] \"ActivityTopDepthHeightMeasure.MeasureUnitCode\" #> [18] \"ActivityBottomDepthHeightMeasure.MeasureValue\" #> [19] \"ActivityBottomDepthHeightMeasure.MeasureUnitCode\" #> [20] \"ProjectIdentifier\" #> [21] \"ActivityConductingOrganizationText\" #> [22] \"MonitoringLocationIdentifier\" #> [23] \"ActivityCommentText\" #> [24] \"SampleAquifer\" #> [25] \"HydrologicCondition\" #> [26] \"HydrologicEvent\" #> [27] \"SampleCollectionMethod.MethodIdentifier\" #> [28] \"SampleCollectionMethod.MethodIdentifierContext\" #> [29] \"SampleCollectionMethod.MethodName\" #> [30] \"SampleCollectionEquipmentName\" #> [31] \"ResultDetectionConditionText\" #> [32] \"CharacteristicName\" #> [33] \"ResultSampleFractionText\" #> [34] \"ResultMeasureValue\" #> [35] \"ResultMeasureValue.Original\" #> [36] \"TADA.ResultMeasureValue.Flag\" #> [37] \"ResultMeasure.MeasureUnitCode\" #> [38] \"MeasureQualifierCode\" #> [39] \"ResultStatusIdentifier\" #> [40] \"StatisticalBaseCode\" #> [41] \"ResultValueTypeName\" #> [42] \"ResultWeightBasisText\" #> [43] \"ResultTimeBasisText\" #> [44] \"ResultTemperatureBasisText\" #> [45] \"ResultParticleSizeBasisText\" #> [46] \"PrecisionValue\" #> [47] \"ResultCommentText\" #> [48] \"USGSPCode\" #> [49] \"ResultDepthHeightMeasure.MeasureValue\" #> [50] \"ResultDepthHeightMeasure.MeasureUnitCode\" #> [51] \"ResultDepthAltitudeReferencePointText\" #> [52] \"SubjectTaxonomicName\" #> [53] \"SampleTissueAnatomyName\" #> [54] \"ResultAnalyticalMethod.MethodIdentifier\" #> [55] \"ResultAnalyticalMethod.MethodIdentifierContext\" #> [56] \"ResultAnalyticalMethod.MethodName\" #> [57] \"MethodDescriptionText\" #> [58] \"LaboratoryName\" #> [59] \"AnalysisStartDate\" #> [60] \"ResultLaboratoryCommentText\" #> [61] \"DetectionQuantitationLimitTypeName\" #> [62] \"DetectionQuantitationLimitMeasure.MeasureValue\" #> [63] \"DetectionLimitMeasureValue.Original\" #> [64] \"TADA.DetectionLimitMeasureValue.Flag\" #> [65] \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" #> [66] \"PreparationStartDate\" #> [67] \"ProviderName\" #> [68] \"timeZoneStart\" #> [69] \"timeZoneEnd\" #> [70] \"ActivityStartDateTime\" #> [71] \"ActivityEndDateTime\" #> [72] \"MonitoringLocationName\" #> [73] \"MonitoringLocationTypeName\" #> [74] \"MonitoringLocationDescriptionText\" #> [75] \"HUCEightDigitCode\" #> [76] \"DrainageAreaMeasure.MeasureValue\" #> [77] \"DrainageAreaMeasure.MeasureUnitCode\" #> [78] \"ContributingDrainageAreaMeasure.MeasureValue\" #> [79] \"ContributingDrainageAreaMeasure.MeasureUnitCode\" #> [80] \"LatitudeMeasure\" #> [81] \"LongitudeMeasure\" #> [82] \"SourceMapScaleNumeric\" #> [83] \"HorizontalAccuracyMeasure.MeasureValue\" #> [84] \"HorizontalAccuracyMeasure.MeasureUnitCode\" #> [85] \"HorizontalCollectionMethodName\" #> [86] \"HorizontalCoordinateReferenceSystemDatumName\" #> [87] \"VerticalMeasure.MeasureValue\" #> [88] \"VerticalMeasure.MeasureUnitCode\" #> [89] \"VerticalAccuracyMeasure.MeasureValue\" #> [90] \"VerticalAccuracyMeasure.MeasureUnitCode\" #> [91] \"VerticalCollectionMethodName\" #> [92] \"VerticalCoordinateReferenceSystemDatumName\" #> [93] \"CountryCode\" #> [94] \"StateCode\" #> [95] \"CountyCode\" #> [96] \"AquiferName\" #> [97] \"LocalAqfrName\" #> [98] \"FormationTypeText\" #> [99] \"AquiferTypeName\" #> [100] \"ConstructionDateText\" #> [101] \"WellDepthMeasure.MeasureValue\" #> [102] \"WellDepthMeasure.MeasureUnitCode\" #> [103] \"WellHoleDepthMeasure.MeasureValue\" #> [104] \"WellHoleDepthMeasure.MeasureUnitCode\" #> [105] \"MethodSpecificationName\" #> [106] \"ProjectName\" #> [107] \"ProjectDescriptionText\" #> [108] \"SamplingDesignTypeCode\" #> [109] \"QAPPApprovedIndicator\" #> [110] \"QAPPApprovalAgencyName\" #> [111] \"ProjectFileUrl\" #> [112] \"ProjectMonitoringLocationWeightingUrl\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"depth-unit-conversions","dir":"Articles","previous_headings":"","what":"Depth unit conversions","title":"WQP Data Harmonization","text":"Converts depth units consistent unit. ActivityDepthHeightMeasure.MeasureValue provides depth information. crucial column lake data less often river data. Function checks dataset depth profile data. depth profile columns populated, function appends ‘Conversion Factor’ columns populates columns based original unit (MeasureUnitCode columns) target unit, defined ‘unit’ argument. ‘Depth Target Unit’ column also appended, indicating unit selected depth data converted . transform = FALSE, output includes ‘Conversion Factor’ columns ‘Depth Target Unit’ column. transform = TRUE, output includes converted depth data ‘Depth Target Unit’ column, acts flag indicating rows converted. Default transform = TRUE. depth profile function can harmonize depth units across following fields (specific one): “ActivityDepthHeightMeasure”, “ActivityTopDepthHeightMeasure”, “ActivityBottomDepthHeightMeasure”, “ResultDepthHeightMeasure”). default . Allowable values ‘unit’ either ‘m’ (meter), ‘ft’ (feet), ‘’ (inch). ‘unit’ accepts one allowable value input. Default unit = “m”. See additional function documentation additional function options entering following code console: ?DepthProfileData","code":"#converts all depth profile data to meters TADAProfileClean1 <- DepthProfileData(TADAProfile, unit = \"m\", transform = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"result-unit-conversions","dir":"Articles","previous_headings":"","what":"Result unit conversions","title":"WQP Data Harmonization","text":"Converts results WQX target units. WQX target units pulled MeasureUnit domain table: https://cdx.epa.gov/wqx/download/DomainValues/MeasureUnit.CSV See additional function documentation additional function options entering following code console: ?WQXTargetUnits","code":"#Converts all results to WQX target units TADAProfileClean2 <- WQXTargetUnits(TADAProfileClean1, transform = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"statistically-aggregated-data","dir":"Articles","previous_headings":"","what":"Statistically aggregated data","title":"WQP Data Harmonization","text":"Checks removes statistically aggregated high frequency (.e., continuous) data, present. Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = “Reported Raw Data (attached)” clean = TRUE, rows aggregated continuous data removed dataset column appended Default clean = TRUE See function documentation additional function options entering following code console: ?DepthProfileData","code":"TADAProfileClean3 <- AggregatedContinuousData(TADAProfileClean2, clean = TRUE) #> [1] \"The dataset does not contain aggregated continuous data.\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-qaqc-service-result-flags","dir":"Articles","previous_headings":"","what":"WQX QAQC Service Result Flags","title":"WQP Data Harmonization","text":"Run following result functions address invalid method, fraction, speciation, unit metadata characteristic. default clean = TRUE, remove invalid results. can change clean = FALSE flag results, remove . See documentation details: ?InvalidMethod Clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidSpeciation clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidResultUnit clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidFraction clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended.","code":"TADAProfileClean4 <- InvalidMethod(TADAProfileClean3, clean = TRUE) #> [1] \"No changes were made, because we did not find any invalid method/characteristic combinations in your dataset.\" TADAProfileClean5 <- InvalidFraction(TADAProfileClean4, clean = TRUE) #> [1] \"All data is valid, therefore the function cannot be applied.\" TADAProfileClean6 <- InvalidSpeciation(TADAProfileClean5, clean = FALSE) TADAProfileClean7 <- InvalidResultUnit(TADAProfileClean6, clean = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-national-upper-and-lower-thresholds","dir":"Articles","previous_headings":"","what":"WQX national upper and lower thresholds","title":"WQP Data Harmonization","text":"Run following code flag remove results national upper lower bound characteristic unit combination. See documentation details: ?AboveNationalWQXUpperThreshold clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset. ?BelowNationalWQXUpperThreshold clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset. default clean=TRUE, can change flag results desired. Results flagged, removed, clean=FALSE.","code":"TADAProfileClean8 <- AboveNationalWQXUpperThreshold(TADAProfileClean7, clean = TRUE) TADAProfileClean9 <- BelowNationalWQXUpperThreshold(TADAProfileClean8, clean = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"potential-duplicates","dir":"Articles","previous_headings":"","what":"Potential duplicates","title":"WQP Data Harmonization","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. information, review documentation entering following console: ?PotentialDuplicateRowID clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":"TADAProfileClean10 <- PotentialDuplicateRowID(TADAProfileClean9)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"invalid-coordinates","dir":"Articles","previous_headings":"","what":"Invalid coordinates","title":"WQP Data Harmonization","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled “TADA.InvalidCoordinates” following flags (relevant dataset). latitude less zero, row flagged “LAT_OutsideUSA”. longitude greater zero less 145, row flagged “LONG_OutsideUSA”. latitude longitude contains string, “999”, row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged “Imprecise”.","code":"TADAProfileClean11 <- InvalidCoordinates(TADAProfileClean10, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"review-qapp-information","dir":"Articles","previous_headings":"","what":"Review QAPP information","title":"WQP Data Harmonization","text":"Check data approved QAPP function checks see information column “QAPPApprovedIndicator”. organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . field, Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. defaults remove rows data QAPPApprovedIndicator equals “N”. Users alternatively remove N’s NA’s using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function anything. Check see QAPP Doc Available function checks data submitted “ProjectFileUrl” column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":"TADAProfileClean12 <- QAPPapproved(TADAProfileClean11, clean = TRUE, cleanNA = FALSE) TADAProfileClean13 <- QAPPDocAvailable(TADAProfileClean12, clean = FALSE) #> Warning in QAPPDocAvailable(TADAProfileClean12, clean = FALSE): The dataset does #> not contain QAPP document url data."},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field","dir":"Articles","previous_headings":"","what":"Filter data by field","title":"WQP Data Harmonization","text":"section TADA user want review unique values specific fields may choose remove data particular values. start, review list fields number unique values field. Next, choose field list see unique values field, well number times value appears dataset. ’ll start ActivityTypeCode. list fields review: ResultCommentText often details relating additional QA. MeasureQualifierCode Contains information data flags 3. codes may designate suspect data flags may described detail ResultLaboratoryCommentText another column ActivityTypeCode field four unique values – “Sample-Routine”, “Quality Control Sample-Field Replicate”, “Field Msr/Obs”, “Quality Control Sample-Field Blank.” example want remove quality control values ActivityTypeCode field, therefore, ’ll specify want remove “Quality Control Sample-Field Replicate” “Quality Control Sample-Field Blank” values ActivityTypeCode field. ’ve completed review ActivityTypeCode field. Let’s move different field see values want remove – ’ll look values ResultStatusIdentifier field. ActivityMediaSubdivisionName field two unique values, “Surface Water” “Groundwater.” example want remove “Groundwater” values.","code":"FilterFields(TADAProfileClean13) #> FieldName Count #> 1 OrganizationFormalName 7 #> 2 ActivityTypeCode 7 #> 3 ActivityMediaName 1 #> 4 ActivityMediaSubdivisionName 4 #> 5 ActivityCommentText 4 #> 6 HydrologicCondition 8 #> 7 HydrologicEvent 4 #> 8 CharacteristicName 3 #> 9 MeasureQualifierCode 4 #> 10 SampleTissueAnatomyName 1 #> 11 LaboratoryName 11 #> 12 DetectionQuantitationLimitTypeName 7 #> 13 MonitoringLocationTypeName 14 #> 14 ProjectName 8 FilterFieldReview(\"ActivityTypeCode\", TADAProfileClean13) #> FieldValue Count #> 7 Sample-Routine 5268 #> 6 Sample-Integrated Vertical Profile 474 #> 4 Quality Control Sample-Field Replicate 454 #> 2 Quality Control Sample-Equipment Blank 276 #> 3 Quality Control Sample-Field Blank 60 #> 1 Field Msr/Obs 4 #> 5 Quality Control Sample-Lab Duplicate 2 TADAProfileClean14 <- dplyr::filter(TADAProfileClean13, !(ActivityTypeCode %in% c(\"Quality Control Sample-Field Replicate\", \"Quality Control Sample-Field Blank\", \"Quality Control Sample-Lab Duplicate\", \"Quality Control Sample-Equipment Blank\"))) FilterFieldReview(\"ActivityMediaSubdivisionName\", TADAProfileClean14) #> FieldValue Count #> 3 Surface Water 687 #> 2 Groundwater 106 #> 1 Bulk deposition 1 TADAProfileClean15 <- dplyr::filter(TADAProfileClean14, !(ActivityMediaSubdivisionName %in% c(\"Groundwater\", \"Bulk deposition\")))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field-subset-by-parameter","dir":"Articles","previous_headings":"","what":"Filter data by field, subset by parameter","title":"WQP Data Harmonization","text":"section TADA user want select parameter, review unique values associated parameter specific fields, choose remove particular values. start, review list parameters dataset. (list sorted highest lowest counts. first rows displayed save space page) Next, select parameter. Let’s explore fields associated Nitrogen: Selecting parameter generates list , subset selected parameter, fields number unique values field. choose field list. example ’ll remove certain values HydrologicEvent field. HydrologicEvent field three unique values. example want remove samples collected “Storm” events. Therefore, ’ll specify want remove rows CharacteristicName “NITROGEN” HydrologicEvent field “Storm.”","code":"FilterParList(TADAProfileClean15) #> FieldValue Count #> 3 NITROGEN 4130 #> 2 NITRATE 1479 #> 1 AMMONIA 30 FilterParFields(TADAProfileClean15, \"NITROGEN\") #> FieldName Count #> 1 ActivityTypeCode 2 #> 2 ActivityMediaName 1 #> 3 ActivityMediaSubdivisionName 2 #> 4 ActivityCommentText 3 #> 5 HydrologicCondition 7 #> 6 HydrologicEvent 2 #> 7 SampleCollectionMethod.MethodIdentifier 6 #> 8 SampleCollectionMethod.MethodIdentifierContext 2 #> 9 SampleCollectionMethod.MethodName 6 #> 10 SampleCollectionEquipmentName 6 #> 11 ResultSampleFractionText 3 #> 12 ResultMeasure.MeasureUnitCode 2 #> 13 MeasureQualifierCode 3 #> 14 ResultStatusIdentifier 2 #> 15 ResultValueTypeName 1 #> 16 ResultWeightBasisText 1 #> 17 ResultTemperatureBasisText 1 #> 18 ResultParticleSizeBasisText 1 #> 19 ResultCommentText 7 #> 20 ResultAnalyticalMethod.MethodIdentifier 2 #> 21 ResultAnalyticalMethod.MethodIdentifierContext 2 #> 22 ResultAnalyticalMethod.MethodName 2 #> 23 MethodDescriptionText 1 #> 24 LaboratoryName 2 #> 25 ResultLaboratoryCommentText 5 #> 26 DetectionQuantitationLimitTypeName 2 #> 27 MonitoringLocationTypeName 11 FilterParFieldReview(\"HydrologicEvent\", TADAProfileClean15, \"NITROGEN\") #> FieldValue Count #> 1 Routine sample 59 TADAProfileClean16 <- dplyr::filter(TADAProfileClean15, !(CharacteristicName %in% \"NITROGEN\" & HydrologicEvent %in% \"Storm\"))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"transform-characteristic-speciation-and-unit-values-to-tada-standards","dir":"Articles","previous_headings":"","what":"Transform Characteristic, Speciation, and Unit values to TADA Standards","title":"WQP Data Harmonization","text":"HarmonizeRefTable function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values following elements: CharacteristicName ResultSampleFractionText MethodSpecicationName ResultMeasure.MeasureUnitCode HarmonizeData function compares input dataset TADA Harmonization Reference Table. purpose function make similar data consistent therefore easier compare analyze. Users can also edit reference file meet needs desired. download argument can used save harmonization file current working directory download = TRUE, default download = FALSE. Optional outputs include: dataset Harmonization columns appended, datset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE. examples HarmonizeData function can used: ResultSampleFractionText specifies forms constituents. cases, single CharacteristicName “Total” “Dissolved” forms specified, combined. cases, CharacteristicName ResultSampleFractionText combination given different identifier. identifier can used later identify comparable data groups calculating statistics creating figures combination. variables different names represent constituent (e.g., “Total Kjeldahl nitrogen (Organic N & NH3)” “Kjeldahl nitrogen”). HarmonizeData function gives consistent name (identifier) synonyms.","code":"UniqueHarmonizationRef <- HarmonizationRefTable(TADAProfileClean16, download = FALSE) TADAProfileClean17 <- HarmonizeData(TADAProfileClean16, ref = UniqueHarmonizationRef, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Cristina Mullin. Author, maintainer. Michelle Thawley. Author. Laura Shumway. Author. Jacob Greif. Author.","code":""},{"path":"usepa.github.io/tada/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Mullin, C.., Greif, J., Thawley, M., Shumway, L., 2022, TADA: R Tools Automated Data Assessment, U.S. Environmental Protection Agency, Washington, DC","code":"@Manual{, author = {Cristina A. Mullin and Jacob Greif and Michelle Thawley and Laura Shumway}, title = {TADA: R Tools for Automated Data Assessment}, address = {Washington, DC}, institution = {U.S. Environmental Protection Agency}, year = {2022}, url = {https://github.com/USEPA/TADA}, }"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"package-development","dir":"","previous_headings":"","what":"Package Development","title":"NA","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"what-is-github","dir":"","previous_headings":"","what":"What is GitHub?","title":"NA","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"required-installations","dir":"","previous_headings":"","what":"Required Installations","title":"NA","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"NA","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"branches","dir":"","previous_headings":"","what":"Branches","title":"NA","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"additional-references","dir":"","previous_headings":"","what":"Additional References","title":"NA","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/index.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"Tools for Automated Data Assessment R Package","text":"encourage read package’s CONTRIBUTING file, LICENSE, README (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/index.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"Tools for Automated Data Assessment R Package","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Tools for Automated Data Assessment R Package","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/index.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"Tools for Automated Data Assessment R Package","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Tools for Automated Data Assessment R Package","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/index.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"Tools for Automated Data Assessment R Package","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Tools for Automated Data Assessment R Package","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":[]},{"path":"usepa.github.io/tada/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"CC0 1.0 Universal","title":"CC0 1.0 Universal","text":"CREATIVE COMMONS CORPORATION LAW FIRM PROVIDE LEGAL SERVICES. DISTRIBUTION DOCUMENT CREATE ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES INFORMATION “-” BASIS. CREATIVE COMMONS MAKES WARRANTIES REGARDING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER, DISCLAIMS LIABILITY DAMAGES RESULTING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER.","code":""},{"path":"usepa.github.io/tada/LICENSE.html","id":"statement-of-purpose","dir":"","previous_headings":"","what":"Statement of Purpose","title":"CC0 1.0 Universal","text":"laws jurisdictions throughout world automatically confer exclusive Copyright Related Rights (defined ) upon creator subsequent owner(s) (, “owner”) original work authorship /database (, “Work”). 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Affirmer disclaims responsibility clearing rights persons may apply Work use thereof, including without limitation person’s Copyright Related Rights Work. , Affirmer disclaims responsibility obtaining necessary consents, permissions rights required use Work. Affirmer understands acknowledges Creative Commons party document duty obligation respect CC0 use Work.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"NA","text":"encourage read package’s CONTRIBUTING file, LICENSE, README (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"NA","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"NA","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/readme.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data upper threshold result values submitted WQX given characteristic. clean = TRUE, rows values upper WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"","code":"AboveNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data upper WQX threshold dataset clean = TRUE. Default clean = TRUE","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Aggregated Continuous Data — AggregatedContinuousData","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = \"Reported Raw Data (attached)\". clean = TRUE, rows aggregated continuous data removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"","code":"AggregatedContinuousData(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":".data TADA dataframe clean Boolean argument; removes aggregated continuous data dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"clean = FALSE, column flagging rows aggregated continuous data appended input data set. clean = TRUE, aggregated continuous data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — autoclean","title":"autoclean — autoclean","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — autoclean","text":"","code":"autoclean(.data)"},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — autoclean","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — autoclean","text":"autocleaned TADA data profile","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — autoclean","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":null,"dir":"Reference","previous_headings":"","what":"AutoFilter — AutoFilter","title":"AutoFilter — AutoFilter","text":"Function can used autofilter simplify WQP dataset. applying function, dataset contain result values water media types chemicals tissue (e.g. mercury fish tissue). complex biological data (counts macroinvertebrates) removed. function looks following fields autofilter: ActivityMediaName, ActivityMediaSubDivisionName, AssemblageSampledName","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AutoFilter — AutoFilter","text":"","code":"AutoFilter(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AutoFilter — AutoFilter","text":".data TADA dataframe clean Indicates whether flag columns appended data (clean = FALSE), flagged data transformed/filtered dataset columns appended (clean = TRUE).","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"AutoFilter — AutoFilter","text":"clean = FALSE, flag column appended dataset. clean = TRUE, flag column appended relevant rows removed.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data lower threshold result values submitted WQX given characteristic. clean = TRUE, rows values lower WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"","code":"BelowNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data lower WQX threshold dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalnumcount — decimalnumcount","title":"decimalnumcount — decimalnumcount","text":"character data type","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalnumcount — decimalnumcount","text":"","code":"decimalnumcount(x)"},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalnumcount — decimalnumcount","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalnumcount — decimalnumcount","text":"Number values right decimal point character type data.","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalplaces — decimalplaces","title":"decimalplaces — decimalplaces","text":"numeric data type","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalplaces — decimalplaces","text":"","code":"decimalplaces(x)"},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalplaces — decimalplaces","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalplaces — decimalplaces","text":"Number values right decimal point numeric type data.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":null,"dir":"Reference","previous_headings":"","what":"Depth Profile Flag & Unit Conversion — DepthProfileData","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Function checks dataset depth profile data. depth profile columns populated, function appends 'Conversion Factor' columns populates columns based original unit (MeasureUnitCode columns) target unit, defined 'unit' argument. 'Depth Target Unit' column also appended, indicating unit selected depth data converted . transform = FALSE, output includes 'Conversion Factor' columns 'Depth Target Unit' column. transform = TRUE, output includes converted depth data 'Depth Target Unit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"","code":"DepthProfileData( .data, unit = \"m\", fields = c(\"ActivityDepthHeightMeasure\", \"ActivityTopDepthHeightMeasure\", \"ActivityBottomDepthHeightMeasure\", \"ResultDepthHeightMeasure\"), transform = TRUE )"},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":".data TADA dataframe unit Character string input indicating uniform unit depth data converted . Allowable values 'unit' either 'm' (meter), 'ft' (feet), '' (inch). 'unit' accepts one allowable value input. Default unit = \"m\". fields Character string input indicating depth fields checked data. Allowable values 'fields' 'ActivityDepthHeightMeasure,' 'ActivityTopDepthHeightMeasure,' 'ActivityBottomDepthHeightMeasure,' 'ResultDepthHeightMeasure.'. Default include allowable values. transform Boolean argument; transform = FALSE, output includes Conversion Factor' columns 'Depth Target Unit' column. transform = TRUE, output includes converted depth data 'Depth Target Unit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Full dataset converted uniform depth units 'Depth Target Unit' column, acts flag indicating rows converted. transform = FALSE, output full dataset 'Conversion Factor' columns 'Depth Target Unit' column.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field — FilterFieldReview","title":"Generate list of unique values in a given field — FilterFieldReview","text":"Function creates table pie chart unique values, counts values chosen field dataframe.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field — FilterFieldReview","text":"","code":"FilterFieldReview(field, .data)"},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field — FilterFieldReview","text":"field Field name .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field — FilterFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names — FilterFields","title":"Generate list of field names — FilterFields","text":"Function creates list fields input dataframe well number unique values field. list intended inform users specific fields explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names — FilterFields","text":"","code":"FilterFields(.data)"},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names — FilterFields","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names — FilterFields","text":"table fields count unique values field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"Function creates table pie chart unique values, counts values, chosen field dataframe subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"","code":"FilterParFieldReview(field, .data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"field Field name .data Optional argument; TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names subset by parameter — FilterParFields","title":"Generate list of field names subset by parameter — FilterParFields","text":"Function subsets input dataframe input parameter creates list fields subset dataframe well number unique values field. list intended inform users specific fields explore filter subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names subset by parameter — FilterParFields","text":"","code":"FilterParFields(.data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names subset by parameter — FilterParFields","text":".data TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names subset by parameter — FilterParFields","text":"table fields count unique values field, subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of parameters — FilterParList","title":"Generate list of parameters — FilterParList","text":"Function generates list characteristics input dataset, well number records . list intended inform users parameters explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of parameters — FilterParList","text":"","code":"FilterParList(.data)"},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of parameters — FilterParList","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of parameters — FilterParList","text":"list unique characteristics counts","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":null,"dir":"Reference","previous_headings":"","what":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Function summarizes censored data dataset, including substitutions made.","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"","code":"GenerateCensoredDataStats(.data)"},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":".data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Summary table","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table — GetMeasureUnitRef","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"Function downloads returns latest WQX MeasureUnit Domain table, adds additional target unit information, writes data sysdata.rda.","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"","code":"GetMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"sysdata.rda updated WQXunitRef object (unit conversion reference table)","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Function downloads returns newest available (cleaned) raw Water Quality Exchange (WQX) QAQC Characteristic Validation reference table. WQXcharValRef data frame contains information four functions: InvalidFraction, InvalidResultUnit, InvalidSpeciation, UncommonAnalyticalMethodID.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"","code":"GetWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Updated sysdata.rda updated WQXcharValRef object","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values CharacteristicName, ResultSampleFractionText, MethodSpecicationName, ResultMeasure.MeasureUnitCode can optionally edit reference file meet needs.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"","code":"HarmonizationRefTable(.data, download = FALSE)"},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":".data TADA dataframe download Boolean argument; download = TRUE, output downloaded current working directory.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Harmonization Reference Table unique input dataset","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"Function compares input dataset TADA Harmonization Reference Table, makes synonymous data consistent. Optional outputs include: 1) dataset Harmonization columns appended, 2) dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards 3) four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"","code":"HarmonizeData(.data, ref, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":".data TADA dataframe ref Optional argument specify dataframe use reference file. primary use argument user generated harmonization reference file unique data, made changes file. transform Boolean argument; transforms /converts original values dataset TADA Harmonization Reference Table values following fields: CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode. Default transform = TRUE. flag Boolean argument; appends columns TADA Harmonization Reference Table dataframe. Default flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"transform = FALSE flag = TRUE, Harmonization Reference Table columns appended dataset . transform = TRUE flag = TRUE, Harmonization columns appended dataset transformations executed. transform = TRUE flag = FALSE, transformations executed . transform = FALSE flag = FALSE, error returned (function return input dataframe unchanged input allowed).","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":null,"dir":"Reference","previous_headings":"","what":"Invalid coordinates — InvalidCoordinates","title":"Invalid coordinates — InvalidCoordinates","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled \"TADA.InvalidCoordinates\" following flags (relevant dataset). latitude less zero, row flagged \"LAT_OutsideUSA\". longitude greater zero less 145, row flagged \"LONG_OutsideUSA\". latitude longitude contains string, \"999\", row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged \"Imprecise\".","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Invalid coordinates — InvalidCoordinates","text":"","code":"InvalidCoordinates(.data, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Invalid coordinates — InvalidCoordinates","text":".data TADA dataframe clean_outsideUSA Boolean argument; removes data coordinates outside United States clean_outsideUSA = TRUE. Default clean = FALSE. clean_imprecise Boolean arguments; removes imprecise data clean_imprecise = TRUE. Default clean_imprecise = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Invalid coordinates — InvalidCoordinates","text":"either clean_outsideUSA clean_imprecise argument FALSE, column flagging rows respective QA check appended input dataset. either argument TRUE, \"invalid\" \"imprecise\" data removed, respectively.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Sample Fraction Validity — InvalidFraction","title":"Check Sample Fraction Validity — InvalidFraction","text":"Function checks validity characteristic-fraction combination dataset. clean = TRUE, rows invalid characteristic-fraction combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Sample Fraction Validity — InvalidFraction","text":"","code":"InvalidFraction(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Sample Fraction Validity — InvalidFraction","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-fraction combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Sample Fraction Validity — InvalidFraction","text":"clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Invalid Analytical Methods — InvalidMethod","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"Function checks validity characteristic-analytical method combination dataset. clean = TRUE, rows invalid characteristic-analytical method combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"","code":"InvalidMethod(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Invalid Analytical Methods — InvalidMethod","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-analytical method combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Unit Validity — InvalidResultUnit","title":"Check Result Unit Validity — InvalidResultUnit","text":"Function checks validity characteristic-media-result unit combination dataset. clean = TRUE, rows invalid characteristic-media-result unit combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Unit Validity — InvalidResultUnit","text":"","code":"InvalidResultUnit(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Unit Validity — InvalidResultUnit","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-media-result unit combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Unit Validity — InvalidResultUnit","text":"clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Method Speciation Validity — InvalidSpeciation","title":"Check Method Speciation Validity — InvalidSpeciation","text":"Function checks validity characteristic-method speciation combination dataset. clean = TRUE, rows invalid characteristic-method speciation combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Method Speciation Validity — InvalidSpeciation","text":"","code":"InvalidSpeciation(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Method Speciation Validity — InvalidSpeciation","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-method speciation combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Method Speciation Validity — InvalidSpeciation","text":"#'clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Function checks special characters non-numeric values ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields appends flag columns indicating special characters included , special characters . ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields also converted class numeric.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"","code":"MeasureValueSpecialCharacters(.data)"},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Full dataset column indicating presence special characters ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields. Additionally, ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric, copies column created preserve original character values.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"usepa.github.io/tada/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Potential Duplicates — PotentialDuplicateRowID","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"","code":"PotentialDuplicateRowID(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":".data TADA dataframe clean Boolean argument; removes potential duplicate data dataset clean = TRUE. clean = FALSE, column indicating potential duplicate rows unique number linking rows appended input data set. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":null,"dir":"Reference","previous_headings":"","what":"Check data for an approved QAPP — QAPPapproved","title":"Check data for an approved QAPP — QAPPapproved","text":"Function checks data submitted column \"QAPPApprovedIndicator\". organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. default removes rows data QAPPApprovedIndicator equals \"N\". Users alternatively remove N's NA's using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function make changes data.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check data for an approved QAPP — QAPPapproved","text":"","code":"QAPPapproved(.data, clean = TRUE, cleanNA = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check data for an approved QAPP — QAPPapproved","text":".data TADA dataframe clean Boolean argument two possible values called \"TRUE\" \"FALSE\". clean=TRUE, rows data QAPPApprovedIndicator equals \"N\" removed. , clean=FALSE, rows data QAPPApprovedIndicator equals \"N\" retained. cleanNA Boolean argument two possible values called \"TRUE\" \"FALSE\". cleanNA=TRUE, rows data QAPPApprovedIndicator equals \"NA\" removed. , cleanNA=FALSE, rows data QAPPApprovedIndicator equals \"NA\" retained.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check data for an approved QAPP — QAPPapproved","text":"clean = FALSE cleanNA = FALSE, data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check data for an approved QAPP — QAPPapproved","text":"Note: required field, often left blank (NA) even data associated QAPP. states tribes collect monitoring data using 106 funding (almost state tribal data WQX) required EPA approved QAPP receive 106 funding. Therefore, organizations data approved QAPP even data submitted WQP NA.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"Function checks data submitted \"ProjectFileUrl\" column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"","code":"QAPPDocAvailable(.data, clean = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":".data TADA dataframe clean Boolean argument; removes data without associated QAPP document dataset clean = TRUE. Default clean = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"clean = FALSE, column appended input data set flags rows associated QAPP document. clean = TRUE, data without associated QAPP document removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":null,"dir":"Reference","previous_headings":"","what":"Read in WQP data using WQP web services directly — readWQPwebservice","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Go WQP website (https://www.waterqualitydata.us/) fill advanced query form. Choose Full Physical Chemical Data Profile, data sources, file format Comma-Separated. finished, hit download button. Instead, copy web service URL located bottom page header \"Result\". Use \"Result\" web service URL input function download data directly R.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"","code":"readWQPwebservice(webservice)"},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"webservice WQP Web Service URL, entered within quotes \"url\"","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"WQP Full Physical Chemical Results Data Profile","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Note: may useful save Query URL well comment within code. URL return WQP query page original data filters.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"RemoveEmptyColumns — RemoveEmptyColumns","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Removes columns NA values. Used quickly reduce number columns dataframe improve management readability dataset.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"","code":"RemoveEmptyColumns(.data)"},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":".data Dataframe","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Full dataset empty data columns removed","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"TADABigdataRetrieval( startDate = \"null\", endDate = \"null\", characteristicName = \"null\", siteType = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"startDate Start Date YYYY-MM-DD format, example, \"1995-01-01\" endDate end date YYYY-MM-DD format, example, \"2020-12-31\" characteristicName Name water quality parameter siteType Name water body type (e.g., \"Stream\", \"Lake, Reservoir, Impoundment\")","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"Similarly TADAdataRetrieval function, function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"if (FALSE) { tada2 <- TADABigdataRetrieval(startDate = \"01-01-2021\", endDate = \"01-01-2022\", characteristicName = \"Nitrogen\", siteType = \"Stream\") }"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Retrieve data Water Quality Portal (WQP) output TADA-compatible dataset.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"TADAdataRetrieval( statecode = \"null\", startDate = \"null\", countycode = \"null\", siteid = \"null\", siteType = \"null\", characteristicName = \"null\", ActivityMediaName = \"null\", endDate = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"statecode Code identifies state startDate Start Date countycode Code identifies county siteid Unique monitoring station identifier siteType Type waterbody characteristicName Name parameter ActivityMediaName Sampling substrate water, air, sediment endDate End Date","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Keep mind query filters WQP work within fields ORs. example, characteristics – choose pH & – ’s . Similarly, choose VA IL, ’s . combo fields ANDs. State/VA Characteristic/\". \"Characteristic\" \"Characteristic Group\" also work . function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"if (FALSE) { tada1 <- TADAdataRetrieval(statecode = \"WI\", countycode = \"Dane\", characteristicName = \"Phosphorus\") }"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":null,"dir":"Reference","previous_headings":"","what":"TADA Profile Check — TADAprofileCheck","title":"TADA Profile Check — TADAprofileCheck","text":"function checks column names dataframe include TADA profile fields. used beginning TADA functions ensure input data frame suitable (.e. either full physical/chemical results profile downloaded WQP TADA profile template downloaded EPA TADA webpage.)","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"TADA Profile Check — TADAprofileCheck","text":"","code":"TADAprofileCheck(.data)"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"TADA Profile Check — TADAprofileCheck","text":".data dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"TADA Profile Check — TADAprofileCheck","text":"Boolean result indicating whether input dataframe contains TADA profile fields.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":null,"dir":"Reference","previous_headings":"","what":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"Function substitutes monitoring device/method detection limits (available) result values applicable.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"","code":"TransformCensoredData(transform, .data)"},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE. .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform=TRUE, monitoring device/method detection limits (available) substituted result values units. transform = FALSE, monitoring device/method detection limits (available) substituted result values units - Instead, columns appended rows may include censored data. flag indicates 1) row contains censored data, 2) monitoring device/method detection limits available.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Existing Data in sysdata.rda — UpdateInternalData","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Function internal use . used internal functions used update internal data (e.g. reference tables). function adapted stackoverflow.com thread, can accessed .","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"","code":"UpdateInternalData(..., list = character())"},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"... Objects updated sysdata.rda. list Argument indicating data class list.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Updated sysdata.rda file","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"Update Measure Unit Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"","code":"UpdateMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"Update Characteristic Validation Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"","code":"UpdateWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"Used store cached WQX QAQC Characteristic Validation Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"","code":"WQXCharValRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"object class NULL length 0.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Units to WQX Target Units — WQXTargetUnits","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function compares measure units input data Water Quality Exchange (WQX) 3.0 QAQC Characteristic Validation table.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"","code":"WQXTargetUnits(.data, transform = TRUE)"},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":".data TADA dataset transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"transform=TRUE, result values units converted WQX target units. function changes values within \"ResultMeasure.MeasureUnitCode\" \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" WQX target units converts respective values within \"ResultMeasureValue\" \"DetectionQuantitationLimitMeasure.MeasureValue\" fields. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=TRUE add following two fields input dataset, \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\", retain original result unit values. transform = FALSE, result values units converted WQX target units, columns appended indicate target units conversion factors , data can converted. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=FALSE add following two fields input dataset: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function ALWAYS add following two columns input dataset: \"WQX.ResultMeasureValue.UnitConversion\", \"WQX.DetectionLimitMeasureValue.UnitConversion\" two fields indicate data can converted.\"NoResultValue\" means data converted ResultMeasureValue, \"NoTargetUnit\" means data converted original unit associated target unit WQX. \"Convert\" means data can transformed, \"Converted\" means function run input transform = TRUE, values already converted. also uses following six fields input dataset: \"CharacteristicName\", \"ActivityMediaName\", \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" function adds following two fields transforms values within following four fields transform=TRUE: Adds: \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\". Transforms: \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\". function adds following two fields transform=FALSE: Adds: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"Used store cached Measure Unit Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"","code":"WQXunitRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"object class NULL length 0.","code":""}] +[{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contribute-to-tada","dir":"Articles","previous_headings":"","what":"Contribute to TADA!","title":"Contributing","text":"encourage read project’s CONTRIBUTING policy (), LICENSE, README. ’re glad ’re thinking contributing EPA open source project! ’re unsure anything, just ask — submit issue pull request anyway. worst can happen ’ll politely ask change something. appreciate friendly contributions. matter , spot error, omission, bug, ’re welcome open issue repo!","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"package-development","dir":"Articles","previous_headings":"","what":"Package Development","title":"Contributing","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"what-is-github","dir":"Articles","previous_headings":"","what":"What is GitHub?","title":"Contributing","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"required-installations","dir":"Articles","previous_headings":"","what":"Required Installations","title":"Contributing","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"issues","dir":"Articles","previous_headings":"","what":"Issues","title":"Contributing","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"branches","dir":"Articles","previous_headings":"","what":"Branches","title":"Contributing","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"additional-references","dir":"Articles","previous_headings":"","what":"Additional References","title":"Contributing","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"open-source-code-policy","dir":"Articles","previous_headings":"","what":"Open-Source Code Policy","title":"Contributing","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"license","dir":"Articles","previous_headings":"","what":"License","title":"Contributing","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"disclaimer","dir":"Articles","previous_headings":"","what":"Disclaimer","title":"Contributing","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contact","dir":"Articles","previous_headings":"","what":"Contact","title":"Contributing","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"WQP Data Harmonization","text":"vignette walk discover, wrangle, harmonize Water Quality Portal (WQP) data multiple organizations.","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"install-and-load-packages","dir":"Articles","previous_headings":"","what":"Install and load packages","title":"WQP Data Harmonization","text":"install TADA, currently need install GitHub using remotes (shown) devtools. dataRetrieval downloaded CRAN, development version can downloaded directly GitHub (un-comment). following code also install packages , load packages required run vignette R session. Load remotes library installing TADA dataRetrieval GitHub Uncomment lines install latest version TADA dataRetrieval GitHub. Load required libraries run vignette R session","code":"list.of.packages <- c(\"plyr\", \"data.table\", \"dataRetrieval\", \"dplyr\", \"ggplot2\", \"grDevices\", \"magrittr\", \"stringr\", \"utils\", \"RColorBrewer\", \"stats\", \"lubridate\", \"remotes\", \"rlang\", \"tidyverse\", \"knitr\", \"rmarkdown\", \"testthat\", \"usethis\", \"devtools\", \"pkgdown\", \"Rcpp\", \"spelling\") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,\"Package\"])] if(length(new.packages)) install.packages(new.packages) # If you have any issues loading the remotes library, uncomment the line below to install the \"remotes\" package specifying the repo # install.packages(\"remotes\", repos = \"http://cran.us.r-project.org\") library(remotes) # remotes::install_github(\"USGS-R/dataRetrieval\", dependencies=TRUE) remotes::install_github(\"USEPA/TADA\", dependencies=TRUE) library(plyr) library(data.table) library(dplyr) library(ggplot2) library(grDevices) library(magrittr) library(stringr) library(utils) library(RColorBrewer) library(stats) library(lubridate) library(rlang) library(tidyverse) library(knitr) library(rmarkdown) library(testthat) library(usethis) library(devtools) library(pkgdown) library(Rcpp) library(spelling) library(dataRetrieval) library(TADA)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"retrieve-wqp-data","dir":"Articles","previous_headings":"","what":"Retrieve WQP data","title":"WQP Data Harmonization","text":"WQP data retrieved processed compatibility TADA. function, TADAdataRetrieval builds USGS dataRetrieval package functions. joins three WQP profiles (.e., station, narrow, phys/chem), changes data Characteristic, Speciation, Fraction, Unit fields uppercase, removes true duplicates, removes data non-water media types, cleans results special characters. function uses inputs dataRetrieval readWQPdata function. readWQPdata restrict characteristics pulled Water Quality Portal (WQP). may specify desired characteristics using, instance: characteristicName = “pH”. Data retrieval filters include: statecode endDate startDate countycode siteid siteType characteristicName ActivityMediaName Please aware TADAdataRetrieval function automatically runs TADA autoclean MeasureValueSpecialCharacters functions well, required subsequent functions within TADA R package run. functions alter /add following WQP columns (enter ?MeasureValueSpecialCharacters ?autoclean console details): Alters (e.g., ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric) ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue Adds (data cleaning transformations done directly “ResultMeasureValue” “DetectionLimitMeasureValue” columns, however original “ResultMeasureValue” “DetectionLimitMeasureValue” columns values WQP preserved new fields, “ResultMeasureValue.Original” “DetectionLimitMeasureValue.Original”. Additionally, “TADA.ResultMeasureValue.Flag” “TADA.DetectionLimitMeasureValue.Flag” created track changes made “ResultMeasureValue” “DetectionLimitMeasureValue” columns; provide information result values needed address censored data later (.e., nondetections). Specifically, new columns flag special characters included result values, specifies special characters . ResultMeasureValue.Original TADA.ResultMeasureValue.Flag DetectionLimitMeasureValue.Original TADA.DetectionLimitMeasureValue.Flag Downloads using TADAdataRetrieval columns time, aware data uploaded Water Quality Portal individual organizations, may may follow conventions. Data metadata quality guaranteed! Make sure carefully explore data make conservative quality assurance decisions information limited. Tips: query filters WQP work within fields ORs. example: Characteristics: choose pH & - ’s . means retrieve pH data available. States: Similarly, choose VA IL, ’s . means retrieve VA IL data available. Combinations fields ANDs, State/VA Characteristic/”. means receive data available VA. “Characteristic” “Characteristic Type” also work . means Characteristic must fall within CharacteristicGroup filters used, get error. “siteid” general term WQP uses describe Site IDs USGS databases Monitoring Location Identifiers (Water Quality Portal). monitoring location Water Quality Portal (WQP) unique Monitoring Location Identifier, regardless database derives. Monitoring Location Identifier WQP concatenated Organization Identifier plus Site ID number. Site IDs include number unique identifiers monitoring locations within USGS NWIS EPA’s WQX databases separately. Additional resources: Review function documentation entering following code console: ?TADAdataRetrieval Introduction dataRetrieval package General Data Import Water Quality Portal Water Quality Portal Web Services Guide dataRetrieval Tutorial Option 1: Use TADAdataRetrieval function. Option 2: Alternatively, can use data.table::fread function read web service call WQP profile (un-comment). Option 3: need download large amount data across large area, TADAdataRetrieval function working due WQP timeout issues, TADABigdataRetrieval function may work better. function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested. See ?TADABigdataRetrieval details. WARNING, can take multiple hours run. total run time depends query inputs. Review column names TADA Profile","code":"#You can edit this to define your own WQP query inputs below TADAProfile <- TADAdataRetrieval(statecode = \"UT\", characteristicName = c(\"Ammonia\", \"Nitrate\", \"Nitrogen\"), startDate = \"01-01-2021\") # New_Draft_fullphyschem <- data.table::fread(\"https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET\") #AllWaterTempData <- TADABigdataRetrieval(startDate = \"2019-01-01\", endDate = \"2021-12-31\", characteristicName = \"Temperature, water\", siteType = \"Stream\") colnames(TADAProfile) #> [1] \"OrganizationIdentifier\" #> [2] \"OrganizationFormalName\" #> [3] \"ActivityIdentifier\" #> [4] \"ActivityTypeCode\" #> [5] \"ActivityMediaName\" #> [6] \"ActivityMediaSubdivisionName\" #> [7] \"ActivityStartDate\" #> [8] \"ActivityStartTime.Time\" #> [9] \"ActivityStartTime.TimeZoneCode\" #> [10] \"ActivityEndDate\" #> [11] \"ActivityEndTime.Time\" #> [12] \"ActivityEndTime.TimeZoneCode\" #> [13] \"ActivityDepthHeightMeasure.MeasureValue\" #> [14] \"ActivityDepthHeightMeasure.MeasureUnitCode\" #> [15] \"ActivityDepthAltitudeReferencePointText\" #> [16] \"ActivityTopDepthHeightMeasure.MeasureValue\" #> [17] \"ActivityTopDepthHeightMeasure.MeasureUnitCode\" #> [18] \"ActivityBottomDepthHeightMeasure.MeasureValue\" #> [19] \"ActivityBottomDepthHeightMeasure.MeasureUnitCode\" #> [20] \"ProjectIdentifier\" #> [21] \"ActivityConductingOrganizationText\" #> [22] \"MonitoringLocationIdentifier\" #> [23] \"ActivityCommentText\" #> [24] \"SampleAquifer\" #> [25] \"HydrologicCondition\" #> [26] \"HydrologicEvent\" #> [27] \"SampleCollectionMethod.MethodIdentifier\" #> [28] \"SampleCollectionMethod.MethodIdentifierContext\" #> [29] \"SampleCollectionMethod.MethodName\" #> [30] \"SampleCollectionEquipmentName\" #> [31] \"ResultDetectionConditionText\" #> [32] \"CharacteristicName\" #> [33] \"ResultSampleFractionText\" #> [34] \"ResultMeasureValue\" #> [35] \"ResultMeasureValue.Original\" #> [36] \"TADA.ResultMeasureValue.Flag\" #> [37] \"ResultMeasure.MeasureUnitCode\" #> [38] \"MeasureQualifierCode\" #> [39] \"ResultStatusIdentifier\" #> [40] \"StatisticalBaseCode\" #> [41] \"ResultValueTypeName\" #> [42] \"ResultWeightBasisText\" #> [43] \"ResultTimeBasisText\" #> [44] \"ResultTemperatureBasisText\" #> [45] \"ResultParticleSizeBasisText\" #> [46] \"PrecisionValue\" #> [47] \"ResultCommentText\" #> [48] \"USGSPCode\" #> [49] \"ResultDepthHeightMeasure.MeasureValue\" #> [50] \"ResultDepthHeightMeasure.MeasureUnitCode\" #> [51] \"ResultDepthAltitudeReferencePointText\" #> [52] \"SubjectTaxonomicName\" #> [53] \"SampleTissueAnatomyName\" #> [54] \"ResultAnalyticalMethod.MethodIdentifier\" #> [55] \"ResultAnalyticalMethod.MethodIdentifierContext\" #> [56] \"ResultAnalyticalMethod.MethodName\" #> [57] \"MethodDescriptionText\" #> [58] \"LaboratoryName\" #> [59] \"AnalysisStartDate\" #> [60] \"ResultLaboratoryCommentText\" #> [61] \"DetectionQuantitationLimitTypeName\" #> [62] \"DetectionQuantitationLimitMeasure.MeasureValue\" #> [63] \"DetectionLimitMeasureValue.Original\" #> [64] \"TADA.DetectionLimitMeasureValue.Flag\" #> [65] \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" #> [66] \"PreparationStartDate\" #> [67] \"ProviderName\" #> [68] \"timeZoneStart\" #> [69] \"timeZoneEnd\" #> [70] \"ActivityStartDateTime\" #> [71] \"ActivityEndDateTime\" #> [72] \"MonitoringLocationName\" #> [73] \"MonitoringLocationTypeName\" #> [74] \"MonitoringLocationDescriptionText\" #> [75] \"HUCEightDigitCode\" #> [76] \"DrainageAreaMeasure.MeasureValue\" #> [77] \"DrainageAreaMeasure.MeasureUnitCode\" #> [78] \"ContributingDrainageAreaMeasure.MeasureValue\" #> [79] \"ContributingDrainageAreaMeasure.MeasureUnitCode\" #> [80] \"LatitudeMeasure\" #> [81] \"LongitudeMeasure\" #> [82] \"SourceMapScaleNumeric\" #> [83] \"HorizontalAccuracyMeasure.MeasureValue\" #> [84] \"HorizontalAccuracyMeasure.MeasureUnitCode\" #> [85] \"HorizontalCollectionMethodName\" #> [86] \"HorizontalCoordinateReferenceSystemDatumName\" #> [87] \"VerticalMeasure.MeasureValue\" #> [88] \"VerticalMeasure.MeasureUnitCode\" #> [89] \"VerticalAccuracyMeasure.MeasureValue\" #> [90] \"VerticalAccuracyMeasure.MeasureUnitCode\" #> [91] \"VerticalCollectionMethodName\" #> [92] \"VerticalCoordinateReferenceSystemDatumName\" #> [93] \"CountryCode\" #> [94] \"StateCode\" #> [95] \"CountyCode\" #> [96] \"AquiferName\" #> [97] \"LocalAqfrName\" #> [98] \"FormationTypeText\" #> [99] \"AquiferTypeName\" #> [100] \"ConstructionDateText\" #> [101] \"WellDepthMeasure.MeasureValue\" #> [102] \"WellDepthMeasure.MeasureUnitCode\" #> [103] \"WellHoleDepthMeasure.MeasureValue\" #> [104] \"WellHoleDepthMeasure.MeasureUnitCode\" #> [105] \"MethodSpecificationName\" #> [106] \"ProjectName\" #> [107] \"ProjectDescriptionText\" #> [108] \"SamplingDesignTypeCode\" #> [109] \"QAPPApprovedIndicator\" #> [110] \"QAPPApprovalAgencyName\" #> [111] \"ProjectFileUrl\" #> [112] \"ProjectMonitoringLocationWeightingUrl\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"depth-unit-conversions","dir":"Articles","previous_headings":"","what":"Depth unit conversions","title":"WQP Data Harmonization","text":"Converts depth units consistent unit. ActivityDepthHeightMeasure.MeasureValue provides depth information. crucial column lake data less often river data. Function checks dataset depth profile data. depth profile columns populated, function appends ‘Conversion Factor’ columns populates columns based original unit (MeasureUnitCode columns) target unit, defined ‘unit’ argument. ‘Depth Target Unit’ column also appended, indicating unit selected depth data converted . transform = FALSE, output includes ‘Conversion Factor’ columns ‘Depth Target Unit’ column. transform = TRUE, output includes converted depth data ‘Depth Target Unit’ column, acts flag indicating rows converted. Default transform = TRUE. depth profile function can harmonize depth units across following fields (specific one): “ActivityDepthHeightMeasure”, “ActivityTopDepthHeightMeasure”, “ActivityBottomDepthHeightMeasure”, “ResultDepthHeightMeasure”). default . Allowable values ‘unit’ either ‘m’ (meter), ‘ft’ (feet), ‘’ (inch). ‘unit’ accepts one allowable value input. Default unit = “m”. See additional function documentation additional function options entering following code console: ?DepthProfileData","code":"#converts all depth profile data to meters TADAProfileClean1 <- DepthProfileData(TADAProfile, unit = \"m\", transform = TRUE) #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"result-unit-conversions","dir":"Articles","previous_headings":"","what":"Result unit conversions","title":"WQP Data Harmonization","text":"Converts results WQX target units. WQX target units pulled MeasureUnit domain table: https://cdx.epa.gov/wqx/download/DomainValues/MeasureUnit.CSV See additional function documentation additional function options entering following code console: ?WQXTargetUnits","code":"#Converts all results to WQX target units TADAProfileClean2 <- WQXTargetUnits(TADAProfileClean1, transform = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"statistically-aggregated-data","dir":"Articles","previous_headings":"","what":"Statistically aggregated data","title":"WQP Data Harmonization","text":"Checks removes statistically aggregated high frequency (.e., continuous) data, present. Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = “Reported Raw Data (attached)” clean = TRUE, rows aggregated continuous data removed dataset column appended Default clean = TRUE See function documentation additional function options entering following code console: ?DepthProfileData","code":"TADAProfileClean3 <- AggregatedContinuousData(TADAProfileClean2, clean = TRUE) #> [1] \"The dataset does not contain aggregated continuous data.\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-qaqc-service-result-flags","dir":"Articles","previous_headings":"","what":"WQX QAQC Service Result Flags","title":"WQP Data Harmonization","text":"Run following result functions address invalid method, fraction, speciation, unit metadata characteristic. default clean = TRUE, remove invalid results. can change clean = FALSE flag results, remove . See documentation details: ?InvalidMethod Clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidSpeciation clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidResultUnit clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidFraction clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended.","code":"TADAProfileClean4 <- InvalidMethod(TADAProfileClean3, clean = TRUE) #> [1] \"No changes were made, because we did not find any invalid method/characteristic combinations in your dataset.\" TADAProfileClean5 <- InvalidFraction(TADAProfileClean4, clean = TRUE) #> [1] \"All data is valid, therefore the function cannot be applied.\" TADAProfileClean6 <- InvalidSpeciation(TADAProfileClean5, clean = FALSE) TADAProfileClean7 <- InvalidResultUnit(TADAProfileClean6, clean = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-national-upper-and-lower-thresholds","dir":"Articles","previous_headings":"","what":"WQX national upper and lower thresholds","title":"WQP Data Harmonization","text":"Run following code flag remove results national upper lower bound characteristic unit combination. See documentation details: ?AboveNationalWQXUpperThreshold clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset. ?BelowNationalWQXUpperThreshold clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset. default clean=TRUE, can change flag results desired. Results flagged, removed, clean=FALSE.","code":"TADAProfileClean8 <- AboveNationalWQXUpperThreshold(TADAProfileClean7, clean = TRUE) TADAProfileClean9 <- BelowNationalWQXUpperThreshold(TADAProfileClean8, clean = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"potential-duplicates","dir":"Articles","previous_headings":"","what":"Potential duplicates","title":"WQP Data Harmonization","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. information, review documentation entering following console: ?PotentialDuplicateRowID clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":"TADAProfileClean10 <- PotentialDuplicateRowID(TADAProfileClean9)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"invalid-coordinates","dir":"Articles","previous_headings":"","what":"Invalid coordinates","title":"WQP Data Harmonization","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled “TADA.InvalidCoordinates” following flags (relevant dataset). latitude less zero, row flagged “LAT_OutsideUSA”. longitude greater zero less 145, row flagged “LONG_OutsideUSA”. latitude longitude contains string, “999”, row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged “Imprecise”.","code":"TADAProfileClean11 <- InvalidCoordinates(TADAProfileClean10, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"review-qapp-information","dir":"Articles","previous_headings":"","what":"Review QAPP information","title":"WQP Data Harmonization","text":"Check data approved QAPP function checks see information column “QAPPApprovedIndicator”. organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . field, Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. defaults remove rows data QAPPApprovedIndicator equals “N”. Users alternatively remove N’s NA’s using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function anything. Check see QAPP Doc Available function checks data submitted “ProjectFileUrl” column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":"TADAProfileClean12 <- QAPPapproved(TADAProfileClean11, clean = TRUE, cleanNA = FALSE) TADAProfileClean13 <- QAPPDocAvailable(TADAProfileClean12, clean = FALSE) #> Warning in QAPPDocAvailable(TADAProfileClean12, clean = FALSE): The dataset does #> not contain QAPP document url data."},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field","dir":"Articles","previous_headings":"","what":"Filter data by field","title":"WQP Data Harmonization","text":"section TADA user want review unique values specific fields may choose remove data particular values. start, review list fields number unique values field. Next, choose field list see unique values field, well number times value appears dataset. ’ll start ActivityTypeCode. list fields review: ResultCommentText often details relating additional QA. MeasureQualifierCode Contains information data flags 3. codes may designate suspect data flags may described detail ResultLaboratoryCommentText another column ActivityTypeCode field four unique values – “Sample-Routine”, “Quality Control Sample-Field Replicate”, “Field Msr/Obs”, “Quality Control Sample-Field Blank.” example want remove quality control values ActivityTypeCode field, therefore, ’ll specify want remove “Quality Control Sample-Field Replicate” “Quality Control Sample-Field Blank” values ActivityTypeCode field. ’ve completed review ActivityTypeCode field. Let’s move different field see values want remove – ’ll look values ResultStatusIdentifier field. ActivityMediaSubdivisionName field two unique values, “Surface Water” “Groundwater.” example want remove “Groundwater” values.","code":"FilterFields(TADAProfileClean13) #> FieldName Count #> 1 OrganizationFormalName 7 #> 2 ActivityTypeCode 7 #> 3 ActivityMediaName 1 #> 4 ActivityMediaSubdivisionName 4 #> 5 ActivityCommentText 4 #> 6 HydrologicCondition 8 #> 7 HydrologicEvent 4 #> 8 CharacteristicName 3 #> 9 MeasureQualifierCode 4 #> 10 SampleTissueAnatomyName 1 #> 11 LaboratoryName 11 #> 12 DetectionQuantitationLimitTypeName 7 #> 13 MonitoringLocationTypeName 14 #> 14 ProjectName 8 FilterFieldReview(\"ActivityTypeCode\", TADAProfileClean13) #> FieldValue Count #> 7 Sample-Routine 5268 #> 6 Sample-Integrated Vertical Profile 474 #> 4 Quality Control Sample-Field Replicate 454 #> 2 Quality Control Sample-Equipment Blank 276 #> 3 Quality Control Sample-Field Blank 60 #> 1 Field Msr/Obs 4 #> 5 Quality Control Sample-Lab Duplicate 2 TADAProfileClean14 <- dplyr::filter(TADAProfileClean13, !(ActivityTypeCode %in% c(\"Quality Control Sample-Field Replicate\", \"Quality Control Sample-Field Blank\", \"Quality Control Sample-Lab Duplicate\", \"Quality Control Sample-Equipment Blank\"))) FilterFieldReview(\"ActivityMediaSubdivisionName\", TADAProfileClean14) #> FieldValue Count #> 3 Surface Water 687 #> 2 Groundwater 106 #> 1 Bulk deposition 1 TADAProfileClean15 <- dplyr::filter(TADAProfileClean14, !(ActivityMediaSubdivisionName %in% c(\"Groundwater\", \"Bulk deposition\")))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field-subset-by-parameter","dir":"Articles","previous_headings":"","what":"Filter data by field, subset by parameter","title":"WQP Data Harmonization","text":"section TADA user want select parameter, review unique values associated parameter specific fields, choose remove particular values. start, review list parameters dataset. (list sorted highest lowest counts. first rows displayed save space page) Next, select parameter. Let’s explore fields associated Nitrogen: Selecting parameter generates list , subset selected parameter, fields number unique values field. choose field list. example ’ll remove certain values HydrologicEvent field. HydrologicEvent field three unique values. example want remove samples collected “Storm” events. Therefore, ’ll specify want remove rows CharacteristicName “NITROGEN” HydrologicEvent field “Storm.”","code":"FilterParList(TADAProfileClean15) #> FieldValue Count #> 3 NITROGEN 4130 #> 2 NITRATE 1479 #> 1 AMMONIA 30 FilterParFields(TADAProfileClean15, \"NITROGEN\") #> FieldName Count #> 1 ActivityTypeCode 2 #> 2 ActivityMediaName 1 #> 3 ActivityMediaSubdivisionName 2 #> 4 ActivityCommentText 3 #> 5 HydrologicCondition 7 #> 6 HydrologicEvent 2 #> 7 SampleCollectionMethod.MethodIdentifier 6 #> 8 SampleCollectionMethod.MethodIdentifierContext 2 #> 9 SampleCollectionMethod.MethodName 6 #> 10 SampleCollectionEquipmentName 6 #> 11 ResultSampleFractionText 3 #> 12 ResultMeasure.MeasureUnitCode 2 #> 13 MeasureQualifierCode 3 #> 14 ResultStatusIdentifier 2 #> 15 ResultValueTypeName 1 #> 16 ResultWeightBasisText 1 #> 17 ResultTemperatureBasisText 1 #> 18 ResultParticleSizeBasisText 1 #> 19 ResultCommentText 7 #> 20 ResultAnalyticalMethod.MethodIdentifier 2 #> 21 ResultAnalyticalMethod.MethodIdentifierContext 2 #> 22 ResultAnalyticalMethod.MethodName 2 #> 23 MethodDescriptionText 1 #> 24 LaboratoryName 2 #> 25 ResultLaboratoryCommentText 5 #> 26 DetectionQuantitationLimitTypeName 2 #> 27 MonitoringLocationTypeName 11 FilterParFieldReview(\"HydrologicEvent\", TADAProfileClean15, \"NITROGEN\") #> FieldValue Count #> 1 Routine sample 59 TADAProfileClean16 <- dplyr::filter(TADAProfileClean15, !(CharacteristicName %in% \"NITROGEN\" & HydrologicEvent %in% \"Storm\"))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"transform-characteristic-speciation-and-unit-values-to-tada-standards","dir":"Articles","previous_headings":"","what":"Transform Characteristic, Speciation, and Unit values to TADA Standards","title":"WQP Data Harmonization","text":"HarmonizeRefTable function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values following elements: CharacteristicName ResultSampleFractionText MethodSpecicationName ResultMeasure.MeasureUnitCode HarmonizeData function compares input dataset TADA Harmonization Reference Table. purpose function make similar data consistent therefore easier compare analyze. Users can also edit reference file meet needs desired. download argument can used save harmonization file current working directory download = TRUE, default download = FALSE. Optional outputs include: dataset Harmonization columns appended, datset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE. examples HarmonizeData function can used: ResultSampleFractionText specifies forms constituents. cases, single CharacteristicName “Total” “Dissolved” forms specified, combined. cases, CharacteristicName ResultSampleFractionText combination given different identifier. identifier can used later identify comparable data groups calculating statistics creating figures combination. variables different names represent constituent (e.g., “Total Kjeldahl nitrogen (Organic N & NH3)” “Kjeldahl nitrogen”). HarmonizeData function gives consistent name (identifier) synonyms.","code":"UniqueHarmonizationRef <- HarmonizationRefTable(TADAProfileClean16, download = FALSE) TADAProfileClean17 <- HarmonizeData(TADAProfileClean16, ref = UniqueHarmonizationRef, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Cristina Mullin. Author, maintainer. Michelle Thawley. Author. Laura Shumway. Author. Jacob Greif. Author.","code":""},{"path":"usepa.github.io/tada/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Mullin, C.., Greif, J., Thawley, M., Shumway, L., 2022, TADA: R Tools Automated Data Assessment, U.S. Environmental Protection Agency, Washington, DC","code":"@Manual{, author = {Cristina A. Mullin and Jacob Greif and Michelle Thawley and Laura Shumway}, title = {TADA: R Tools for Automated Data Assessment}, address = {Washington, DC}, institution = {U.S. Environmental Protection Agency}, year = {2022}, url = {https://github.com/USEPA/TADA}, }"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"package-development","dir":"","previous_headings":"","what":"Package Development","title":"NA","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"what-is-github","dir":"","previous_headings":"","what":"What is GitHub?","title":"NA","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"required-installations","dir":"","previous_headings":"","what":"Required Installations","title":"NA","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"NA","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"branches","dir":"","previous_headings":"","what":"Branches","title":"NA","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"additional-references","dir":"","previous_headings":"","what":"Additional References","title":"NA","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/index.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"Tools for Automated Data Assessment R Package","text":"encourage read package’s CONTRIBUTING, LICENSE, [README] information (https://usepa.github.io/TADA/index.html) (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/index.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"Tools for Automated Data Assessment R Package","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Tools for Automated Data Assessment R Package","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/index.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"Tools for Automated Data Assessment R Package","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Tools for Automated Data Assessment R Package","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/index.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"Tools for Automated Data Assessment R Package","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Tools for Automated Data Assessment R Package","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":[]},{"path":"usepa.github.io/tada/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"CC0 1.0 Universal","title":"CC0 1.0 Universal","text":"CREATIVE COMMONS CORPORATION LAW FIRM PROVIDE LEGAL SERVICES. DISTRIBUTION DOCUMENT CREATE ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES INFORMATION “-” BASIS. CREATIVE COMMONS MAKES WARRANTIES REGARDING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER, DISCLAIMS LIABILITY DAMAGES RESULTING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER.","code":""},{"path":"usepa.github.io/tada/LICENSE.html","id":"statement-of-purpose","dir":"","previous_headings":"","what":"Statement of Purpose","title":"CC0 1.0 Universal","text":"laws jurisdictions throughout world automatically confer exclusive Copyright Related Rights (defined ) upon creator subsequent owner(s) (, “owner”) original work authorship /database (, “Work”). 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Affirmer disclaims responsibility clearing rights persons may apply Work use thereof, including without limitation person’s Copyright Related Rights Work. , Affirmer disclaims responsibility obtaining necessary consents, permissions rights required use Work. Affirmer understands acknowledges Creative Commons party document duty obligation respect CC0 use Work.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"NA","text":"encourage read package’s CONTRIBUTING, LICENSE, [README] information (https://usepa.github.io/TADA/index.html) (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"NA","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"NA","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/readme.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data upper threshold result values submitted WQX given characteristic. clean = TRUE, rows values upper WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"","code":"AboveNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data upper WQX threshold dataset clean = TRUE. Default clean = TRUE","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Aggregated Continuous Data — AggregatedContinuousData","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = \"Reported Raw Data (attached)\". clean = TRUE, rows aggregated continuous data removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"","code":"AggregatedContinuousData(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":".data TADA dataframe clean Boolean argument; removes aggregated continuous data dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"clean = FALSE, column flagging rows aggregated continuous data appended input data set. clean = TRUE, aggregated continuous data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — autoclean","title":"autoclean — autoclean","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — autoclean","text":"","code":"autoclean(.data)"},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — autoclean","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — autoclean","text":"autocleaned TADA data profile","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — autoclean","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":null,"dir":"Reference","previous_headings":"","what":"AutoFilter — AutoFilter","title":"AutoFilter — AutoFilter","text":"Function can used autofilter simplify WQP dataset. applying function, dataset contain result values water media types chemicals tissue (e.g. mercury fish tissue). complex biological data (counts macroinvertebrates) removed. function looks following fields autofilter: ActivityMediaName, ActivityMediaSubDivisionName, AssemblageSampledName","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AutoFilter — AutoFilter","text":"","code":"AutoFilter(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AutoFilter — AutoFilter","text":".data TADA dataframe clean Indicates whether flag columns appended data (clean = FALSE), flagged data transformed/filtered dataset columns appended (clean = TRUE).","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"AutoFilter — AutoFilter","text":"clean = FALSE, flag column appended dataset. clean = TRUE, flag column appended relevant rows removed.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data lower threshold result values submitted WQX given characteristic. clean = TRUE, rows values lower WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"","code":"BelowNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data lower WQX threshold dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalnumcount — decimalnumcount","title":"decimalnumcount — decimalnumcount","text":"character data type","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalnumcount — decimalnumcount","text":"","code":"decimalnumcount(x)"},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalnumcount — decimalnumcount","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalnumcount — decimalnumcount","text":"Number values right decimal point character type data.","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalplaces — decimalplaces","title":"decimalplaces — decimalplaces","text":"numeric data type","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalplaces — decimalplaces","text":"","code":"decimalplaces(x)"},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalplaces — decimalplaces","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalplaces — decimalplaces","text":"Number values right decimal point numeric type data.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":null,"dir":"Reference","previous_headings":"","what":"Depth Profile Flag & Unit Conversion — DepthProfileData","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Function checks dataset depth profile data. depth profile columns populated, function appends 'Conversion.Factor' columns populates columns based original unit (MeasureUnitCode columns) target unit, defined 'unit' argument. 'WQX.Depth.TargetUnit' column also appended, indicating unit selected depth data converted . transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"","code":"DepthProfileData( .data, unit = \"m\", fields = c(\"ActivityDepthHeightMeasure\", \"ActivityTopDepthHeightMeasure\", \"ActivityBottomDepthHeightMeasure\", \"ResultDepthHeightMeasure\"), transform = TRUE )"},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":".data TADA dataframe unit Character string input indicating uniform unit depth data converted . Allowable values 'unit' either 'm' (meter), 'ft' (feet), '' (inch). 'unit' accepts one allowable value input. Default unit = \"m\". fields Character string input indicating depth fields checked data. Allowable values 'fields' 'ActivityDepthHeightMeasure,' 'ActivityTopDepthHeightMeasure,' 'ActivityBottomDepthHeightMeasure,' 'ResultDepthHeightMeasure.'. Default include allowable values. transform Boolean argument; transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'Depth Target Unit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Full dataset converted uniform depth units 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. transform = FALSE, output full dataset 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field — FilterFieldReview","title":"Generate list of unique values in a given field — FilterFieldReview","text":"Function creates table pie chart unique values, counts values chosen field dataframe.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field — FilterFieldReview","text":"","code":"FilterFieldReview(field, .data)"},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field — FilterFieldReview","text":"field Field name .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field — FilterFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names — FilterFields","title":"Generate list of field names — FilterFields","text":"Function creates list fields input dataframe well number unique values field. list intended inform users specific fields explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names — FilterFields","text":"","code":"FilterFields(.data)"},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names — FilterFields","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names — FilterFields","text":"table fields count unique values field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"Function creates table pie chart unique values, counts values, chosen field dataframe subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"","code":"FilterParFieldReview(field, .data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"field Field name .data Optional argument; TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names subset by parameter — FilterParFields","title":"Generate list of field names subset by parameter — FilterParFields","text":"Function subsets input dataframe input parameter creates list fields subset dataframe well number unique values field. list intended inform users specific fields explore filter subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names subset by parameter — FilterParFields","text":"","code":"FilterParFields(.data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names subset by parameter — FilterParFields","text":".data TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names subset by parameter — FilterParFields","text":"table fields count unique values field, subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of parameters — FilterParList","title":"Generate list of parameters — FilterParList","text":"Function generates list characteristics input dataset, well number records . list intended inform users parameters explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of parameters — FilterParList","text":"","code":"FilterParList(.data)"},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of parameters — FilterParList","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of parameters — FilterParList","text":"list unique characteristics counts","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":null,"dir":"Reference","previous_headings":"","what":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Function summarizes censored data dataset, including substitutions made.","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"","code":"GenerateCensoredDataStats(.data)"},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":".data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Summary table","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table — GetMeasureUnitRef","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"Function downloads returns latest WQX MeasureUnit Domain table, adds additional target unit information, writes data sysdata.rda.","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"","code":"GetMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"sysdata.rda updated WQXunitRef object (unit conversion reference table)","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Function downloads returns newest available (cleaned) raw Water Quality Exchange (WQX) QAQC Characteristic Validation reference table. WQXcharValRef data frame contains information four functions: InvalidFraction, InvalidResultUnit, InvalidSpeciation, UncommonAnalyticalMethodID.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"","code":"GetWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Updated sysdata.rda updated WQXcharValRef object","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode can optionally edit reference file meet needs.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"","code":"HarmonizationRefTable(.data, download = FALSE)"},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":".data TADA dataframe download Boolean argument; download = TRUE, output downloaded current working directory.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Harmonization Reference Table unique input dataset","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"Function compares input dataset TADA Harmonization Reference Table, makes synonymous data consistent. Optional outputs include: 1) dataset Harmonization columns appended, 2) dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards 3) four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"","code":"HarmonizeData(.data, ref, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":".data TADA dataframe ref Optional argument specify dataframe use reference file. primary use argument user generated harmonization reference file unique data, made changes file. transform Boolean argument; transforms /converts original values dataset TADA Harmonization Reference Table values following fields: CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode. Default transform = TRUE. flag Boolean argument; appends columns TADA Harmonization Reference Table dataframe. Default flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"transform = FALSE flag = TRUE, Harmonization Reference Table columns appended dataset . transform = TRUE flag = TRUE, Harmonization columns appended dataset transformations executed. transform = TRUE flag = FALSE, transformations executed . transform = FALSE flag = FALSE, error returned (function return input dataframe unchanged input allowed).","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":null,"dir":"Reference","previous_headings":"","what":"Invalid coordinates — InvalidCoordinates","title":"Invalid coordinates — InvalidCoordinates","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled \"TADA.InvalidCoordinates\" following flags (relevant dataset). latitude less zero, row flagged \"LAT_OutsideUSA\". longitude greater zero less 145, row flagged \"LONG_OutsideUSA\". latitude longitude contains string, \"999\", row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged \"Imprecise\".","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Invalid coordinates — InvalidCoordinates","text":"","code":"InvalidCoordinates(.data, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Invalid coordinates — InvalidCoordinates","text":".data TADA dataframe clean_outsideUSA Boolean argument; removes data coordinates outside United States clean_outsideUSA = TRUE. Default clean = FALSE. clean_imprecise Boolean arguments; removes imprecise data clean_imprecise = TRUE. Default clean_imprecise = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Invalid coordinates — InvalidCoordinates","text":"either clean_outsideUSA clean_imprecise argument FALSE, column flagging rows respective QA check appended input dataset. either argument TRUE, \"invalid\" \"imprecise\" data removed, respectively.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Sample Fraction Validity — InvalidFraction","title":"Check Sample Fraction Validity — InvalidFraction","text":"Function checks validity characteristic-fraction combination dataset. clean = TRUE, rows invalid characteristic-fraction combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Sample Fraction Validity — InvalidFraction","text":"","code":"InvalidFraction(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Sample Fraction Validity — InvalidFraction","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-fraction combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Sample Fraction Validity — InvalidFraction","text":"clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Invalid Analytical Methods — InvalidMethod","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"Function checks validity characteristic-analytical method combination dataset. clean = TRUE, rows invalid characteristic-analytical method combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"","code":"InvalidMethod(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Invalid Analytical Methods — InvalidMethod","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-analytical method combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Unit Validity — InvalidResultUnit","title":"Check Result Unit Validity — InvalidResultUnit","text":"Function checks validity characteristic-media-result unit combination dataset. clean = TRUE, rows invalid characteristic-media-result unit combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Unit Validity — InvalidResultUnit","text":"","code":"InvalidResultUnit(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Unit Validity — InvalidResultUnit","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-media-result unit combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Unit Validity — InvalidResultUnit","text":"clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Method Speciation Validity — InvalidSpeciation","title":"Check Method Speciation Validity — InvalidSpeciation","text":"Function checks validity characteristic-method speciation combination dataset. clean = TRUE, rows invalid characteristic-method speciation combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Method Speciation Validity — InvalidSpeciation","text":"","code":"InvalidSpeciation(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Method Speciation Validity — InvalidSpeciation","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-method speciation combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Method Speciation Validity — InvalidSpeciation","text":"#'clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Function checks special characters non-numeric values ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields appends flag columns indicating special characters included , special characters . ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields also converted class numeric.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"","code":"MeasureValueSpecialCharacters(.data)"},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Full dataset column indicating presence special characters ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields. Additionally, ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric, copies column created preserve original character values.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"usepa.github.io/tada/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Potential Duplicates — PotentialDuplicateRowID","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"","code":"PotentialDuplicateRowID(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":".data TADA dataframe clean Boolean argument; removes potential duplicate data dataset clean = TRUE. clean = FALSE, column indicating potential duplicate rows unique number linking rows appended input data set. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":null,"dir":"Reference","previous_headings":"","what":"Check data for an approved QAPP — QAPPapproved","title":"Check data for an approved QAPP — QAPPapproved","text":"Function checks data submitted column \"QAPPApprovedIndicator\". organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. default removes rows data QAPPApprovedIndicator equals \"N\". Users alternatively remove N's NA's using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function make changes data.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check data for an approved QAPP — QAPPapproved","text":"","code":"QAPPapproved(.data, clean = TRUE, cleanNA = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check data for an approved QAPP — QAPPapproved","text":".data TADA dataframe clean Boolean argument two possible values called \"TRUE\" \"FALSE\". clean=TRUE, rows data QAPPApprovedIndicator equals \"N\" removed. , clean=FALSE, rows data QAPPApprovedIndicator equals \"N\" retained. cleanNA Boolean argument two possible values called \"TRUE\" \"FALSE\". cleanNA=TRUE, rows data QAPPApprovedIndicator equals \"NA\" removed. , cleanNA=FALSE, rows data QAPPApprovedIndicator equals \"NA\" retained.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check data for an approved QAPP — QAPPapproved","text":"clean = FALSE cleanNA = FALSE, data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check data for an approved QAPP — QAPPapproved","text":"Note: required field, often left blank (NA) even data associated QAPP. states tribes collect monitoring data using 106 funding (almost state tribal data WQX) required EPA approved QAPP receive 106 funding. Therefore, organizations data approved QAPP even data submitted WQP NA.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"Function checks data submitted \"ProjectFileUrl\" column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"","code":"QAPPDocAvailable(.data, clean = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":".data TADA dataframe clean Boolean argument; removes data without associated QAPP document dataset clean = TRUE. Default clean = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"clean = FALSE, column appended input data set flags rows associated QAPP document. clean = TRUE, data without associated QAPP document removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":null,"dir":"Reference","previous_headings":"","what":"Read in WQP data using WQP web services directly — readWQPwebservice","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Go WQP website (https://www.waterqualitydata.us/) fill advanced query form. Choose Full Physical Chemical Data Profile, data sources, file format Comma-Separated. finished, hit download button. Instead, copy web service URL located bottom page header \"Result\". Use \"Result\" web service URL input function download data directly R.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"","code":"readWQPwebservice(webservice)"},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"webservice WQP Web Service URL, entered within quotes \"url\"","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"WQP Full Physical Chemical Results Data Profile","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Note: may useful save Query URL well comment within code. URL return WQP query page original data filters.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"RemoveEmptyColumns — RemoveEmptyColumns","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Removes columns NA values. Used quickly reduce number columns dataframe improve management readability dataset.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"","code":"RemoveEmptyColumns(.data)"},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":".data Dataframe","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Full dataset empty data columns removed","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"TADABigdataRetrieval( startDate = \"null\", endDate = \"null\", characteristicName = \"null\", siteType = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"startDate Start Date YYYY-MM-DD format, example, \"1995-01-01\" endDate end date YYYY-MM-DD format, example, \"2020-12-31\" characteristicName Name water quality parameter siteType Name water body type (e.g., \"Stream\", \"Lake, Reservoir, Impoundment\")","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"Similarly TADAdataRetrieval function, function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"if (FALSE) { tada2 <- TADABigdataRetrieval(startDate = \"01-01-2021\", endDate = \"01-01-2022\", characteristicName = \"Nitrogen\", siteType = \"Stream\") }"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Retrieve data Water Quality Portal (WQP) output TADA-compatible dataset.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"TADAdataRetrieval( statecode = \"null\", startDate = \"null\", countycode = \"null\", siteid = \"null\", siteType = \"null\", characteristicName = \"null\", ActivityMediaName = \"null\", endDate = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"statecode Code identifies state startDate Start Date countycode Code identifies county siteid Unique monitoring station identifier siteType Type waterbody characteristicName Name parameter ActivityMediaName Sampling substrate water, air, sediment endDate End Date","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Keep mind query filters WQP work within fields ORs. example, characteristics – choose pH & – ’s . Similarly, choose VA IL, ’s . combo fields ANDs. State/VA Characteristic/\". \"Characteristic\" \"Characteristic Group\" also work . function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"if (FALSE) { tada1 <- TADAdataRetrieval(statecode = \"WI\", countycode = \"Dane\", characteristicName = \"Phosphorus\") }"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — TADAprofileCheck","title":"autoclean — TADAprofileCheck","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — TADAprofileCheck","text":"","code":"TADAprofileCheck(.data)"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — TADAprofileCheck","text":".data dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — TADAprofileCheck","text":"cleaned TADA data profile TADA Profile Check function checks column names dataframe include TADA profile fields. used beginning TADA functions ensure input data frame suitable (.e. either full physical/chemical results profile downloaded WQP TADA profile template downloaded EPA TADA webpage.) Boolean result indicating whether input dataframe contains TADA profile fields.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — TADAprofileCheck","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":null,"dir":"Reference","previous_headings":"","what":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"Function substitutes monitoring device/method detection limits (available) result values applicable.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"","code":"TransformCensoredData(transform, .data)"},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE. .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform=TRUE, monitoring device/method detection limits (available) substituted result values units. transform = FALSE, monitoring device/method detection limits (available) substituted result values units - Instead, columns appended rows may include censored data. flag indicates 1) row contains censored data, 2) monitoring device/method detection limits available.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Existing Data in sysdata.rda — UpdateInternalData","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Function internal use . used internal functions used update internal data (e.g. reference tables). function adapted stackoverflow.com thread, can accessed .","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"","code":"UpdateInternalData(..., list = character())"},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"... Objects updated sysdata.rda. list Argument indicating data class list.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Updated sysdata.rda file","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"Update Measure Unit Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"","code":"UpdateMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"Update Characteristic Validation Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"","code":"UpdateWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"Used store cached WQX QAQC Characteristic Validation Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"","code":"WQXCharValRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"object class NULL length 0.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Units to WQX Target Units — WQXTargetUnits","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function compares measure units input data Water Quality Exchange (WQX) 3.0 QAQC Characteristic Validation table.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"","code":"WQXTargetUnits(.data, transform = TRUE)"},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":".data TADA dataset transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"transform=TRUE, result values units converted WQX target units. function changes values within \"ResultMeasure.MeasureUnitCode\" \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" WQX target units converts respective values within \"ResultMeasureValue\" \"DetectionQuantitationLimitMeasure.MeasureValue\" fields. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=TRUE add following two fields input dataset, \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\", retain original result unit values. transform = FALSE, result values units converted WQX target units, columns appended indicate target units conversion factors , data can converted. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=FALSE add following two fields input dataset: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function ALWAYS add following two columns input dataset: \"WQX.ResultMeasureValue.UnitConversion\", \"WQX.DetectionLimitMeasureValue.UnitConversion\" two fields indicate data can converted.\"NoResultValue\" means data converted ResultMeasureValue, \"NoTargetUnit\" means data converted original unit associated target unit WQX. \"Convert\" means data can transformed, \"Converted\" means function run input transform = TRUE, values already converted. also uses following six fields input dataset: \"CharacteristicName\", \"ActivityMediaName\", \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" function adds following two fields transforms values within following four fields transform=TRUE: Adds: \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\". Transforms: \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\". function adds following two fields transform=FALSE: Adds: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"Used store cached Measure Unit Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"","code":"WQXunitRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"object class NULL length 0.","code":""}] diff --git a/man/DepthProfileData.Rd b/man/DepthProfileData.Rd index b656a6b9..185f030b 100644 --- a/man/DepthProfileData.Rd +++ b/man/DepthProfileData.Rd @@ -27,26 +27,26 @@ checked for data. Allowable values for 'fields' are is to include all allowable values.} \item{transform}{Boolean argument; When transform = FALSE, the output includes -all Conversion Factor' columns and the 'Depth Target Unit' column. When +all 'Conversion.Factor' columns and the 'WQX.Depth.TargetUnit' column. When transform = TRUE, the output includes converted depth data and the 'Depth Target Unit' column, which acts as a flag indicating which rows have been converted. Default is transform = TRUE.} } \value{ -Full dataset with converted uniform depth units and a 'Depth Target -Unit' column, which acts as a flag indicating which rows have been converted. -When transform = FALSE, the output is the full dataset with 'Conversion Factor' -columns and a 'Depth Target Unit' column. +Full dataset with converted uniform depth units and a 'WQX.Depth.TargetUnit' +column, which acts as a flag indicating which rows have been converted. +When transform = FALSE, the output is the full dataset with 'Conversion.Factor' +columns and a 'WQX.Depth.TargetUnit' column. } \description{ Function checks dataset for depth profile data. Where depth profile columns -are populated, the function appends 'Conversion Factor' columns +are populated, the function appends 'Conversion.Factor' columns and populates those columns based on the original unit (MeasureUnitCode columns) and the target unit, which is defined in the 'unit' argument. A -'Depth Target Unit' column is also appended, indicating the unit all selected +'WQX.Depth.TargetUnit' column is also appended, indicating the unit all selected depth data is converted to. When transform = FALSE, the output includes all -'Conversion Factor' columns and the 'Depth Target Unit' column. When transform -= TRUE, the output includes converted depth data and the 'Depth Target -Unit' column, which acts as a flag indicating which rows have been converted. +'Conversion.Factor' columns and the 'WQX.Depth.TargetUnit' column. When transform += TRUE, the output includes converted depth data and the 'WQX.Depth.TargetUnit' +column, which acts as a flag indicating which rows have been converted. Default is transform = TRUE. } diff --git a/man/HarmonizationRefTable.Rd b/man/HarmonizationRefTable.Rd index 30159416..ec4f2422 100644 --- a/man/HarmonizationRefTable.Rd +++ b/man/HarmonizationRefTable.Rd @@ -19,6 +19,6 @@ Harmonization Reference Table unique to the input dataset Function generates a harmonization reference table that is specific to the input dataset. Users can review how their input data relates to standard TADA values for CharacteristicName, ResultSampleFractionText, -MethodSpecicationName, and ResultMeasure.MeasureUnitCode and they can optionally +MethodSpecificationName, and ResultMeasure.MeasureUnitCode and they can optionally edit the reference file to meet their needs. } diff --git a/man/TADAprofileCheck.Rd b/man/TADAprofileCheck.Rd index 68bfa787..7ac049ec 100644 --- a/man/TADAprofileCheck.Rd +++ b/man/TADAprofileCheck.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/DataDiscoveryRetrieval.R \name{TADAprofileCheck} \alias{TADAprofileCheck} -\title{TADA Profile Check} +\title{autoclean} \usage{ TADAprofileCheck(.data) } @@ -10,13 +10,34 @@ TADAprofileCheck(.data) \item{.data}{A dataframe} } \value{ -Boolean result indicating whether or not the input dataframe contains -all of the TADA profile fields. -} -\description{ +cleaned TADA data profile + +TADA Profile Check + This function checks if the column names in a dataframe include the TADA profile fields. It is used at the beginning of TADA functions to ensure the input data frame is suitable (i.e. is either the full physical/chemical results profile downloaded from WQP or the TADA profile template downloaded from the EPA TADA webpage.) + +Boolean result indicating whether or not the input dataframe contains +all of the TADA profile fields. +} +\description{ +Removes complex biological data. Removes non-water media samples. +Removes rows of data that are true duplicates. Capitalizes fields to harmonize +data. This function includes and runs the TADA "MeasureValueSpecialCharacters" +function as well. +} +\details{ +Within "BiologicalIntentName", only the allowable values "tissue", "toxicity", +and "NA" apply to non-biological data (the function removes all others). +Toxicity and fish tissue data will be kept, but other types of biological +monitoring data will not. + +We decided to make some fields uppercase that way they're more compatible +with the WQX validation reference tables and to avoid any issues with +case-sensitivity when joining data. Therefore, we might need to tack on any +immediate QA steps (removing true duplicates, converting result values to numeric, +capitalizing letters, etc.) to this function, as well as the other retrieval functions. } diff --git a/readme.md b/readme.md index 74573680..c8b199ab 100644 --- a/readme.md +++ b/readme.md @@ -2,11 +2,11 @@ [![](https://github.com/USEPA/TADA/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/USEPA/TADA/actions/workflows/R-CMD-check.yaml) -We encourage you to read this package's [CONTRIBUTING](https://github.com/USEPA/TADA/blob/develop/vignettes/CONTRIBUTING.Rmd) file, [LICENSE](https://github.com/USEPA/TADA/blob/develop/LICENSE.md), and [README](https://github.com/USEPA/TADA/blob/develop/readme.md) (you are here). +We encourage you to read this package's [CONTRIBUTING](https://usepa.github.io/TADA/articles/CONTRIBUTING.html), [LICENSE](https://usepa.github.io/TADA/LICENSE.html), and [README] information (https://usepa.github.io/TADA/index.html) (you are here). TADA is a draft R package being developed to help States, Tribes, Tribal Nations, Pueblos, and other stakeholders more efficiently compile and evaluate [Water Quality Portal (WQP)](https://www.waterqualitydata.us/) data collected from surface water monitoring sites. TADA is a building block to support future development of the [TADA R Shiny application](https://github.com/USEPA/TADAShiny). -We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the [CONTRIBUTING](https://github.com/USEPA/TADA/blob/develop/vignettes/CONTRIBUTING.Rmd) file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time. +We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the [CONTRIBUTING](https://usepa.github.io/TADA/articles/CONTRIBUTING.html) file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time. ## Water Quality Portal diff --git a/tests/testthat/test-DataDiscoveryRetrieval.R b/tests/testthat/test-DataDiscoveryRetrieval.R index c94241b6..7f173f36 100644 --- a/tests/testthat/test-DataDiscoveryRetrieval.R +++ b/tests/testthat/test-DataDiscoveryRetrieval.R @@ -112,3 +112,13 @@ test_that("TADAdataRetrieval", { "MethodSpecificationName") %in% names(tada1))) }) + +#testing that "meters" is successfully replaced with "m". This feature is part of the autoclean function +#which runs automatically when TADAdataRetrieval runs +test_that("TADAdataRetrieval", { + check_autoclean_meters_works <- TADAdataRetrieval(statecode = "UT", + characteristicName = c("Ammonia", "Nitrate", "Nitrogen"), + startDate = "01-01-2021") + expect_equal(check_autoclean_meters_works$ActivityDepthHeightMeasure.MeasureUnitCode[975], "m" + ) + }) diff --git a/vignettes/WQPDataHarmonization.Rmd b/vignettes/WQPDataHarmonization.Rmd index eefeb9e9..df60c6e5 100644 --- a/vignettes/WQPDataHarmonization.Rmd +++ b/vignettes/WQPDataHarmonization.Rmd @@ -22,17 +22,18 @@ knitr::opts_chunk$set( ## Overview -This vignette will walk through how to discover, wrangle, and -harmonize [Water Quality Portal (WQP)](https://www.waterqualitydata.us/) -data from multiple organizations. +This vignette will walk through how to discover, wrangle, and harmonize +[Water Quality Portal (WQP)](https://www.waterqualitydata.us/) data from +multiple organizations. ## Install and load packages -To install TADA, currently you need to install from GitHub using remotes (shown) -or devtools. dataRetrieval will be downloaded from CRAN, but the development -version can be downloaded directly from GitHub (un-comment). The following code will also install -any packages you do not have, and load all packages required to run this vignette into -your R session. +To install TADA, currently you need to install from GitHub using remotes +(shown) or devtools. dataRetrieval will be downloaded from CRAN, but the +development version can be downloaded directly from GitHub (un-comment). +The following code will also install any packages you do not have, and +load all packages required to run this vignette into your R session. + ```{r, results = 'hide', message = FALSE, warning = FALSE} list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes", "rlang", "tidyverse", "knitr", "rmarkdown", "testthat", "usethis", "devtools", "pkgdown", "Rcpp", "spelling") @@ -40,22 +41,27 @@ new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[," if(length(new.packages)) install.packages(new.packages) ``` -Load the remotes library before installing TADA or dataRetrieval from GitHub -```{r} +Load the remotes library before installing TADA or dataRetrieval from +GitHub + +```{r, results = 'hide', message = FALSE, warning = FALSE} # If you have any issues loading the remotes library, uncomment the line below to install the "remotes" package specifying the repo # install.packages("remotes", repos = "http://cran.us.r-project.org") library(remotes) ``` -Uncomment the lines below to install latest version of TADA and dataRetrieval from GitHub. -```{r} +Uncomment the lines below to install latest version of TADA and +dataRetrieval from GitHub. + +```{r, results = 'hide', message = FALSE, warning = FALSE} # remotes::install_github("USGS-R/dataRetrieval", dependencies=TRUE) -# remotes::install_github("USEPA/TADA", dependencies=TRUE) +remotes::install_github("USEPA/TADA", dependencies=TRUE) ``` Load the required libraries to run this vignette into your R session -```{r} + +```{r, results = 'hide', message = FALSE, warning = FALSE} library(plyr) library(data.table) library(dplyr) @@ -206,29 +212,45 @@ Additional resources: - [dataRetrieval Tutorial](https://owi.usgs.gov/R/dataRetrieval.html) - Option 1: Use the TADAdataRetrieval function. + ```{r} #You can edit this to define your own WQP query inputs below TADAProfile <- TADAdataRetrieval(statecode = "UT", characteristicName = c("Ammonia", "Nitrate", "Nitrogen"), startDate = "01-01-2021") ``` -Option 2: Alternatively, you can use the data.table::fread function to read in a web service call for any WQP profile (un-comment). +Option 2: Alternatively, you can use the data.table::fread function to +read in a web service call for any WQP profile (un-comment). + ```{r} -# new_fullphyschem <- data.table::fread("https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET") +# New_Draft_fullphyschem <- data.table::fread("https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET") ``` -Option 3: If you need to download a large amount of data from across a large area, and the TADAdataRetrieval function is not working due to WQP timeout issues, then the TADABigdataRetrieval function may work better. +Option 3: If you need to download a large amount of data from across a +large area, and the TADAdataRetrieval function is not working due to WQP +timeout issues, then the TADABigdataRetrieval function may work better. + +This function does multiple synchronous data calls to the WQP +(waterqualitydata.us). It uses the WQP summary service to limit the +amount downloaded to only relevant data, and pulls back data from 100 +stations at a time and then joins the data back together and produces a +single TADA compatible dataframe as the output. For large data sets, +that can save a lot of time and ultimately reduce the complexity of +subsequent data processing. Using this function, you will be able to +download all data available from all sites in the contiguous United +States that is available for the time period, characteristicName, and +siteType requested. -This function does multiple synchronous data calls to the WQP (waterqualitydata.us). It uses the WQP summary service to limit the amount downloaded to only relevant data, and pulls back data from 100 stations at a time and then joins the data back together and produces a single TADA compatible dataframe as the output. For large data sets, that can save a lot of time and ultimately reduce the complexity of subsequent data processing. Using this function, you will be able to download all data available from all sites in the contiguous United States that is available for the time period, characteristicName, and siteType requested. +See ?TADABigdataRetrieval for more details. WARNING, this can take +multiple hours to run. The total run time depends on your query inputs. -See ?TADABigdataRetrieval for more details. WARNING, this can take multiple hours to run. The total run time depends on your query inputs. ```{r} #AllWaterTempData <- TADABigdataRetrieval(startDate = "2019-01-01", endDate = "2021-12-31", characteristicName = "Temperature, water", siteType = "Stream") ``` Review all column names in the TADA Profile + ```{r} colnames(TADAProfile) ``` @@ -313,9 +335,9 @@ TADAProfileClean3 <- AggregatedContinuousData(TADAProfileClean2, clean = TRUE) ## WQX QAQC Service Result Flags Run the following result functions to address invalid method, fraction, -speciation, and unit metadata by characteristic. The default is -clean = TRUE, which will remove invalid results. You can change this to -clean = FALSE to flag results, but not remove them. +speciation, and unit metadata by characteristic. The default is clean = +TRUE, which will remove invalid results. You can change this to clean = +FALSE to flag results, but not remove them. See documentation for more details: From 7bf416dd29b75c06413563229753fa71cfce1bd9 Mon Sep 17 00:00:00 2001 From: Mullin Date: Tue, 18 Oct 2022 17:38:25 -0400 Subject: [PATCH 05/10] cut the suggestions --- readme.md | 4 ++-- vignettes/CONTRIBUTING.Rmd | 2 +- vignettes/WQPDataHarmonization.Rmd | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/readme.md b/readme.md index c8b199ab..aca95a58 100644 --- a/readme.md +++ b/readme.md @@ -2,9 +2,9 @@ [![](https://github.com/USEPA/TADA/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/USEPA/TADA/actions/workflows/R-CMD-check.yaml) -We encourage you to read this package's [CONTRIBUTING](https://usepa.github.io/TADA/articles/CONTRIBUTING.html), [LICENSE](https://usepa.github.io/TADA/LICENSE.html), and [README] information (https://usepa.github.io/TADA/index.html) (you are here). +We encourage you to read this package's [CONTRIBUTING](https://usepa.github.io/TADA/articles/CONTRIBUTING.html), [LICENSE](https://usepa.github.io/TADA/LICENSE.html), and [README](https://usepa.github.io/TADA/index.html) files (you are here). -TADA is a draft R package being developed to help States, Tribes, Tribal Nations, Pueblos, and other stakeholders more efficiently compile and evaluate [Water Quality Portal (WQP)](https://www.waterqualitydata.us/) data collected from surface water monitoring sites. TADA is a building block to support future development of the [TADA R Shiny application](https://github.com/USEPA/TADAShiny). +TADA is a draft R package being developed to help States, Tribes, Tribal Nations, Pueblos, and other stakeholders more efficiently compile and evaluate [Water Quality Portal (WQP)](https://www.waterqualitydata.us/) data collected from surface water monitoring sites. TADA is a building block to support future development of the [TADA R Shiny application](https://github.com/USEPA/TADAShiny). We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the [CONTRIBUTING](https://usepa.github.io/TADA/articles/CONTRIBUTING.html) file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time. diff --git a/vignettes/CONTRIBUTING.Rmd b/vignettes/CONTRIBUTING.Rmd index b83ca8b3..1e17d74e 100644 --- a/vignettes/CONTRIBUTING.Rmd +++ b/vignettes/CONTRIBUTING.Rmd @@ -87,7 +87,7 @@ Complete the pull request by detailing all fixes and contributions, and tagging ## Open-Source Code Policy -Effective August 8, 2016, the [OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, and Innovation through Reusable and Open Source Software](https://sourcecode.cio.gov/) applies to new custom-developed code created or procured by EPA consistent with the scope and applicability requirements of Office of Management and Budget's (OMB's) Federal Source Code Policy. In general, it states that all new custom-developed code by Federal Agencies should be made available and reusable as open-source code. +Effective August 8, 2016, the [OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, and Innovation through Reusable and Open Source Software](https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/memoranda/2016/m_16_21.pdf) applies to new custom-developed code created or procured by EPA consistent with the scope and applicability requirements of Office of Management and Budget's (OMB's) Federal Source Code Policy. In general, it states that all new custom-developed code by Federal Agencies should be made available and reusable as open-source code. The EPA specific implementation of OMB Mandate M-16-21 is addressed in the [System Life Cycle Management Procedure](https://www.epa.gov/irmpoli8/policy-procedures-and-guidance-system-life-cycle-management-slcm). EPA has chosen to use GitHub as its version control system as well as its inventory of open-source code projects. EPA uses GitHub to inventory its custom-developed, open-source code and generate the necessary metadata file that is then posted to code.gov for broad reuse in compliance with OMB Mandate M-16-21. diff --git a/vignettes/WQPDataHarmonization.Rmd b/vignettes/WQPDataHarmonization.Rmd index df60c6e5..3888dcaf 100644 --- a/vignettes/WQPDataHarmonization.Rmd +++ b/vignettes/WQPDataHarmonization.Rmd @@ -643,7 +643,7 @@ Optional outputs include: 1. the dataset with Harmonization columns appended, -2. the datset with CharacteristicName, ResultSampleFractionText, +2. the dataset with CharacteristicName, ResultSampleFractionText, MethodSpecificationName, and ResultMeasure.MeasureUnitCode converted to TADA standards or From 6912271c0ed19f656b87c8442b6020fb4dc1072a Mon Sep 17 00:00:00 2001 From: Mullin Date: Tue, 18 Oct 2022 18:17:02 -0400 Subject: [PATCH 06/10] updates --- docs/articles/CONTRIBUTING.html | 16 ++++++++-------- docs/articles/WQPDataHarmonization.html | 14 ++------------ docs/index.html | 2 +- docs/pkgdown.yml | 2 +- docs/readme.html | 2 +- docs/search.json | 2 +- vignettes/WQPDataHarmonization.Rmd | 12 +----------- 7 files changed, 15 insertions(+), 35 deletions(-) diff --git a/docs/articles/CONTRIBUTING.html b/docs/articles/CONTRIBUTING.html index 0d374c16..0d366923 100644 --- a/docs/articles/CONTRIBUTING.html +++ b/docs/articles/CONTRIBUTING.html @@ -206,14 +206,14 @@

Additional References

Open-Source Code Policy

-

Effective August 8, 2016, the OMB Mandate: M-16-21; Federal Source -Code Policy: Achieving Efficiency, Transparency, and Innovation through -Reusable and Open Source Software applies to new custom-developed -code created or procured by EPA consistent with the scope and -applicability requirements of Office of Management and Budget’s (OMB’s) -Federal Source Code Policy. In general, it states that all new -custom-developed code by Federal Agencies should be made available and -reusable as open-source code.

+

Effective August 8, 2016, the OMB +Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, +Transparency, and Innovation through Reusable and Open Source +Software applies to new custom-developed code created or procured by +EPA consistent with the scope and applicability requirements of Office +of Management and Budget’s (OMB’s) Federal Source Code Policy. In +general, it states that all new custom-developed code by Federal +Agencies should be made available and reusable as open-source code.

The EPA specific implementation of OMB Mandate M-16-21 is addressed in the System Life Cycle Management Procedure. EPA has chosen to use GitHub as its diff --git a/docs/articles/WQPDataHarmonization.html b/docs/articles/WQPDataHarmonization.html index 18782d7f..9a21a12a 100644 --- a/docs/articles/WQPDataHarmonization.html +++ b/docs/articles/WQPDataHarmonization.html @@ -98,7 +98,7 @@

Install and load packages 
-list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes", "rlang", "tidyverse", "knitr", "rmarkdown", "testthat", "usethis", "devtools", "pkgdown", "Rcpp", "spelling")
+list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes", "rlang")
 
 new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
 if(length(new.packages)) install.packages(new.packages)
@@ -107,7 +107,6 @@

Install and load packages
 # If you have any issues loading the remotes library, uncomment the line below to install the "remotes" package specifying the repo
 # install.packages("remotes", repos = "http://cran.us.r-project.org")
-
 library(remotes)

Uncomment the lines below to install latest version of TADA and dataRetrieval from GitHub.

@@ -129,15 +128,6 @@

Install and load packageslibrary(stats) library(lubridate) library(rlang) -library(tidyverse) -library(knitr) -library(rmarkdown) -library(testthat) -library(usethis) -library(devtools) -library(pkgdown) -library(Rcpp) -library(spelling) library(dataRetrieval) library(TADA)

@@ -824,7 +814,7 @@

T

Optional outputs include:

  1. the dataset with Harmonization columns appended,

    2. -

  2. the datset with CharacteristicName, ResultSampleFractionText, +

  3. the dataset with CharacteristicName, ResultSampleFractionText, MethodSpecificationName, and ResultMeasure.MeasureUnitCode converted to TADA standards or

  4. the four fields converted with most Harmonization Reference Table diff --git a/docs/index.html b/docs/index.html index 6b77e1a7..ea624b81 100644 --- a/docs/index.html +++ b/docs/index.html @@ -70,7 +70,7 @@

    Welcome to TADA!

    -

    We encourage you to read this package’s CONTRIBUTING, LICENSE, and [README] information (https://usepa.github.io/TADA/index.html) (you are here).

    +

    We encourage you to read this package’s CONTRIBUTING, LICENSE, and README files (you are here).

    TADA is a draft R package being developed to help States, Tribes, Tribal Nations, Pueblos, and other stakeholders more efficiently compile and evaluate Water Quality Portal (WQP) data collected from surface water monitoring sites. TADA is a building block to support future development of the TADA R Shiny application.

    We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the CONTRIBUTING file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time.

    diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index b7eefd98..9681f792 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -4,7 +4,7 @@ pkgdown_sha: ~ articles: CONTRIBUTING: CONTRIBUTING.html WQPDataHarmonization: WQPDataHarmonization.html -last_built: 2022-10-18T21:13Z +last_built: 2022-10-18T21:55Z urls: reference: usepa.github.io/tada/reference article: usepa.github.io/tada/articles diff --git a/docs/readme.html b/docs/readme.html index 5985d50e..e778b4b9 100644 --- a/docs/readme.html +++ b/docs/readme.html @@ -52,7 +52,7 @@

    Welcome to TADA!

    -

    We encourage you to read this package’s CONTRIBUTING, LICENSE, and [README] information (https://usepa.github.io/TADA/index.html) (you are here).

    +

    We encourage you to read this package’s CONTRIBUTING, LICENSE, and README files (you are here).

    TADA is a draft R package being developed to help States, Tribes, Tribal Nations, Pueblos, and other stakeholders more efficiently compile and evaluate Water Quality Portal (WQP) data collected from surface water monitoring sites. TADA is a building block to support future development of the TADA R Shiny application.

    We encourage stakeholders to test the functionality and provide feedback. Moreover, open source software provides an avenue for water quality data originators and users to develop and share code, and we welcome your contributions! More information on how to contribute can be found in the CONTRIBUTING file. This file explains how users can contribute to the R package by submitting an issue, requesting a change, or submitting an inquiry. We hope to build a collaborative community dedicated to this effort where contributors can discover, share and build the package functionality over time.

    diff --git a/docs/search.json b/docs/search.json index 535c8e66..d850b736 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contribute-to-tada","dir":"Articles","previous_headings":"","what":"Contribute to TADA!","title":"Contributing","text":"encourage read project’s CONTRIBUTING policy (), LICENSE, README. ’re glad ’re thinking contributing EPA open source project! ’re unsure anything, just ask — submit issue pull request anyway. worst can happen ’ll politely ask change something. appreciate friendly contributions. matter , spot error, omission, bug, ’re welcome open issue repo!","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"package-development","dir":"Articles","previous_headings":"","what":"Package Development","title":"Contributing","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"what-is-github","dir":"Articles","previous_headings":"","what":"What is GitHub?","title":"Contributing","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"required-installations","dir":"Articles","previous_headings":"","what":"Required Installations","title":"Contributing","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"issues","dir":"Articles","previous_headings":"","what":"Issues","title":"Contributing","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"branches","dir":"Articles","previous_headings":"","what":"Branches","title":"Contributing","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"additional-references","dir":"Articles","previous_headings":"","what":"Additional References","title":"Contributing","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"open-source-code-policy","dir":"Articles","previous_headings":"","what":"Open-Source Code Policy","title":"Contributing","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"license","dir":"Articles","previous_headings":"","what":"License","title":"Contributing","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"disclaimer","dir":"Articles","previous_headings":"","what":"Disclaimer","title":"Contributing","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contact","dir":"Articles","previous_headings":"","what":"Contact","title":"Contributing","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"WQP Data Harmonization","text":"vignette walk discover, wrangle, harmonize Water Quality Portal (WQP) data multiple organizations.","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"install-and-load-packages","dir":"Articles","previous_headings":"","what":"Install and load packages","title":"WQP Data Harmonization","text":"install TADA, currently need install GitHub using remotes (shown) devtools. dataRetrieval downloaded CRAN, development version can downloaded directly GitHub (un-comment). following code also install packages , load packages required run vignette R session. Load remotes library installing TADA dataRetrieval GitHub Uncomment lines install latest version TADA dataRetrieval GitHub. Load required libraries run vignette R session","code":"list.of.packages <- c(\"plyr\", \"data.table\", \"dataRetrieval\", \"dplyr\", \"ggplot2\", \"grDevices\", \"magrittr\", \"stringr\", \"utils\", \"RColorBrewer\", \"stats\", \"lubridate\", \"remotes\", \"rlang\", \"tidyverse\", \"knitr\", \"rmarkdown\", \"testthat\", \"usethis\", \"devtools\", \"pkgdown\", \"Rcpp\", \"spelling\") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,\"Package\"])] if(length(new.packages)) install.packages(new.packages) # If you have any issues loading the remotes library, uncomment the line below to install the \"remotes\" package specifying the repo # install.packages(\"remotes\", repos = \"http://cran.us.r-project.org\") library(remotes) # remotes::install_github(\"USGS-R/dataRetrieval\", dependencies=TRUE) remotes::install_github(\"USEPA/TADA\", dependencies=TRUE) library(plyr) library(data.table) library(dplyr) library(ggplot2) library(grDevices) library(magrittr) library(stringr) library(utils) library(RColorBrewer) library(stats) library(lubridate) library(rlang) library(tidyverse) library(knitr) library(rmarkdown) library(testthat) library(usethis) library(devtools) library(pkgdown) library(Rcpp) library(spelling) library(dataRetrieval) library(TADA)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"retrieve-wqp-data","dir":"Articles","previous_headings":"","what":"Retrieve WQP data","title":"WQP Data Harmonization","text":"WQP data retrieved processed compatibility TADA. function, TADAdataRetrieval builds USGS dataRetrieval package functions. joins three WQP profiles (.e., station, narrow, phys/chem), changes data Characteristic, Speciation, Fraction, Unit fields uppercase, removes true duplicates, removes data non-water media types, cleans results special characters. function uses inputs dataRetrieval readWQPdata function. readWQPdata restrict characteristics pulled Water Quality Portal (WQP). may specify desired characteristics using, instance: characteristicName = “pH”. Data retrieval filters include: statecode endDate startDate countycode siteid siteType characteristicName ActivityMediaName Please aware TADAdataRetrieval function automatically runs TADA autoclean MeasureValueSpecialCharacters functions well, required subsequent functions within TADA R package run. functions alter /add following WQP columns (enter ?MeasureValueSpecialCharacters ?autoclean console details): Alters (e.g., ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric) ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue Adds (data cleaning transformations done directly “ResultMeasureValue” “DetectionLimitMeasureValue” columns, however original “ResultMeasureValue” “DetectionLimitMeasureValue” columns values WQP preserved new fields, “ResultMeasureValue.Original” “DetectionLimitMeasureValue.Original”. Additionally, “TADA.ResultMeasureValue.Flag” “TADA.DetectionLimitMeasureValue.Flag” created track changes made “ResultMeasureValue” “DetectionLimitMeasureValue” columns; provide information result values needed address censored data later (.e., nondetections). Specifically, new columns flag special characters included result values, specifies special characters . ResultMeasureValue.Original TADA.ResultMeasureValue.Flag DetectionLimitMeasureValue.Original TADA.DetectionLimitMeasureValue.Flag Downloads using TADAdataRetrieval columns time, aware data uploaded Water Quality Portal individual organizations, may may follow conventions. Data metadata quality guaranteed! Make sure carefully explore data make conservative quality assurance decisions information limited. Tips: query filters WQP work within fields ORs. example: Characteristics: choose pH & - ’s . means retrieve pH data available. States: Similarly, choose VA IL, ’s . means retrieve VA IL data available. Combinations fields ANDs, State/VA Characteristic/”. means receive data available VA. “Characteristic” “Characteristic Type” also work . means Characteristic must fall within CharacteristicGroup filters used, get error. “siteid” general term WQP uses describe Site IDs USGS databases Monitoring Location Identifiers (Water Quality Portal). monitoring location Water Quality Portal (WQP) unique Monitoring Location Identifier, regardless database derives. Monitoring Location Identifier WQP concatenated Organization Identifier plus Site ID number. Site IDs include number unique identifiers monitoring locations within USGS NWIS EPA’s WQX databases separately. Additional resources: Review function documentation entering following code console: ?TADAdataRetrieval Introduction dataRetrieval package General Data Import Water Quality Portal Water Quality Portal Web Services Guide dataRetrieval Tutorial Option 1: Use TADAdataRetrieval function. Option 2: Alternatively, can use data.table::fread function read web service call WQP profile (un-comment). Option 3: need download large amount data across large area, TADAdataRetrieval function working due WQP timeout issues, TADABigdataRetrieval function may work better. function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested. See ?TADABigdataRetrieval details. WARNING, can take multiple hours run. total run time depends query inputs. Review column names TADA Profile","code":"#You can edit this to define your own WQP query inputs below TADAProfile <- TADAdataRetrieval(statecode = \"UT\", characteristicName = c(\"Ammonia\", \"Nitrate\", \"Nitrogen\"), startDate = \"01-01-2021\") # New_Draft_fullphyschem <- data.table::fread(\"https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET\") #AllWaterTempData <- TADABigdataRetrieval(startDate = \"2019-01-01\", endDate = \"2021-12-31\", characteristicName = \"Temperature, water\", siteType = \"Stream\") colnames(TADAProfile) #> [1] \"OrganizationIdentifier\" #> [2] \"OrganizationFormalName\" #> [3] \"ActivityIdentifier\" #> [4] \"ActivityTypeCode\" #> [5] \"ActivityMediaName\" #> [6] \"ActivityMediaSubdivisionName\" #> [7] \"ActivityStartDate\" #> [8] \"ActivityStartTime.Time\" #> [9] \"ActivityStartTime.TimeZoneCode\" #> [10] \"ActivityEndDate\" #> [11] \"ActivityEndTime.Time\" #> [12] \"ActivityEndTime.TimeZoneCode\" #> [13] \"ActivityDepthHeightMeasure.MeasureValue\" #> [14] \"ActivityDepthHeightMeasure.MeasureUnitCode\" #> [15] \"ActivityDepthAltitudeReferencePointText\" #> [16] \"ActivityTopDepthHeightMeasure.MeasureValue\" #> [17] \"ActivityTopDepthHeightMeasure.MeasureUnitCode\" #> [18] \"ActivityBottomDepthHeightMeasure.MeasureValue\" #> [19] \"ActivityBottomDepthHeightMeasure.MeasureUnitCode\" #> [20] \"ProjectIdentifier\" #> [21] \"ActivityConductingOrganizationText\" #> [22] \"MonitoringLocationIdentifier\" #> [23] \"ActivityCommentText\" #> [24] \"SampleAquifer\" #> [25] \"HydrologicCondition\" #> [26] \"HydrologicEvent\" #> [27] \"SampleCollectionMethod.MethodIdentifier\" #> [28] \"SampleCollectionMethod.MethodIdentifierContext\" #> [29] \"SampleCollectionMethod.MethodName\" #> [30] \"SampleCollectionEquipmentName\" #> [31] \"ResultDetectionConditionText\" #> [32] \"CharacteristicName\" #> [33] \"ResultSampleFractionText\" #> [34] \"ResultMeasureValue\" #> [35] \"ResultMeasureValue.Original\" #> [36] \"TADA.ResultMeasureValue.Flag\" #> [37] \"ResultMeasure.MeasureUnitCode\" #> [38] \"MeasureQualifierCode\" #> [39] \"ResultStatusIdentifier\" #> [40] \"StatisticalBaseCode\" #> [41] \"ResultValueTypeName\" #> [42] \"ResultWeightBasisText\" #> [43] \"ResultTimeBasisText\" #> [44] \"ResultTemperatureBasisText\" #> [45] \"ResultParticleSizeBasisText\" #> [46] \"PrecisionValue\" #> [47] \"ResultCommentText\" #> [48] \"USGSPCode\" #> [49] \"ResultDepthHeightMeasure.MeasureValue\" #> [50] \"ResultDepthHeightMeasure.MeasureUnitCode\" #> [51] \"ResultDepthAltitudeReferencePointText\" #> [52] \"SubjectTaxonomicName\" #> [53] \"SampleTissueAnatomyName\" #> [54] \"ResultAnalyticalMethod.MethodIdentifier\" #> [55] \"ResultAnalyticalMethod.MethodIdentifierContext\" #> [56] \"ResultAnalyticalMethod.MethodName\" #> [57] \"MethodDescriptionText\" #> [58] \"LaboratoryName\" #> [59] \"AnalysisStartDate\" #> [60] \"ResultLaboratoryCommentText\" #> [61] \"DetectionQuantitationLimitTypeName\" #> [62] \"DetectionQuantitationLimitMeasure.MeasureValue\" #> [63] \"DetectionLimitMeasureValue.Original\" #> [64] \"TADA.DetectionLimitMeasureValue.Flag\" #> [65] \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" #> [66] \"PreparationStartDate\" #> [67] \"ProviderName\" #> [68] \"timeZoneStart\" #> [69] \"timeZoneEnd\" #> [70] \"ActivityStartDateTime\" #> [71] \"ActivityEndDateTime\" #> [72] \"MonitoringLocationName\" #> [73] \"MonitoringLocationTypeName\" #> [74] \"MonitoringLocationDescriptionText\" #> [75] \"HUCEightDigitCode\" #> [76] \"DrainageAreaMeasure.MeasureValue\" #> [77] \"DrainageAreaMeasure.MeasureUnitCode\" #> [78] \"ContributingDrainageAreaMeasure.MeasureValue\" #> [79] \"ContributingDrainageAreaMeasure.MeasureUnitCode\" #> [80] \"LatitudeMeasure\" #> [81] \"LongitudeMeasure\" #> [82] \"SourceMapScaleNumeric\" #> [83] \"HorizontalAccuracyMeasure.MeasureValue\" #> [84] \"HorizontalAccuracyMeasure.MeasureUnitCode\" #> [85] \"HorizontalCollectionMethodName\" #> [86] \"HorizontalCoordinateReferenceSystemDatumName\" #> [87] \"VerticalMeasure.MeasureValue\" #> [88] \"VerticalMeasure.MeasureUnitCode\" #> [89] \"VerticalAccuracyMeasure.MeasureValue\" #> [90] \"VerticalAccuracyMeasure.MeasureUnitCode\" #> [91] \"VerticalCollectionMethodName\" #> [92] \"VerticalCoordinateReferenceSystemDatumName\" #> [93] \"CountryCode\" #> [94] \"StateCode\" #> [95] \"CountyCode\" #> [96] \"AquiferName\" #> [97] \"LocalAqfrName\" #> [98] \"FormationTypeText\" #> [99] \"AquiferTypeName\" #> [100] \"ConstructionDateText\" #> [101] \"WellDepthMeasure.MeasureValue\" #> [102] \"WellDepthMeasure.MeasureUnitCode\" #> [103] \"WellHoleDepthMeasure.MeasureValue\" #> [104] \"WellHoleDepthMeasure.MeasureUnitCode\" #> [105] \"MethodSpecificationName\" #> [106] \"ProjectName\" #> [107] \"ProjectDescriptionText\" #> [108] \"SamplingDesignTypeCode\" #> [109] \"QAPPApprovedIndicator\" #> [110] \"QAPPApprovalAgencyName\" #> [111] \"ProjectFileUrl\" #> [112] \"ProjectMonitoringLocationWeightingUrl\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"depth-unit-conversions","dir":"Articles","previous_headings":"","what":"Depth unit conversions","title":"WQP Data Harmonization","text":"Converts depth units consistent unit. ActivityDepthHeightMeasure.MeasureValue provides depth information. crucial column lake data less often river data. Function checks dataset depth profile data. depth profile columns populated, function appends ‘Conversion Factor’ columns populates columns based original unit (MeasureUnitCode columns) target unit, defined ‘unit’ argument. ‘Depth Target Unit’ column also appended, indicating unit selected depth data converted . transform = FALSE, output includes ‘Conversion Factor’ columns ‘Depth Target Unit’ column. transform = TRUE, output includes converted depth data ‘Depth Target Unit’ column, acts flag indicating rows converted. Default transform = TRUE. depth profile function can harmonize depth units across following fields (specific one): “ActivityDepthHeightMeasure”, “ActivityTopDepthHeightMeasure”, “ActivityBottomDepthHeightMeasure”, “ResultDepthHeightMeasure”). default . Allowable values ‘unit’ either ‘m’ (meter), ‘ft’ (feet), ‘’ (inch). ‘unit’ accepts one allowable value input. Default unit = “m”. See additional function documentation additional function options entering following code console: ?DepthProfileData","code":"#converts all depth profile data to meters TADAProfileClean1 <- DepthProfileData(TADAProfile, unit = \"m\", transform = TRUE) #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"result-unit-conversions","dir":"Articles","previous_headings":"","what":"Result unit conversions","title":"WQP Data Harmonization","text":"Converts results WQX target units. WQX target units pulled MeasureUnit domain table: https://cdx.epa.gov/wqx/download/DomainValues/MeasureUnit.CSV See additional function documentation additional function options entering following code console: ?WQXTargetUnits","code":"#Converts all results to WQX target units TADAProfileClean2 <- WQXTargetUnits(TADAProfileClean1, transform = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"statistically-aggregated-data","dir":"Articles","previous_headings":"","what":"Statistically aggregated data","title":"WQP Data Harmonization","text":"Checks removes statistically aggregated high frequency (.e., continuous) data, present. Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = “Reported Raw Data (attached)” clean = TRUE, rows aggregated continuous data removed dataset column appended Default clean = TRUE See function documentation additional function options entering following code console: ?DepthProfileData","code":"TADAProfileClean3 <- AggregatedContinuousData(TADAProfileClean2, clean = TRUE) #> [1] \"The dataset does not contain aggregated continuous data.\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-qaqc-service-result-flags","dir":"Articles","previous_headings":"","what":"WQX QAQC Service Result Flags","title":"WQP Data Harmonization","text":"Run following result functions address invalid method, fraction, speciation, unit metadata characteristic. default clean = TRUE, remove invalid results. can change clean = FALSE flag results, remove . See documentation details: ?InvalidMethod Clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidSpeciation clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidResultUnit clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidFraction clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended.","code":"TADAProfileClean4 <- InvalidMethod(TADAProfileClean3, clean = TRUE) #> [1] \"No changes were made, because we did not find any invalid method/characteristic combinations in your dataset.\" TADAProfileClean5 <- InvalidFraction(TADAProfileClean4, clean = TRUE) #> [1] \"All data is valid, therefore the function cannot be applied.\" TADAProfileClean6 <- InvalidSpeciation(TADAProfileClean5, clean = FALSE) TADAProfileClean7 <- InvalidResultUnit(TADAProfileClean6, clean = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-national-upper-and-lower-thresholds","dir":"Articles","previous_headings":"","what":"WQX national upper and lower thresholds","title":"WQP Data Harmonization","text":"Run following code flag remove results national upper lower bound characteristic unit combination. See documentation details: ?AboveNationalWQXUpperThreshold clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset. ?BelowNationalWQXUpperThreshold clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset. default clean=TRUE, can change flag results desired. Results flagged, removed, clean=FALSE.","code":"TADAProfileClean8 <- AboveNationalWQXUpperThreshold(TADAProfileClean7, clean = TRUE) TADAProfileClean9 <- BelowNationalWQXUpperThreshold(TADAProfileClean8, clean = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"potential-duplicates","dir":"Articles","previous_headings":"","what":"Potential duplicates","title":"WQP Data Harmonization","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. information, review documentation entering following console: ?PotentialDuplicateRowID clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":"TADAProfileClean10 <- PotentialDuplicateRowID(TADAProfileClean9)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"invalid-coordinates","dir":"Articles","previous_headings":"","what":"Invalid coordinates","title":"WQP Data Harmonization","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled “TADA.InvalidCoordinates” following flags (relevant dataset). latitude less zero, row flagged “LAT_OutsideUSA”. longitude greater zero less 145, row flagged “LONG_OutsideUSA”. latitude longitude contains string, “999”, row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged “Imprecise”.","code":"TADAProfileClean11 <- InvalidCoordinates(TADAProfileClean10, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"review-qapp-information","dir":"Articles","previous_headings":"","what":"Review QAPP information","title":"WQP Data Harmonization","text":"Check data approved QAPP function checks see information column “QAPPApprovedIndicator”. organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . field, Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. defaults remove rows data QAPPApprovedIndicator equals “N”. Users alternatively remove N’s NA’s using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function anything. Check see QAPP Doc Available function checks data submitted “ProjectFileUrl” column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":"TADAProfileClean12 <- QAPPapproved(TADAProfileClean11, clean = TRUE, cleanNA = FALSE) TADAProfileClean13 <- QAPPDocAvailable(TADAProfileClean12, clean = FALSE) #> Warning in QAPPDocAvailable(TADAProfileClean12, clean = FALSE): The dataset does #> not contain QAPP document url data."},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field","dir":"Articles","previous_headings":"","what":"Filter data by field","title":"WQP Data Harmonization","text":"section TADA user want review unique values specific fields may choose remove data particular values. start, review list fields number unique values field. Next, choose field list see unique values field, well number times value appears dataset. ’ll start ActivityTypeCode. list fields review: ResultCommentText often details relating additional QA. MeasureQualifierCode Contains information data flags 3. codes may designate suspect data flags may described detail ResultLaboratoryCommentText another column ActivityTypeCode field four unique values – “Sample-Routine”, “Quality Control Sample-Field Replicate”, “Field Msr/Obs”, “Quality Control Sample-Field Blank.” example want remove quality control values ActivityTypeCode field, therefore, ’ll specify want remove “Quality Control Sample-Field Replicate” “Quality Control Sample-Field Blank” values ActivityTypeCode field. ’ve completed review ActivityTypeCode field. Let’s move different field see values want remove – ’ll look values ResultStatusIdentifier field. ActivityMediaSubdivisionName field two unique values, “Surface Water” “Groundwater.” example want remove “Groundwater” values.","code":"FilterFields(TADAProfileClean13) #> FieldName Count #> 1 OrganizationFormalName 7 #> 2 ActivityTypeCode 7 #> 3 ActivityMediaName 1 #> 4 ActivityMediaSubdivisionName 4 #> 5 ActivityCommentText 4 #> 6 HydrologicCondition 8 #> 7 HydrologicEvent 4 #> 8 CharacteristicName 3 #> 9 MeasureQualifierCode 4 #> 10 SampleTissueAnatomyName 1 #> 11 LaboratoryName 11 #> 12 DetectionQuantitationLimitTypeName 7 #> 13 MonitoringLocationTypeName 14 #> 14 ProjectName 8 FilterFieldReview(\"ActivityTypeCode\", TADAProfileClean13) #> FieldValue Count #> 7 Sample-Routine 5268 #> 6 Sample-Integrated Vertical Profile 474 #> 4 Quality Control Sample-Field Replicate 454 #> 2 Quality Control Sample-Equipment Blank 276 #> 3 Quality Control Sample-Field Blank 60 #> 1 Field Msr/Obs 4 #> 5 Quality Control Sample-Lab Duplicate 2 TADAProfileClean14 <- dplyr::filter(TADAProfileClean13, !(ActivityTypeCode %in% c(\"Quality Control Sample-Field Replicate\", \"Quality Control Sample-Field Blank\", \"Quality Control Sample-Lab Duplicate\", \"Quality Control Sample-Equipment Blank\"))) FilterFieldReview(\"ActivityMediaSubdivisionName\", TADAProfileClean14) #> FieldValue Count #> 3 Surface Water 687 #> 2 Groundwater 106 #> 1 Bulk deposition 1 TADAProfileClean15 <- dplyr::filter(TADAProfileClean14, !(ActivityMediaSubdivisionName %in% c(\"Groundwater\", \"Bulk deposition\")))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field-subset-by-parameter","dir":"Articles","previous_headings":"","what":"Filter data by field, subset by parameter","title":"WQP Data Harmonization","text":"section TADA user want select parameter, review unique values associated parameter specific fields, choose remove particular values. start, review list parameters dataset. (list sorted highest lowest counts. first rows displayed save space page) Next, select parameter. Let’s explore fields associated Nitrogen: Selecting parameter generates list , subset selected parameter, fields number unique values field. choose field list. example ’ll remove certain values HydrologicEvent field. HydrologicEvent field three unique values. example want remove samples collected “Storm” events. Therefore, ’ll specify want remove rows CharacteristicName “NITROGEN” HydrologicEvent field “Storm.”","code":"FilterParList(TADAProfileClean15) #> FieldValue Count #> 3 NITROGEN 4130 #> 2 NITRATE 1479 #> 1 AMMONIA 30 FilterParFields(TADAProfileClean15, \"NITROGEN\") #> FieldName Count #> 1 ActivityTypeCode 2 #> 2 ActivityMediaName 1 #> 3 ActivityMediaSubdivisionName 2 #> 4 ActivityCommentText 3 #> 5 HydrologicCondition 7 #> 6 HydrologicEvent 2 #> 7 SampleCollectionMethod.MethodIdentifier 6 #> 8 SampleCollectionMethod.MethodIdentifierContext 2 #> 9 SampleCollectionMethod.MethodName 6 #> 10 SampleCollectionEquipmentName 6 #> 11 ResultSampleFractionText 3 #> 12 ResultMeasure.MeasureUnitCode 2 #> 13 MeasureQualifierCode 3 #> 14 ResultStatusIdentifier 2 #> 15 ResultValueTypeName 1 #> 16 ResultWeightBasisText 1 #> 17 ResultTemperatureBasisText 1 #> 18 ResultParticleSizeBasisText 1 #> 19 ResultCommentText 7 #> 20 ResultAnalyticalMethod.MethodIdentifier 2 #> 21 ResultAnalyticalMethod.MethodIdentifierContext 2 #> 22 ResultAnalyticalMethod.MethodName 2 #> 23 MethodDescriptionText 1 #> 24 LaboratoryName 2 #> 25 ResultLaboratoryCommentText 5 #> 26 DetectionQuantitationLimitTypeName 2 #> 27 MonitoringLocationTypeName 11 FilterParFieldReview(\"HydrologicEvent\", TADAProfileClean15, \"NITROGEN\") #> FieldValue Count #> 1 Routine sample 59 TADAProfileClean16 <- dplyr::filter(TADAProfileClean15, !(CharacteristicName %in% \"NITROGEN\" & HydrologicEvent %in% \"Storm\"))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"transform-characteristic-speciation-and-unit-values-to-tada-standards","dir":"Articles","previous_headings":"","what":"Transform Characteristic, Speciation, and Unit values to TADA Standards","title":"WQP Data Harmonization","text":"HarmonizeRefTable function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values following elements: CharacteristicName ResultSampleFractionText MethodSpecicationName ResultMeasure.MeasureUnitCode HarmonizeData function compares input dataset TADA Harmonization Reference Table. purpose function make similar data consistent therefore easier compare analyze. Users can also edit reference file meet needs desired. download argument can used save harmonization file current working directory download = TRUE, default download = FALSE. Optional outputs include: dataset Harmonization columns appended, datset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE. examples HarmonizeData function can used: ResultSampleFractionText specifies forms constituents. cases, single CharacteristicName “Total” “Dissolved” forms specified, combined. cases, CharacteristicName ResultSampleFractionText combination given different identifier. identifier can used later identify comparable data groups calculating statistics creating figures combination. variables different names represent constituent (e.g., “Total Kjeldahl nitrogen (Organic N & NH3)” “Kjeldahl nitrogen”). HarmonizeData function gives consistent name (identifier) synonyms.","code":"UniqueHarmonizationRef <- HarmonizationRefTable(TADAProfileClean16, download = FALSE) TADAProfileClean17 <- HarmonizeData(TADAProfileClean16, ref = UniqueHarmonizationRef, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Cristina Mullin. Author, maintainer. Michelle Thawley. Author. Laura Shumway. Author. Jacob Greif. Author.","code":""},{"path":"usepa.github.io/tada/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Mullin, C.., Greif, J., Thawley, M., Shumway, L., 2022, TADA: R Tools Automated Data Assessment, U.S. Environmental Protection Agency, Washington, DC","code":"@Manual{, author = {Cristina A. Mullin and Jacob Greif and Michelle Thawley and Laura Shumway}, title = {TADA: R Tools for Automated Data Assessment}, address = {Washington, DC}, institution = {U.S. Environmental Protection Agency}, year = {2022}, url = {https://github.com/USEPA/TADA}, }"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"package-development","dir":"","previous_headings":"","what":"Package Development","title":"NA","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"what-is-github","dir":"","previous_headings":"","what":"What is GitHub?","title":"NA","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"required-installations","dir":"","previous_headings":"","what":"Required Installations","title":"NA","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"NA","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"branches","dir":"","previous_headings":"","what":"Branches","title":"NA","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"additional-references","dir":"","previous_headings":"","what":"Additional References","title":"NA","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/index.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"Tools for Automated Data Assessment R Package","text":"encourage read package’s CONTRIBUTING, LICENSE, [README] information (https://usepa.github.io/TADA/index.html) (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/index.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"Tools for Automated Data Assessment R Package","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Tools for Automated Data Assessment R Package","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/index.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"Tools for Automated Data Assessment R Package","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Tools for Automated Data Assessment R Package","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/index.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"Tools for Automated Data Assessment R Package","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Tools for Automated Data Assessment R Package","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":[]},{"path":"usepa.github.io/tada/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"CC0 1.0 Universal","title":"CC0 1.0 Universal","text":"CREATIVE COMMONS CORPORATION LAW FIRM PROVIDE LEGAL SERVICES. DISTRIBUTION DOCUMENT CREATE ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES INFORMATION “-” BASIS. CREATIVE COMMONS MAKES WARRANTIES REGARDING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER, DISCLAIMS LIABILITY DAMAGES RESULTING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER.","code":""},{"path":"usepa.github.io/tada/LICENSE.html","id":"statement-of-purpose","dir":"","previous_headings":"","what":"Statement of Purpose","title":"CC0 1.0 Universal","text":"laws jurisdictions throughout world automatically confer exclusive Copyright Related Rights (defined ) upon creator subsequent owner(s) (, “owner”) original work authorship /database (, “Work”). Certain owners wish permanently relinquish rights Work purpose contributing commons creative, cultural scientific works (“Commons”) public can reliably without fear later claims infringement build upon, modify, incorporate works, reuse redistribute freely possible form whatsoever purposes, including without limitation commercial purposes. owners may contribute Commons promote ideal free culture production creative, cultural scientific works, gain reputation greater distribution Work part use efforts others. /purposes motivations, without expectation additional consideration compensation, person associating CC0 Work (“Affirmer”), extent owner Copyright Related Rights Work, voluntarily elects apply CC0 Work publicly distribute Work terms, knowledge Copyright Related Rights Work meaning intended legal effect CC0 rights. Copyright Related Rights. Work made available CC0 may protected copyright related neighboring rights (“Copyright Related Rights”). 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Affirmer disclaims responsibility clearing rights persons may apply Work use thereof, including without limitation person’s Copyright Related Rights Work. , Affirmer disclaims responsibility obtaining necessary consents, permissions rights required use Work. Affirmer understands acknowledges Creative Commons party document duty obligation respect CC0 use Work.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"NA","text":"encourage read package’s CONTRIBUTING, LICENSE, [README] information (https://usepa.github.io/TADA/index.html) (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"NA","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"NA","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/readme.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data upper threshold result values submitted WQX given characteristic. clean = TRUE, rows values upper WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"","code":"AboveNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data upper WQX threshold dataset clean = TRUE. Default clean = TRUE","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Aggregated Continuous Data — AggregatedContinuousData","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = \"Reported Raw Data (attached)\". clean = TRUE, rows aggregated continuous data removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"","code":"AggregatedContinuousData(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":".data TADA dataframe clean Boolean argument; removes aggregated continuous data dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"clean = FALSE, column flagging rows aggregated continuous data appended input data set. clean = TRUE, aggregated continuous data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — autoclean","title":"autoclean — autoclean","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — autoclean","text":"","code":"autoclean(.data)"},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — autoclean","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — autoclean","text":"autocleaned TADA data profile","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — autoclean","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":null,"dir":"Reference","previous_headings":"","what":"AutoFilter — AutoFilter","title":"AutoFilter — AutoFilter","text":"Function can used autofilter simplify WQP dataset. applying function, dataset contain result values water media types chemicals tissue (e.g. mercury fish tissue). complex biological data (counts macroinvertebrates) removed. function looks following fields autofilter: ActivityMediaName, ActivityMediaSubDivisionName, AssemblageSampledName","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AutoFilter — AutoFilter","text":"","code":"AutoFilter(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AutoFilter — AutoFilter","text":".data TADA dataframe clean Indicates whether flag columns appended data (clean = FALSE), flagged data transformed/filtered dataset columns appended (clean = TRUE).","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"AutoFilter — AutoFilter","text":"clean = FALSE, flag column appended dataset. clean = TRUE, flag column appended relevant rows removed.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data lower threshold result values submitted WQX given characteristic. clean = TRUE, rows values lower WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"","code":"BelowNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data lower WQX threshold dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalnumcount — decimalnumcount","title":"decimalnumcount — decimalnumcount","text":"character data type","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalnumcount — decimalnumcount","text":"","code":"decimalnumcount(x)"},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalnumcount — decimalnumcount","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalnumcount — decimalnumcount","text":"Number values right decimal point character type data.","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalplaces — decimalplaces","title":"decimalplaces — decimalplaces","text":"numeric data type","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalplaces — decimalplaces","text":"","code":"decimalplaces(x)"},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalplaces — decimalplaces","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalplaces — decimalplaces","text":"Number values right decimal point numeric type data.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":null,"dir":"Reference","previous_headings":"","what":"Depth Profile Flag & Unit Conversion — DepthProfileData","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Function checks dataset depth profile data. depth profile columns populated, function appends 'Conversion.Factor' columns populates columns based original unit (MeasureUnitCode columns) target unit, defined 'unit' argument. 'WQX.Depth.TargetUnit' column also appended, indicating unit selected depth data converted . transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"","code":"DepthProfileData( .data, unit = \"m\", fields = c(\"ActivityDepthHeightMeasure\", \"ActivityTopDepthHeightMeasure\", \"ActivityBottomDepthHeightMeasure\", \"ResultDepthHeightMeasure\"), transform = TRUE )"},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":".data TADA dataframe unit Character string input indicating uniform unit depth data converted . Allowable values 'unit' either 'm' (meter), 'ft' (feet), '' (inch). 'unit' accepts one allowable value input. Default unit = \"m\". fields Character string input indicating depth fields checked data. Allowable values 'fields' 'ActivityDepthHeightMeasure,' 'ActivityTopDepthHeightMeasure,' 'ActivityBottomDepthHeightMeasure,' 'ResultDepthHeightMeasure.'. Default include allowable values. transform Boolean argument; transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'Depth Target Unit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Full dataset converted uniform depth units 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. transform = FALSE, output full dataset 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field — FilterFieldReview","title":"Generate list of unique values in a given field — FilterFieldReview","text":"Function creates table pie chart unique values, counts values chosen field dataframe.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field — FilterFieldReview","text":"","code":"FilterFieldReview(field, .data)"},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field — FilterFieldReview","text":"field Field name .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field — FilterFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names — FilterFields","title":"Generate list of field names — FilterFields","text":"Function creates list fields input dataframe well number unique values field. list intended inform users specific fields explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names — FilterFields","text":"","code":"FilterFields(.data)"},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names — FilterFields","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names — FilterFields","text":"table fields count unique values field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"Function creates table pie chart unique values, counts values, chosen field dataframe subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"","code":"FilterParFieldReview(field, .data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"field Field name .data Optional argument; TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names subset by parameter — FilterParFields","title":"Generate list of field names subset by parameter — FilterParFields","text":"Function subsets input dataframe input parameter creates list fields subset dataframe well number unique values field. list intended inform users specific fields explore filter subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names subset by parameter — FilterParFields","text":"","code":"FilterParFields(.data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names subset by parameter — FilterParFields","text":".data TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names subset by parameter — FilterParFields","text":"table fields count unique values field, subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of parameters — FilterParList","title":"Generate list of parameters — FilterParList","text":"Function generates list characteristics input dataset, well number records . list intended inform users parameters explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of parameters — FilterParList","text":"","code":"FilterParList(.data)"},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of parameters — FilterParList","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of parameters — FilterParList","text":"list unique characteristics counts","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":null,"dir":"Reference","previous_headings":"","what":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Function summarizes censored data dataset, including substitutions made.","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"","code":"GenerateCensoredDataStats(.data)"},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":".data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Summary table","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table — GetMeasureUnitRef","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"Function downloads returns latest WQX MeasureUnit Domain table, adds additional target unit information, writes data sysdata.rda.","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"","code":"GetMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"sysdata.rda updated WQXunitRef object (unit conversion reference table)","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Function downloads returns newest available (cleaned) raw Water Quality Exchange (WQX) QAQC Characteristic Validation reference table. WQXcharValRef data frame contains information four functions: InvalidFraction, InvalidResultUnit, InvalidSpeciation, UncommonAnalyticalMethodID.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"","code":"GetWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Updated sysdata.rda updated WQXcharValRef object","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode can optionally edit reference file meet needs.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"","code":"HarmonizationRefTable(.data, download = FALSE)"},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":".data TADA dataframe download Boolean argument; download = TRUE, output downloaded current working directory.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Harmonization Reference Table unique input dataset","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"Function compares input dataset TADA Harmonization Reference Table, makes synonymous data consistent. Optional outputs include: 1) dataset Harmonization columns appended, 2) dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards 3) four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"","code":"HarmonizeData(.data, ref, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":".data TADA dataframe ref Optional argument specify dataframe use reference file. primary use argument user generated harmonization reference file unique data, made changes file. transform Boolean argument; transforms /converts original values dataset TADA Harmonization Reference Table values following fields: CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode. Default transform = TRUE. flag Boolean argument; appends columns TADA Harmonization Reference Table dataframe. Default flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"transform = FALSE flag = TRUE, Harmonization Reference Table columns appended dataset . transform = TRUE flag = TRUE, Harmonization columns appended dataset transformations executed. transform = TRUE flag = FALSE, transformations executed . transform = FALSE flag = FALSE, error returned (function return input dataframe unchanged input allowed).","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":null,"dir":"Reference","previous_headings":"","what":"Invalid coordinates — InvalidCoordinates","title":"Invalid coordinates — InvalidCoordinates","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled \"TADA.InvalidCoordinates\" following flags (relevant dataset). latitude less zero, row flagged \"LAT_OutsideUSA\". longitude greater zero less 145, row flagged \"LONG_OutsideUSA\". latitude longitude contains string, \"999\", row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged \"Imprecise\".","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Invalid coordinates — InvalidCoordinates","text":"","code":"InvalidCoordinates(.data, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Invalid coordinates — InvalidCoordinates","text":".data TADA dataframe clean_outsideUSA Boolean argument; removes data coordinates outside United States clean_outsideUSA = TRUE. Default clean = FALSE. clean_imprecise Boolean arguments; removes imprecise data clean_imprecise = TRUE. Default clean_imprecise = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Invalid coordinates — InvalidCoordinates","text":"either clean_outsideUSA clean_imprecise argument FALSE, column flagging rows respective QA check appended input dataset. either argument TRUE, \"invalid\" \"imprecise\" data removed, respectively.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Sample Fraction Validity — InvalidFraction","title":"Check Sample Fraction Validity — InvalidFraction","text":"Function checks validity characteristic-fraction combination dataset. clean = TRUE, rows invalid characteristic-fraction combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Sample Fraction Validity — InvalidFraction","text":"","code":"InvalidFraction(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Sample Fraction Validity — InvalidFraction","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-fraction combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Sample Fraction Validity — InvalidFraction","text":"clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Invalid Analytical Methods — InvalidMethod","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"Function checks validity characteristic-analytical method combination dataset. clean = TRUE, rows invalid characteristic-analytical method combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"","code":"InvalidMethod(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Invalid Analytical Methods — InvalidMethod","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-analytical method combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Unit Validity — InvalidResultUnit","title":"Check Result Unit Validity — InvalidResultUnit","text":"Function checks validity characteristic-media-result unit combination dataset. clean = TRUE, rows invalid characteristic-media-result unit combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Unit Validity — InvalidResultUnit","text":"","code":"InvalidResultUnit(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Unit Validity — InvalidResultUnit","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-media-result unit combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Unit Validity — InvalidResultUnit","text":"clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Method Speciation Validity — InvalidSpeciation","title":"Check Method Speciation Validity — InvalidSpeciation","text":"Function checks validity characteristic-method speciation combination dataset. clean = TRUE, rows invalid characteristic-method speciation combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Method Speciation Validity — InvalidSpeciation","text":"","code":"InvalidSpeciation(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Method Speciation Validity — InvalidSpeciation","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-method speciation combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Method Speciation Validity — InvalidSpeciation","text":"#'clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Function checks special characters non-numeric values ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields appends flag columns indicating special characters included , special characters . ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields also converted class numeric.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"","code":"MeasureValueSpecialCharacters(.data)"},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Full dataset column indicating presence special characters ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields. Additionally, ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric, copies column created preserve original character values.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"usepa.github.io/tada/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Potential Duplicates — PotentialDuplicateRowID","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"","code":"PotentialDuplicateRowID(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":".data TADA dataframe clean Boolean argument; removes potential duplicate data dataset clean = TRUE. clean = FALSE, column indicating potential duplicate rows unique number linking rows appended input data set. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":null,"dir":"Reference","previous_headings":"","what":"Check data for an approved QAPP — QAPPapproved","title":"Check data for an approved QAPP — QAPPapproved","text":"Function checks data submitted column \"QAPPApprovedIndicator\". organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. default removes rows data QAPPApprovedIndicator equals \"N\". Users alternatively remove N's NA's using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function make changes data.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check data for an approved QAPP — QAPPapproved","text":"","code":"QAPPapproved(.data, clean = TRUE, cleanNA = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check data for an approved QAPP — QAPPapproved","text":".data TADA dataframe clean Boolean argument two possible values called \"TRUE\" \"FALSE\". clean=TRUE, rows data QAPPApprovedIndicator equals \"N\" removed. , clean=FALSE, rows data QAPPApprovedIndicator equals \"N\" retained. cleanNA Boolean argument two possible values called \"TRUE\" \"FALSE\". cleanNA=TRUE, rows data QAPPApprovedIndicator equals \"NA\" removed. , cleanNA=FALSE, rows data QAPPApprovedIndicator equals \"NA\" retained.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check data for an approved QAPP — QAPPapproved","text":"clean = FALSE cleanNA = FALSE, data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check data for an approved QAPP — QAPPapproved","text":"Note: required field, often left blank (NA) even data associated QAPP. states tribes collect monitoring data using 106 funding (almost state tribal data WQX) required EPA approved QAPP receive 106 funding. Therefore, organizations data approved QAPP even data submitted WQP NA.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"Function checks data submitted \"ProjectFileUrl\" column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"","code":"QAPPDocAvailable(.data, clean = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":".data TADA dataframe clean Boolean argument; removes data without associated QAPP document dataset clean = TRUE. Default clean = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"clean = FALSE, column appended input data set flags rows associated QAPP document. clean = TRUE, data without associated QAPP document removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":null,"dir":"Reference","previous_headings":"","what":"Read in WQP data using WQP web services directly — readWQPwebservice","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Go WQP website (https://www.waterqualitydata.us/) fill advanced query form. Choose Full Physical Chemical Data Profile, data sources, file format Comma-Separated. finished, hit download button. Instead, copy web service URL located bottom page header \"Result\". Use \"Result\" web service URL input function download data directly R.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"","code":"readWQPwebservice(webservice)"},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"webservice WQP Web Service URL, entered within quotes \"url\"","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"WQP Full Physical Chemical Results Data Profile","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Note: may useful save Query URL well comment within code. URL return WQP query page original data filters.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"RemoveEmptyColumns — RemoveEmptyColumns","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Removes columns NA values. Used quickly reduce number columns dataframe improve management readability dataset.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"","code":"RemoveEmptyColumns(.data)"},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":".data Dataframe","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Full dataset empty data columns removed","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"TADABigdataRetrieval( startDate = \"null\", endDate = \"null\", characteristicName = \"null\", siteType = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"startDate Start Date YYYY-MM-DD format, example, \"1995-01-01\" endDate end date YYYY-MM-DD format, example, \"2020-12-31\" characteristicName Name water quality parameter siteType Name water body type (e.g., \"Stream\", \"Lake, Reservoir, Impoundment\")","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"Similarly TADAdataRetrieval function, function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"if (FALSE) { tada2 <- TADABigdataRetrieval(startDate = \"01-01-2021\", endDate = \"01-01-2022\", characteristicName = \"Nitrogen\", siteType = \"Stream\") }"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Retrieve data Water Quality Portal (WQP) output TADA-compatible dataset.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"TADAdataRetrieval( statecode = \"null\", startDate = \"null\", countycode = \"null\", siteid = \"null\", siteType = \"null\", characteristicName = \"null\", ActivityMediaName = \"null\", endDate = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"statecode Code identifies state startDate Start Date countycode Code identifies county siteid Unique monitoring station identifier siteType Type waterbody characteristicName Name parameter ActivityMediaName Sampling substrate water, air, sediment endDate End Date","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Keep mind query filters WQP work within fields ORs. example, characteristics – choose pH & – ’s . Similarly, choose VA IL, ’s . combo fields ANDs. State/VA Characteristic/\". \"Characteristic\" \"Characteristic Group\" also work . function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"if (FALSE) { tada1 <- TADAdataRetrieval(statecode = \"WI\", countycode = \"Dane\", characteristicName = \"Phosphorus\") }"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — TADAprofileCheck","title":"autoclean — TADAprofileCheck","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — TADAprofileCheck","text":"","code":"TADAprofileCheck(.data)"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — TADAprofileCheck","text":".data dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — TADAprofileCheck","text":"cleaned TADA data profile TADA Profile Check function checks column names dataframe include TADA profile fields. used beginning TADA functions ensure input data frame suitable (.e. either full physical/chemical results profile downloaded WQP TADA profile template downloaded EPA TADA webpage.) Boolean result indicating whether input dataframe contains TADA profile fields.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — TADAprofileCheck","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":null,"dir":"Reference","previous_headings":"","what":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"Function substitutes monitoring device/method detection limits (available) result values applicable.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"","code":"TransformCensoredData(transform, .data)"},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE. .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform=TRUE, monitoring device/method detection limits (available) substituted result values units. transform = FALSE, monitoring device/method detection limits (available) substituted result values units - Instead, columns appended rows may include censored data. flag indicates 1) row contains censored data, 2) monitoring device/method detection limits available.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Existing Data in sysdata.rda — UpdateInternalData","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Function internal use . used internal functions used update internal data (e.g. reference tables). function adapted stackoverflow.com thread, can accessed .","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"","code":"UpdateInternalData(..., list = character())"},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"... Objects updated sysdata.rda. list Argument indicating data class list.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Updated sysdata.rda file","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"Update Measure Unit Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"","code":"UpdateMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"Update Characteristic Validation Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"","code":"UpdateWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"Used store cached WQX QAQC Characteristic Validation Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"","code":"WQXCharValRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"object class NULL length 0.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Units to WQX Target Units — WQXTargetUnits","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function compares measure units input data Water Quality Exchange (WQX) 3.0 QAQC Characteristic Validation table.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"","code":"WQXTargetUnits(.data, transform = TRUE)"},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":".data TADA dataset transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"transform=TRUE, result values units converted WQX target units. function changes values within \"ResultMeasure.MeasureUnitCode\" \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" WQX target units converts respective values within \"ResultMeasureValue\" \"DetectionQuantitationLimitMeasure.MeasureValue\" fields. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=TRUE add following two fields input dataset, \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\", retain original result unit values. transform = FALSE, result values units converted WQX target units, columns appended indicate target units conversion factors , data can converted. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=FALSE add following two fields input dataset: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function ALWAYS add following two columns input dataset: \"WQX.ResultMeasureValue.UnitConversion\", \"WQX.DetectionLimitMeasureValue.UnitConversion\" two fields indicate data can converted.\"NoResultValue\" means data converted ResultMeasureValue, \"NoTargetUnit\" means data converted original unit associated target unit WQX. \"Convert\" means data can transformed, \"Converted\" means function run input transform = TRUE, values already converted. also uses following six fields input dataset: \"CharacteristicName\", \"ActivityMediaName\", \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" function adds following two fields transforms values within following four fields transform=TRUE: Adds: \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\". Transforms: \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\". function adds following two fields transform=FALSE: Adds: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"Used store cached Measure Unit Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"","code":"WQXunitRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"object class NULL length 0.","code":""}] +[{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contribute-to-tada","dir":"Articles","previous_headings":"","what":"Contribute to TADA!","title":"Contributing","text":"encourage read project’s CONTRIBUTING policy (), LICENSE, README. ’re glad ’re thinking contributing EPA open source project! ’re unsure anything, just ask — submit issue pull request anyway. worst can happen ’ll politely ask change something. appreciate friendly contributions. matter , spot error, omission, bug, ’re welcome open issue repo!","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"package-development","dir":"Articles","previous_headings":"","what":"Package Development","title":"Contributing","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"what-is-github","dir":"Articles","previous_headings":"","what":"What is GitHub?","title":"Contributing","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"required-installations","dir":"Articles","previous_headings":"","what":"Required Installations","title":"Contributing","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"issues","dir":"Articles","previous_headings":"","what":"Issues","title":"Contributing","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"branches","dir":"Articles","previous_headings":"","what":"Branches","title":"Contributing","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"additional-references","dir":"Articles","previous_headings":"","what":"Additional References","title":"Contributing","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"open-source-code-policy","dir":"Articles","previous_headings":"","what":"Open-Source Code Policy","title":"Contributing","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"license","dir":"Articles","previous_headings":"","what":"License","title":"Contributing","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"disclaimer","dir":"Articles","previous_headings":"","what":"Disclaimer","title":"Contributing","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contact","dir":"Articles","previous_headings":"","what":"Contact","title":"Contributing","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"WQP Data Harmonization","text":"vignette walk discover, wrangle, harmonize Water Quality Portal (WQP) data multiple organizations.","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"install-and-load-packages","dir":"Articles","previous_headings":"","what":"Install and load packages","title":"WQP Data Harmonization","text":"install TADA, currently need install GitHub using remotes (shown) devtools. dataRetrieval downloaded CRAN, development version can downloaded directly GitHub (un-comment). following code also install packages , load packages required run vignette R session. Load remotes library installing TADA dataRetrieval GitHub Uncomment lines install latest version TADA dataRetrieval GitHub. Load required libraries run vignette R session","code":"list.of.packages <- c(\"plyr\", \"data.table\", \"dataRetrieval\", \"dplyr\", \"ggplot2\", \"grDevices\", \"magrittr\", \"stringr\", \"utils\", \"RColorBrewer\", \"stats\", \"lubridate\", \"remotes\", \"rlang\") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,\"Package\"])] if(length(new.packages)) install.packages(new.packages) # If you have any issues loading the remotes library, uncomment the line below to install the \"remotes\" package specifying the repo # install.packages(\"remotes\", repos = \"http://cran.us.r-project.org\") library(remotes) # remotes::install_github(\"USGS-R/dataRetrieval\", dependencies=TRUE) remotes::install_github(\"USEPA/TADA\", dependencies=TRUE) library(plyr) library(data.table) library(dplyr) library(ggplot2) library(grDevices) library(magrittr) library(stringr) library(utils) library(RColorBrewer) library(stats) library(lubridate) library(rlang) library(dataRetrieval) library(TADA)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"retrieve-wqp-data","dir":"Articles","previous_headings":"","what":"Retrieve WQP data","title":"WQP Data Harmonization","text":"WQP data retrieved processed compatibility TADA. function, TADAdataRetrieval builds USGS dataRetrieval package functions. joins three WQP profiles (.e., station, narrow, phys/chem), changes data Characteristic, Speciation, Fraction, Unit fields uppercase, removes true duplicates, removes data non-water media types, cleans results special characters. function uses inputs dataRetrieval readWQPdata function. readWQPdata restrict characteristics pulled Water Quality Portal (WQP). may specify desired characteristics using, instance: characteristicName = “pH”. Data retrieval filters include: statecode endDate startDate countycode siteid siteType characteristicName ActivityMediaName Please aware TADAdataRetrieval function automatically runs TADA autoclean MeasureValueSpecialCharacters functions well, required subsequent functions within TADA R package run. functions alter /add following WQP columns (enter ?MeasureValueSpecialCharacters ?autoclean console details): Alters (e.g., ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric) ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue Adds (data cleaning transformations done directly “ResultMeasureValue” “DetectionLimitMeasureValue” columns, however original “ResultMeasureValue” “DetectionLimitMeasureValue” columns values WQP preserved new fields, “ResultMeasureValue.Original” “DetectionLimitMeasureValue.Original”. Additionally, “TADA.ResultMeasureValue.Flag” “TADA.DetectionLimitMeasureValue.Flag” created track changes made “ResultMeasureValue” “DetectionLimitMeasureValue” columns; provide information result values needed address censored data later (.e., nondetections). Specifically, new columns flag special characters included result values, specifies special characters . ResultMeasureValue.Original TADA.ResultMeasureValue.Flag DetectionLimitMeasureValue.Original TADA.DetectionLimitMeasureValue.Flag Downloads using TADAdataRetrieval columns time, aware data uploaded Water Quality Portal individual organizations, may may follow conventions. Data metadata quality guaranteed! Make sure carefully explore data make conservative quality assurance decisions information limited. Tips: query filters WQP work within fields ORs. example: Characteristics: choose pH & - ’s . means retrieve pH data available. States: Similarly, choose VA IL, ’s . means retrieve VA IL data available. Combinations fields ANDs, State/VA Characteristic/”. means receive data available VA. “Characteristic” “Characteristic Type” also work . means Characteristic must fall within CharacteristicGroup filters used, get error. “siteid” general term WQP uses describe Site IDs USGS databases Monitoring Location Identifiers (Water Quality Portal). monitoring location Water Quality Portal (WQP) unique Monitoring Location Identifier, regardless database derives. Monitoring Location Identifier WQP concatenated Organization Identifier plus Site ID number. Site IDs include number unique identifiers monitoring locations within USGS NWIS EPA’s WQX databases separately. Additional resources: Review function documentation entering following code console: ?TADAdataRetrieval Introduction dataRetrieval package General Data Import Water Quality Portal Water Quality Portal Web Services Guide dataRetrieval Tutorial Option 1: Use TADAdataRetrieval function. Option 2: Alternatively, can use data.table::fread function read web service call WQP profile (un-comment). Option 3: need download large amount data across large area, TADAdataRetrieval function working due WQP timeout issues, TADABigdataRetrieval function may work better. function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested. See ?TADABigdataRetrieval details. WARNING, can take multiple hours run. total run time depends query inputs. Review column names TADA Profile","code":"#You can edit this to define your own WQP query inputs below TADAProfile <- TADAdataRetrieval(statecode = \"UT\", characteristicName = c(\"Ammonia\", \"Nitrate\", \"Nitrogen\"), startDate = \"01-01-2021\") # New_Draft_fullphyschem <- data.table::fread(\"https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET\") #AllWaterTempData <- TADABigdataRetrieval(startDate = \"2019-01-01\", endDate = \"2021-12-31\", characteristicName = \"Temperature, water\", siteType = \"Stream\") colnames(TADAProfile) #> [1] \"OrganizationIdentifier\" #> [2] \"OrganizationFormalName\" #> [3] \"ActivityIdentifier\" #> [4] \"ActivityTypeCode\" #> [5] \"ActivityMediaName\" #> [6] \"ActivityMediaSubdivisionName\" #> [7] \"ActivityStartDate\" #> [8] \"ActivityStartTime.Time\" #> [9] \"ActivityStartTime.TimeZoneCode\" #> [10] \"ActivityEndDate\" #> [11] \"ActivityEndTime.Time\" #> [12] \"ActivityEndTime.TimeZoneCode\" #> [13] \"ActivityDepthHeightMeasure.MeasureValue\" #> [14] \"ActivityDepthHeightMeasure.MeasureUnitCode\" #> [15] \"ActivityDepthAltitudeReferencePointText\" #> [16] \"ActivityTopDepthHeightMeasure.MeasureValue\" #> [17] \"ActivityTopDepthHeightMeasure.MeasureUnitCode\" #> [18] \"ActivityBottomDepthHeightMeasure.MeasureValue\" #> [19] \"ActivityBottomDepthHeightMeasure.MeasureUnitCode\" #> [20] \"ProjectIdentifier\" #> [21] \"ActivityConductingOrganizationText\" #> [22] \"MonitoringLocationIdentifier\" #> [23] \"ActivityCommentText\" #> [24] \"SampleAquifer\" #> [25] \"HydrologicCondition\" #> [26] \"HydrologicEvent\" #> [27] \"SampleCollectionMethod.MethodIdentifier\" #> [28] \"SampleCollectionMethod.MethodIdentifierContext\" #> [29] \"SampleCollectionMethod.MethodName\" #> [30] \"SampleCollectionEquipmentName\" #> [31] \"ResultDetectionConditionText\" #> [32] \"CharacteristicName\" #> [33] \"ResultSampleFractionText\" #> [34] \"ResultMeasureValue\" #> [35] \"ResultMeasureValue.Original\" #> [36] \"TADA.ResultMeasureValue.Flag\" #> [37] \"ResultMeasure.MeasureUnitCode\" #> [38] \"MeasureQualifierCode\" #> [39] \"ResultStatusIdentifier\" #> [40] \"StatisticalBaseCode\" #> [41] \"ResultValueTypeName\" #> [42] \"ResultWeightBasisText\" #> [43] \"ResultTimeBasisText\" #> [44] \"ResultTemperatureBasisText\" #> [45] \"ResultParticleSizeBasisText\" #> [46] \"PrecisionValue\" #> [47] \"ResultCommentText\" #> [48] \"USGSPCode\" #> [49] \"ResultDepthHeightMeasure.MeasureValue\" #> [50] \"ResultDepthHeightMeasure.MeasureUnitCode\" #> [51] \"ResultDepthAltitudeReferencePointText\" #> [52] \"SubjectTaxonomicName\" #> [53] \"SampleTissueAnatomyName\" #> [54] \"ResultAnalyticalMethod.MethodIdentifier\" #> [55] \"ResultAnalyticalMethod.MethodIdentifierContext\" #> [56] \"ResultAnalyticalMethod.MethodName\" #> [57] \"MethodDescriptionText\" #> [58] \"LaboratoryName\" #> [59] \"AnalysisStartDate\" #> [60] \"ResultLaboratoryCommentText\" #> [61] \"DetectionQuantitationLimitTypeName\" #> [62] \"DetectionQuantitationLimitMeasure.MeasureValue\" #> [63] \"DetectionLimitMeasureValue.Original\" #> [64] \"TADA.DetectionLimitMeasureValue.Flag\" #> [65] \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" #> [66] \"PreparationStartDate\" #> [67] \"ProviderName\" #> [68] \"timeZoneStart\" #> [69] \"timeZoneEnd\" #> [70] \"ActivityStartDateTime\" #> [71] \"ActivityEndDateTime\" #> [72] \"MonitoringLocationName\" #> [73] \"MonitoringLocationTypeName\" #> [74] \"MonitoringLocationDescriptionText\" #> [75] \"HUCEightDigitCode\" #> [76] \"DrainageAreaMeasure.MeasureValue\" #> [77] \"DrainageAreaMeasure.MeasureUnitCode\" #> [78] \"ContributingDrainageAreaMeasure.MeasureValue\" #> [79] \"ContributingDrainageAreaMeasure.MeasureUnitCode\" #> [80] \"LatitudeMeasure\" #> [81] \"LongitudeMeasure\" #> [82] \"SourceMapScaleNumeric\" #> [83] \"HorizontalAccuracyMeasure.MeasureValue\" #> [84] \"HorizontalAccuracyMeasure.MeasureUnitCode\" #> [85] \"HorizontalCollectionMethodName\" #> [86] \"HorizontalCoordinateReferenceSystemDatumName\" #> [87] \"VerticalMeasure.MeasureValue\" #> [88] \"VerticalMeasure.MeasureUnitCode\" #> [89] \"VerticalAccuracyMeasure.MeasureValue\" #> [90] \"VerticalAccuracyMeasure.MeasureUnitCode\" #> [91] \"VerticalCollectionMethodName\" #> [92] \"VerticalCoordinateReferenceSystemDatumName\" #> [93] \"CountryCode\" #> [94] \"StateCode\" #> [95] \"CountyCode\" #> [96] \"AquiferName\" #> [97] \"LocalAqfrName\" #> [98] \"FormationTypeText\" #> [99] \"AquiferTypeName\" #> [100] \"ConstructionDateText\" #> [101] \"WellDepthMeasure.MeasureValue\" #> [102] \"WellDepthMeasure.MeasureUnitCode\" #> [103] \"WellHoleDepthMeasure.MeasureValue\" #> [104] \"WellHoleDepthMeasure.MeasureUnitCode\" #> [105] \"MethodSpecificationName\" #> [106] \"ProjectName\" #> [107] \"ProjectDescriptionText\" #> [108] \"SamplingDesignTypeCode\" #> [109] \"QAPPApprovedIndicator\" #> [110] \"QAPPApprovalAgencyName\" #> [111] \"ProjectFileUrl\" #> [112] \"ProjectMonitoringLocationWeightingUrl\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"depth-unit-conversions","dir":"Articles","previous_headings":"","what":"Depth unit conversions","title":"WQP Data Harmonization","text":"Converts depth units consistent unit. ActivityDepthHeightMeasure.MeasureValue provides depth information. crucial column lake data less often river data. Function checks dataset depth profile data. depth profile columns populated, function appends ‘Conversion Factor’ columns populates columns based original unit (MeasureUnitCode columns) target unit, defined ‘unit’ argument. ‘Depth Target Unit’ column also appended, indicating unit selected depth data converted . transform = FALSE, output includes ‘Conversion Factor’ columns ‘Depth Target Unit’ column. transform = TRUE, output includes converted depth data ‘Depth Target Unit’ column, acts flag indicating rows converted. Default transform = TRUE. depth profile function can harmonize depth units across following fields (specific one): “ActivityDepthHeightMeasure”, “ActivityTopDepthHeightMeasure”, “ActivityBottomDepthHeightMeasure”, “ResultDepthHeightMeasure”). default . Allowable values ‘unit’ either ‘m’ (meter), ‘ft’ (feet), ‘’ (inch). ‘unit’ accepts one allowable value input. Default unit = “m”. See additional function documentation additional function options entering following code console: ?DepthProfileData","code":"#converts all depth profile data to meters TADAProfileClean1 <- DepthProfileData(TADAProfile, unit = \"m\", transform = TRUE) #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"result-unit-conversions","dir":"Articles","previous_headings":"","what":"Result unit conversions","title":"WQP Data Harmonization","text":"Converts results WQX target units. WQX target units pulled MeasureUnit domain table: https://cdx.epa.gov/wqx/download/DomainValues/MeasureUnit.CSV See additional function documentation additional function options entering following code console: ?WQXTargetUnits","code":"#Converts all results to WQX target units TADAProfileClean2 <- WQXTargetUnits(TADAProfileClean1, transform = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"statistically-aggregated-data","dir":"Articles","previous_headings":"","what":"Statistically aggregated data","title":"WQP Data Harmonization","text":"Checks removes statistically aggregated high frequency (.e., continuous) data, present. Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = “Reported Raw Data (attached)” clean = TRUE, rows aggregated continuous data removed dataset column appended Default clean = TRUE See function documentation additional function options entering following code console: ?DepthProfileData","code":"TADAProfileClean3 <- AggregatedContinuousData(TADAProfileClean2, clean = TRUE) #> [1] \"The dataset does not contain aggregated continuous data.\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-qaqc-service-result-flags","dir":"Articles","previous_headings":"","what":"WQX QAQC Service Result Flags","title":"WQP Data Harmonization","text":"Run following result functions address invalid method, fraction, speciation, unit metadata characteristic. default clean = TRUE, remove invalid results. can change clean = FALSE flag results, remove . See documentation details: ?InvalidMethod Clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidSpeciation clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidResultUnit clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidFraction clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended.","code":"TADAProfileClean4 <- InvalidMethod(TADAProfileClean3, clean = TRUE) #> [1] \"No changes were made, because we did not find any invalid method/characteristic combinations in your dataset.\" TADAProfileClean5 <- InvalidFraction(TADAProfileClean4, clean = TRUE) #> [1] \"All data is valid, therefore the function cannot be applied.\" TADAProfileClean6 <- InvalidSpeciation(TADAProfileClean5, clean = FALSE) TADAProfileClean7 <- InvalidResultUnit(TADAProfileClean6, clean = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-national-upper-and-lower-thresholds","dir":"Articles","previous_headings":"","what":"WQX national upper and lower thresholds","title":"WQP Data Harmonization","text":"Run following code flag remove results national upper lower bound characteristic unit combination. See documentation details: ?AboveNationalWQXUpperThreshold clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset. ?BelowNationalWQXUpperThreshold clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset. default clean=TRUE, can change flag results desired. Results flagged, removed, clean=FALSE.","code":"TADAProfileClean8 <- AboveNationalWQXUpperThreshold(TADAProfileClean7, clean = TRUE) TADAProfileClean9 <- BelowNationalWQXUpperThreshold(TADAProfileClean8, clean = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"potential-duplicates","dir":"Articles","previous_headings":"","what":"Potential duplicates","title":"WQP Data Harmonization","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. information, review documentation entering following console: ?PotentialDuplicateRowID clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":"TADAProfileClean10 <- PotentialDuplicateRowID(TADAProfileClean9)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"invalid-coordinates","dir":"Articles","previous_headings":"","what":"Invalid coordinates","title":"WQP Data Harmonization","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled “TADA.InvalidCoordinates” following flags (relevant dataset). latitude less zero, row flagged “LAT_OutsideUSA”. longitude greater zero less 145, row flagged “LONG_OutsideUSA”. latitude longitude contains string, “999”, row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged “Imprecise”.","code":"TADAProfileClean11 <- InvalidCoordinates(TADAProfileClean10, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"review-qapp-information","dir":"Articles","previous_headings":"","what":"Review QAPP information","title":"WQP Data Harmonization","text":"Check data approved QAPP function checks see information column “QAPPApprovedIndicator”. organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . field, Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. defaults remove rows data QAPPApprovedIndicator equals “N”. Users alternatively remove N’s NA’s using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function anything. Check see QAPP Doc Available function checks data submitted “ProjectFileUrl” column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":"TADAProfileClean12 <- QAPPapproved(TADAProfileClean11, clean = TRUE, cleanNA = FALSE) TADAProfileClean13 <- QAPPDocAvailable(TADAProfileClean12, clean = FALSE) #> Warning in QAPPDocAvailable(TADAProfileClean12, clean = FALSE): The dataset does #> not contain QAPP document url data."},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field","dir":"Articles","previous_headings":"","what":"Filter data by field","title":"WQP Data Harmonization","text":"section TADA user want review unique values specific fields may choose remove data particular values. start, review list fields number unique values field. Next, choose field list see unique values field, well number times value appears dataset. ’ll start ActivityTypeCode. list fields review: ResultCommentText often details relating additional QA. MeasureQualifierCode Contains information data flags 3. codes may designate suspect data flags may described detail ResultLaboratoryCommentText another column ActivityTypeCode field four unique values – “Sample-Routine”, “Quality Control Sample-Field Replicate”, “Field Msr/Obs”, “Quality Control Sample-Field Blank.” example want remove quality control values ActivityTypeCode field, therefore, ’ll specify want remove “Quality Control Sample-Field Replicate” “Quality Control Sample-Field Blank” values ActivityTypeCode field. ’ve completed review ActivityTypeCode field. Let’s move different field see values want remove – ’ll look values ResultStatusIdentifier field. ActivityMediaSubdivisionName field two unique values, “Surface Water” “Groundwater.” example want remove “Groundwater” values.","code":"FilterFields(TADAProfileClean13) #> FieldName Count #> 1 OrganizationFormalName 7 #> 2 ActivityTypeCode 7 #> 3 ActivityMediaName 1 #> 4 ActivityMediaSubdivisionName 4 #> 5 ActivityCommentText 4 #> 6 HydrologicCondition 8 #> 7 HydrologicEvent 4 #> 8 CharacteristicName 3 #> 9 MeasureQualifierCode 4 #> 10 SampleTissueAnatomyName 1 #> 11 LaboratoryName 11 #> 12 DetectionQuantitationLimitTypeName 7 #> 13 MonitoringLocationTypeName 14 #> 14 ProjectName 8 FilterFieldReview(\"ActivityTypeCode\", TADAProfileClean13) #> FieldValue Count #> 7 Sample-Routine 5268 #> 6 Sample-Integrated Vertical Profile 474 #> 4 Quality Control Sample-Field Replicate 454 #> 2 Quality Control Sample-Equipment Blank 276 #> 3 Quality Control Sample-Field Blank 60 #> 1 Field Msr/Obs 4 #> 5 Quality Control Sample-Lab Duplicate 2 TADAProfileClean14 <- dplyr::filter(TADAProfileClean13, !(ActivityTypeCode %in% c(\"Quality Control Sample-Field Replicate\", \"Quality Control Sample-Field Blank\", \"Quality Control Sample-Lab Duplicate\", \"Quality Control Sample-Equipment Blank\"))) FilterFieldReview(\"ActivityMediaSubdivisionName\", TADAProfileClean14) #> FieldValue Count #> 3 Surface Water 687 #> 2 Groundwater 106 #> 1 Bulk deposition 1 TADAProfileClean15 <- dplyr::filter(TADAProfileClean14, !(ActivityMediaSubdivisionName %in% c(\"Groundwater\", \"Bulk deposition\")))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field-subset-by-parameter","dir":"Articles","previous_headings":"","what":"Filter data by field, subset by parameter","title":"WQP Data Harmonization","text":"section TADA user want select parameter, review unique values associated parameter specific fields, choose remove particular values. start, review list parameters dataset. (list sorted highest lowest counts. first rows displayed save space page) Next, select parameter. Let’s explore fields associated Nitrogen: Selecting parameter generates list , subset selected parameter, fields number unique values field. choose field list. example ’ll remove certain values HydrologicEvent field. HydrologicEvent field three unique values. example want remove samples collected “Storm” events. Therefore, ’ll specify want remove rows CharacteristicName “NITROGEN” HydrologicEvent field “Storm.”","code":"FilterParList(TADAProfileClean15) #> FieldValue Count #> 3 NITROGEN 4130 #> 2 NITRATE 1479 #> 1 AMMONIA 30 FilterParFields(TADAProfileClean15, \"NITROGEN\") #> FieldName Count #> 1 ActivityTypeCode 2 #> 2 ActivityMediaName 1 #> 3 ActivityMediaSubdivisionName 2 #> 4 ActivityCommentText 3 #> 5 HydrologicCondition 7 #> 6 HydrologicEvent 2 #> 7 SampleCollectionMethod.MethodIdentifier 6 #> 8 SampleCollectionMethod.MethodIdentifierContext 2 #> 9 SampleCollectionMethod.MethodName 6 #> 10 SampleCollectionEquipmentName 6 #> 11 ResultSampleFractionText 3 #> 12 ResultMeasure.MeasureUnitCode 2 #> 13 MeasureQualifierCode 3 #> 14 ResultStatusIdentifier 2 #> 15 ResultValueTypeName 1 #> 16 ResultWeightBasisText 1 #> 17 ResultTemperatureBasisText 1 #> 18 ResultParticleSizeBasisText 1 #> 19 ResultCommentText 7 #> 20 ResultAnalyticalMethod.MethodIdentifier 2 #> 21 ResultAnalyticalMethod.MethodIdentifierContext 2 #> 22 ResultAnalyticalMethod.MethodName 2 #> 23 MethodDescriptionText 1 #> 24 LaboratoryName 2 #> 25 ResultLaboratoryCommentText 5 #> 26 DetectionQuantitationLimitTypeName 2 #> 27 MonitoringLocationTypeName 11 FilterParFieldReview(\"HydrologicEvent\", TADAProfileClean15, \"NITROGEN\") #> FieldValue Count #> 1 Routine sample 59 TADAProfileClean16 <- dplyr::filter(TADAProfileClean15, !(CharacteristicName %in% \"NITROGEN\" & HydrologicEvent %in% \"Storm\"))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"transform-characteristic-speciation-and-unit-values-to-tada-standards","dir":"Articles","previous_headings":"","what":"Transform Characteristic, Speciation, and Unit values to TADA Standards","title":"WQP Data Harmonization","text":"HarmonizeRefTable function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values following elements: CharacteristicName ResultSampleFractionText MethodSpecicationName ResultMeasure.MeasureUnitCode HarmonizeData function compares input dataset TADA Harmonization Reference Table. purpose function make similar data consistent therefore easier compare analyze. Users can also edit reference file meet needs desired. download argument can used save harmonization file current working directory download = TRUE, default download = FALSE. Optional outputs include: dataset Harmonization columns appended, dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE. examples HarmonizeData function can used: ResultSampleFractionText specifies forms constituents. cases, single CharacteristicName “Total” “Dissolved” forms specified, combined. cases, CharacteristicName ResultSampleFractionText combination given different identifier. identifier can used later identify comparable data groups calculating statistics creating figures combination. variables different names represent constituent (e.g., “Total Kjeldahl nitrogen (Organic N & NH3)” “Kjeldahl nitrogen”). HarmonizeData function gives consistent name (identifier) synonyms.","code":"UniqueHarmonizationRef <- HarmonizationRefTable(TADAProfileClean16, download = FALSE) TADAProfileClean17 <- HarmonizeData(TADAProfileClean16, ref = UniqueHarmonizationRef, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Cristina Mullin. Author, maintainer. Michelle Thawley. Author. Laura Shumway. Author. Jacob Greif. Author.","code":""},{"path":"usepa.github.io/tada/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Mullin, C.., Greif, J., Thawley, M., Shumway, L., 2022, TADA: R Tools Automated Data Assessment, U.S. Environmental Protection Agency, Washington, DC","code":"@Manual{, author = {Cristina A. Mullin and Jacob Greif and Michelle Thawley and Laura Shumway}, title = {TADA: R Tools for Automated Data Assessment}, address = {Washington, DC}, institution = {U.S. Environmental Protection Agency}, year = {2022}, url = {https://github.com/USEPA/TADA}, }"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"package-development","dir":"","previous_headings":"","what":"Package Development","title":"NA","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"what-is-github","dir":"","previous_headings":"","what":"What is GitHub?","title":"NA","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"required-installations","dir":"","previous_headings":"","what":"Required Installations","title":"NA","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"NA","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"branches","dir":"","previous_headings":"","what":"Branches","title":"NA","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"additional-references","dir":"","previous_headings":"","what":"Additional References","title":"NA","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/index.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"Tools for Automated Data Assessment R Package","text":"encourage read package’s CONTRIBUTING, LICENSE, README files (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/index.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"Tools for Automated Data Assessment R Package","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Tools for Automated Data Assessment R Package","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/index.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"Tools for Automated Data Assessment R Package","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Tools for Automated Data Assessment R Package","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/index.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"Tools for Automated Data Assessment R Package","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Tools for Automated Data Assessment R Package","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":[]},{"path":"usepa.github.io/tada/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"CC0 1.0 Universal","title":"CC0 1.0 Universal","text":"CREATIVE COMMONS CORPORATION LAW FIRM PROVIDE LEGAL SERVICES. DISTRIBUTION DOCUMENT CREATE ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES INFORMATION “-” BASIS. CREATIVE COMMONS MAKES WARRANTIES REGARDING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER, DISCLAIMS LIABILITY DAMAGES RESULTING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER.","code":""},{"path":"usepa.github.io/tada/LICENSE.html","id":"statement-of-purpose","dir":"","previous_headings":"","what":"Statement of Purpose","title":"CC0 1.0 Universal","text":"laws jurisdictions throughout world automatically confer exclusive Copyright Related Rights (defined ) upon creator subsequent owner(s) (, “owner”) original work authorship /database (, “Work”). Certain owners wish permanently relinquish rights Work purpose contributing commons creative, cultural scientific works (“Commons”) public can reliably without fear later claims infringement build upon, modify, incorporate works, reuse redistribute freely possible form whatsoever purposes, including without limitation commercial purposes. owners may contribute Commons promote ideal free culture production creative, cultural scientific works, gain reputation greater distribution Work part use efforts others. /purposes motivations, without expectation additional consideration compensation, person associating CC0 Work (“Affirmer”), extent owner Copyright Related Rights Work, voluntarily elects apply CC0 Work publicly distribute Work terms, knowledge Copyright Related Rights Work meaning intended legal effect CC0 rights. Copyright Related Rights. Work made available CC0 may protected copyright related neighboring rights (“Copyright Related Rights”). 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Affirmer disclaims responsibility clearing rights persons may apply Work use thereof, including without limitation person’s Copyright Related Rights Work. , Affirmer disclaims responsibility obtaining necessary consents, permissions rights required use Work. Affirmer understands acknowledges Creative Commons party document duty obligation respect CC0 use Work.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"NA","text":"encourage read package’s CONTRIBUTING, LICENSE, README files (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"NA","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"NA","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/readme.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data upper threshold result values submitted WQX given characteristic. clean = TRUE, rows values upper WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"","code":"AboveNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data upper WQX threshold dataset clean = TRUE. Default clean = TRUE","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Aggregated Continuous Data — AggregatedContinuousData","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = \"Reported Raw Data (attached)\". clean = TRUE, rows aggregated continuous data removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"","code":"AggregatedContinuousData(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":".data TADA dataframe clean Boolean argument; removes aggregated continuous data dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"clean = FALSE, column flagging rows aggregated continuous data appended input data set. clean = TRUE, aggregated continuous data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — autoclean","title":"autoclean — autoclean","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — autoclean","text":"","code":"autoclean(.data)"},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — autoclean","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — autoclean","text":"autocleaned TADA data profile","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — autoclean","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":null,"dir":"Reference","previous_headings":"","what":"AutoFilter — AutoFilter","title":"AutoFilter — AutoFilter","text":"Function can used autofilter simplify WQP dataset. applying function, dataset contain result values water media types chemicals tissue (e.g. mercury fish tissue). complex biological data (counts macroinvertebrates) removed. function looks following fields autofilter: ActivityMediaName, ActivityMediaSubDivisionName, AssemblageSampledName","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AutoFilter — AutoFilter","text":"","code":"AutoFilter(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AutoFilter — AutoFilter","text":".data TADA dataframe clean Indicates whether flag columns appended data (clean = FALSE), flagged data transformed/filtered dataset columns appended (clean = TRUE).","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"AutoFilter — AutoFilter","text":"clean = FALSE, flag column appended dataset. clean = TRUE, flag column appended relevant rows removed.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data lower threshold result values submitted WQX given characteristic. clean = TRUE, rows values lower WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"","code":"BelowNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data lower WQX threshold dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalnumcount — decimalnumcount","title":"decimalnumcount — decimalnumcount","text":"character data type","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalnumcount — decimalnumcount","text":"","code":"decimalnumcount(x)"},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalnumcount — decimalnumcount","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalnumcount — decimalnumcount","text":"Number values right decimal point character type data.","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalplaces — decimalplaces","title":"decimalplaces — decimalplaces","text":"numeric data type","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalplaces — decimalplaces","text":"","code":"decimalplaces(x)"},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalplaces — decimalplaces","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalplaces — decimalplaces","text":"Number values right decimal point numeric type data.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":null,"dir":"Reference","previous_headings":"","what":"Depth Profile Flag & Unit Conversion — DepthProfileData","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Function checks dataset depth profile data. depth profile columns populated, function appends 'Conversion.Factor' columns populates columns based original unit (MeasureUnitCode columns) target unit, defined 'unit' argument. 'WQX.Depth.TargetUnit' column also appended, indicating unit selected depth data converted . transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"","code":"DepthProfileData( .data, unit = \"m\", fields = c(\"ActivityDepthHeightMeasure\", \"ActivityTopDepthHeightMeasure\", \"ActivityBottomDepthHeightMeasure\", \"ResultDepthHeightMeasure\"), transform = TRUE )"},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":".data TADA dataframe unit Character string input indicating uniform unit depth data converted . Allowable values 'unit' either 'm' (meter), 'ft' (feet), '' (inch). 'unit' accepts one allowable value input. Default unit = \"m\". fields Character string input indicating depth fields checked data. Allowable values 'fields' 'ActivityDepthHeightMeasure,' 'ActivityTopDepthHeightMeasure,' 'ActivityBottomDepthHeightMeasure,' 'ResultDepthHeightMeasure.'. Default include allowable values. transform Boolean argument; transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'Depth Target Unit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Full dataset converted uniform depth units 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. transform = FALSE, output full dataset 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field — FilterFieldReview","title":"Generate list of unique values in a given field — FilterFieldReview","text":"Function creates table pie chart unique values, counts values chosen field dataframe.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field — FilterFieldReview","text":"","code":"FilterFieldReview(field, .data)"},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field — FilterFieldReview","text":"field Field name .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field — FilterFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names — FilterFields","title":"Generate list of field names — FilterFields","text":"Function creates list fields input dataframe well number unique values field. list intended inform users specific fields explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names — FilterFields","text":"","code":"FilterFields(.data)"},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names — FilterFields","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names — FilterFields","text":"table fields count unique values field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"Function creates table pie chart unique values, counts values, chosen field dataframe subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"","code":"FilterParFieldReview(field, .data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"field Field name .data Optional argument; TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names subset by parameter — FilterParFields","title":"Generate list of field names subset by parameter — FilterParFields","text":"Function subsets input dataframe input parameter creates list fields subset dataframe well number unique values field. list intended inform users specific fields explore filter subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names subset by parameter — FilterParFields","text":"","code":"FilterParFields(.data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names subset by parameter — FilterParFields","text":".data TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names subset by parameter — FilterParFields","text":"table fields count unique values field, subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of parameters — FilterParList","title":"Generate list of parameters — FilterParList","text":"Function generates list characteristics input dataset, well number records . list intended inform users parameters explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of parameters — FilterParList","text":"","code":"FilterParList(.data)"},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of parameters — FilterParList","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of parameters — FilterParList","text":"list unique characteristics counts","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":null,"dir":"Reference","previous_headings":"","what":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Function summarizes censored data dataset, including substitutions made.","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"","code":"GenerateCensoredDataStats(.data)"},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":".data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Summary table","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table — GetMeasureUnitRef","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"Function downloads returns latest WQX MeasureUnit Domain table, adds additional target unit information, writes data sysdata.rda.","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"","code":"GetMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"sysdata.rda updated WQXunitRef object (unit conversion reference table)","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Function downloads returns newest available (cleaned) raw Water Quality Exchange (WQX) QAQC Characteristic Validation reference table. WQXcharValRef data frame contains information four functions: InvalidFraction, InvalidResultUnit, InvalidSpeciation, UncommonAnalyticalMethodID.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"","code":"GetWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Updated sysdata.rda updated WQXcharValRef object","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode can optionally edit reference file meet needs.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"","code":"HarmonizationRefTable(.data, download = FALSE)"},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":".data TADA dataframe download Boolean argument; download = TRUE, output downloaded current working directory.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Harmonization Reference Table unique input dataset","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"Function compares input dataset TADA Harmonization Reference Table, makes synonymous data consistent. Optional outputs include: 1) dataset Harmonization columns appended, 2) dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards 3) four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"","code":"HarmonizeData(.data, ref, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":".data TADA dataframe ref Optional argument specify dataframe use reference file. primary use argument user generated harmonization reference file unique data, made changes file. transform Boolean argument; transforms /converts original values dataset TADA Harmonization Reference Table values following fields: CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode. Default transform = TRUE. flag Boolean argument; appends columns TADA Harmonization Reference Table dataframe. Default flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"transform = FALSE flag = TRUE, Harmonization Reference Table columns appended dataset . transform = TRUE flag = TRUE, Harmonization columns appended dataset transformations executed. transform = TRUE flag = FALSE, transformations executed . transform = FALSE flag = FALSE, error returned (function return input dataframe unchanged input allowed).","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":null,"dir":"Reference","previous_headings":"","what":"Invalid coordinates — InvalidCoordinates","title":"Invalid coordinates — InvalidCoordinates","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled \"TADA.InvalidCoordinates\" following flags (relevant dataset). latitude less zero, row flagged \"LAT_OutsideUSA\". longitude greater zero less 145, row flagged \"LONG_OutsideUSA\". latitude longitude contains string, \"999\", row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged \"Imprecise\".","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Invalid coordinates — InvalidCoordinates","text":"","code":"InvalidCoordinates(.data, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Invalid coordinates — InvalidCoordinates","text":".data TADA dataframe clean_outsideUSA Boolean argument; removes data coordinates outside United States clean_outsideUSA = TRUE. Default clean = FALSE. clean_imprecise Boolean arguments; removes imprecise data clean_imprecise = TRUE. Default clean_imprecise = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Invalid coordinates — InvalidCoordinates","text":"either clean_outsideUSA clean_imprecise argument FALSE, column flagging rows respective QA check appended input dataset. either argument TRUE, \"invalid\" \"imprecise\" data removed, respectively.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Sample Fraction Validity — InvalidFraction","title":"Check Sample Fraction Validity — InvalidFraction","text":"Function checks validity characteristic-fraction combination dataset. clean = TRUE, rows invalid characteristic-fraction combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Sample Fraction Validity — InvalidFraction","text":"","code":"InvalidFraction(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Sample Fraction Validity — InvalidFraction","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-fraction combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Sample Fraction Validity — InvalidFraction","text":"clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Invalid Analytical Methods — InvalidMethod","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"Function checks validity characteristic-analytical method combination dataset. clean = TRUE, rows invalid characteristic-analytical method combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"","code":"InvalidMethod(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Invalid Analytical Methods — InvalidMethod","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-analytical method combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Unit Validity — InvalidResultUnit","title":"Check Result Unit Validity — InvalidResultUnit","text":"Function checks validity characteristic-media-result unit combination dataset. clean = TRUE, rows invalid characteristic-media-result unit combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Unit Validity — InvalidResultUnit","text":"","code":"InvalidResultUnit(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Unit Validity — InvalidResultUnit","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-media-result unit combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Unit Validity — InvalidResultUnit","text":"clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Method Speciation Validity — InvalidSpeciation","title":"Check Method Speciation Validity — InvalidSpeciation","text":"Function checks validity characteristic-method speciation combination dataset. clean = TRUE, rows invalid characteristic-method speciation combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Method Speciation Validity — InvalidSpeciation","text":"","code":"InvalidSpeciation(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Method Speciation Validity — InvalidSpeciation","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-method speciation combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Method Speciation Validity — InvalidSpeciation","text":"#'clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Function checks special characters non-numeric values ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields appends flag columns indicating special characters included , special characters . ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields also converted class numeric.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"","code":"MeasureValueSpecialCharacters(.data)"},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Full dataset column indicating presence special characters ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields. Additionally, ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric, copies column created preserve original character values.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"usepa.github.io/tada/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Potential Duplicates — PotentialDuplicateRowID","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"","code":"PotentialDuplicateRowID(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":".data TADA dataframe clean Boolean argument; removes potential duplicate data dataset clean = TRUE. clean = FALSE, column indicating potential duplicate rows unique number linking rows appended input data set. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":null,"dir":"Reference","previous_headings":"","what":"Check data for an approved QAPP — QAPPapproved","title":"Check data for an approved QAPP — QAPPapproved","text":"Function checks data submitted column \"QAPPApprovedIndicator\". organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. default removes rows data QAPPApprovedIndicator equals \"N\". Users alternatively remove N's NA's using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function make changes data.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check data for an approved QAPP — QAPPapproved","text":"","code":"QAPPapproved(.data, clean = TRUE, cleanNA = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check data for an approved QAPP — QAPPapproved","text":".data TADA dataframe clean Boolean argument two possible values called \"TRUE\" \"FALSE\". clean=TRUE, rows data QAPPApprovedIndicator equals \"N\" removed. , clean=FALSE, rows data QAPPApprovedIndicator equals \"N\" retained. cleanNA Boolean argument two possible values called \"TRUE\" \"FALSE\". cleanNA=TRUE, rows data QAPPApprovedIndicator equals \"NA\" removed. , cleanNA=FALSE, rows data QAPPApprovedIndicator equals \"NA\" retained.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check data for an approved QAPP — QAPPapproved","text":"clean = FALSE cleanNA = FALSE, data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check data for an approved QAPP — QAPPapproved","text":"Note: required field, often left blank (NA) even data associated QAPP. states tribes collect monitoring data using 106 funding (almost state tribal data WQX) required EPA approved QAPP receive 106 funding. Therefore, organizations data approved QAPP even data submitted WQP NA.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"Function checks data submitted \"ProjectFileUrl\" column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"","code":"QAPPDocAvailable(.data, clean = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":".data TADA dataframe clean Boolean argument; removes data without associated QAPP document dataset clean = TRUE. Default clean = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"clean = FALSE, column appended input data set flags rows associated QAPP document. clean = TRUE, data without associated QAPP document removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":null,"dir":"Reference","previous_headings":"","what":"Read in WQP data using WQP web services directly — readWQPwebservice","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Go WQP website (https://www.waterqualitydata.us/) fill advanced query form. Choose Full Physical Chemical Data Profile, data sources, file format Comma-Separated. finished, hit download button. Instead, copy web service URL located bottom page header \"Result\". Use \"Result\" web service URL input function download data directly R.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"","code":"readWQPwebservice(webservice)"},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"webservice WQP Web Service URL, entered within quotes \"url\"","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"WQP Full Physical Chemical Results Data Profile","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Note: may useful save Query URL well comment within code. URL return WQP query page original data filters.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"RemoveEmptyColumns — RemoveEmptyColumns","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Removes columns NA values. Used quickly reduce number columns dataframe improve management readability dataset.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"","code":"RemoveEmptyColumns(.data)"},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":".data Dataframe","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Full dataset empty data columns removed","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"TADABigdataRetrieval( startDate = \"null\", endDate = \"null\", characteristicName = \"null\", siteType = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"startDate Start Date YYYY-MM-DD format, example, \"1995-01-01\" endDate end date YYYY-MM-DD format, example, \"2020-12-31\" characteristicName Name water quality parameter siteType Name water body type (e.g., \"Stream\", \"Lake, Reservoir, Impoundment\")","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"Similarly TADAdataRetrieval function, function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"if (FALSE) { tada2 <- TADABigdataRetrieval(startDate = \"01-01-2021\", endDate = \"01-01-2022\", characteristicName = \"Nitrogen\", siteType = \"Stream\") }"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Retrieve data Water Quality Portal (WQP) output TADA-compatible dataset.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"TADAdataRetrieval( statecode = \"null\", startDate = \"null\", countycode = \"null\", siteid = \"null\", siteType = \"null\", characteristicName = \"null\", ActivityMediaName = \"null\", endDate = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"statecode Code identifies state startDate Start Date countycode Code identifies county siteid Unique monitoring station identifier siteType Type waterbody characteristicName Name parameter ActivityMediaName Sampling substrate water, air, sediment endDate End Date","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Keep mind query filters WQP work within fields ORs. example, characteristics – choose pH & – ’s . Similarly, choose VA IL, ’s . combo fields ANDs. State/VA Characteristic/\". \"Characteristic\" \"Characteristic Group\" also work . function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"if (FALSE) { tada1 <- TADAdataRetrieval(statecode = \"WI\", countycode = \"Dane\", characteristicName = \"Phosphorus\") }"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — TADAprofileCheck","title":"autoclean — TADAprofileCheck","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — TADAprofileCheck","text":"","code":"TADAprofileCheck(.data)"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — TADAprofileCheck","text":".data dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — TADAprofileCheck","text":"cleaned TADA data profile TADA Profile Check function checks column names dataframe include TADA profile fields. used beginning TADA functions ensure input data frame suitable (.e. either full physical/chemical results profile downloaded WQP TADA profile template downloaded EPA TADA webpage.) Boolean result indicating whether input dataframe contains TADA profile fields.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — TADAprofileCheck","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":null,"dir":"Reference","previous_headings":"","what":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"Function substitutes monitoring device/method detection limits (available) result values applicable.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"","code":"TransformCensoredData(transform, .data)"},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE. .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform=TRUE, monitoring device/method detection limits (available) substituted result values units. transform = FALSE, monitoring device/method detection limits (available) substituted result values units - Instead, columns appended rows may include censored data. flag indicates 1) row contains censored data, 2) monitoring device/method detection limits available.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Existing Data in sysdata.rda — UpdateInternalData","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Function internal use . used internal functions used update internal data (e.g. reference tables). function adapted stackoverflow.com thread, can accessed .","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"","code":"UpdateInternalData(..., list = character())"},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"... Objects updated sysdata.rda. list Argument indicating data class list.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Updated sysdata.rda file","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"Update Measure Unit Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"","code":"UpdateMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"Update Characteristic Validation Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"","code":"UpdateWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"Used store cached WQX QAQC Characteristic Validation Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"","code":"WQXCharValRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"object class NULL length 0.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Units to WQX Target Units — WQXTargetUnits","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function compares measure units input data Water Quality Exchange (WQX) 3.0 QAQC Characteristic Validation table.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"","code":"WQXTargetUnits(.data, transform = TRUE)"},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":".data TADA dataset transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"transform=TRUE, result values units converted WQX target units. function changes values within \"ResultMeasure.MeasureUnitCode\" \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" WQX target units converts respective values within \"ResultMeasureValue\" \"DetectionQuantitationLimitMeasure.MeasureValue\" fields. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=TRUE add following two fields input dataset, \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\", retain original result unit values. transform = FALSE, result values units converted WQX target units, columns appended indicate target units conversion factors , data can converted. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=FALSE add following two fields input dataset: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function ALWAYS add following two columns input dataset: \"WQX.ResultMeasureValue.UnitConversion\", \"WQX.DetectionLimitMeasureValue.UnitConversion\" two fields indicate data can converted.\"NoResultValue\" means data converted ResultMeasureValue, \"NoTargetUnit\" means data converted original unit associated target unit WQX. \"Convert\" means data can transformed, \"Converted\" means function run input transform = TRUE, values already converted. also uses following six fields input dataset: \"CharacteristicName\", \"ActivityMediaName\", \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" function adds following two fields transforms values within following four fields transform=TRUE: Adds: \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\". Transforms: \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\". function adds following two fields transform=FALSE: Adds: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"Used store cached Measure Unit Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"","code":"WQXunitRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"object class NULL length 0.","code":""}] diff --git a/vignettes/WQPDataHarmonization.Rmd b/vignettes/WQPDataHarmonization.Rmd index 3888dcaf..1b1d38e5 100644 --- a/vignettes/WQPDataHarmonization.Rmd +++ b/vignettes/WQPDataHarmonization.Rmd @@ -35,7 +35,7 @@ The following code will also install any packages you do not have, and load all packages required to run this vignette into your R session. ```{r, results = 'hide', message = FALSE, warning = FALSE} -list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes", "rlang", "tidyverse", "knitr", "rmarkdown", "testthat", "usethis", "devtools", "pkgdown", "Rcpp", "spelling") +list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes", "rlang") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])] if(length(new.packages)) install.packages(new.packages) @@ -47,7 +47,6 @@ GitHub ```{r, results = 'hide', message = FALSE, warning = FALSE} # If you have any issues loading the remotes library, uncomment the line below to install the "remotes" package specifying the repo # install.packages("remotes", repos = "http://cran.us.r-project.org") - library(remotes) ``` @@ -74,15 +73,6 @@ library(RColorBrewer) library(stats) library(lubridate) library(rlang) -library(tidyverse) -library(knitr) -library(rmarkdown) -library(testthat) -library(usethis) -library(devtools) -library(pkgdown) -library(Rcpp) -library(spelling) library(dataRetrieval) library(TADA) ``` From b21d7775d0390400bf1dd0377daf0c1c2c261eae Mon Sep 17 00:00:00 2001 From: cristinamullin Date: Wed, 19 Oct 2022 14:55:27 -0400 Subject: [PATCH 07/10] big fix depth conv --- R/ResultFlagsDependent.R | 122 ++++++++++++++++++--------------------- 1 file changed, 55 insertions(+), 67 deletions(-) diff --git a/R/ResultFlagsDependent.R b/R/ResultFlagsDependent.R index 9a76594a..e01db306 100644 --- a/R/ResultFlagsDependent.R +++ b/R/ResultFlagsDependent.R @@ -384,66 +384,49 @@ DepthProfileData <- function(.data, ) %in% colnames(.data)) == TRUE) { + # define check.data (to preserve .data and avoid mistakes with if statements below) + check.data <- .data + + appCols <- c("WQXConversionFactor.ActivityDepthHeightMeasure", + "WQXConversionFactor.ActivityTopDepthHeightMeasure", + "WQXConversionFactor.ActivityBottomDepthHeightMeasure", + "WQXConversionFactor.ResultDepthHeightMeasure") + # read in unit conversion reference table from extdata unit.ref <- GetMeasureUnitRef() + # subset to include only "Length Distance" units; filter by target unit defined in 'unit' argument unit.ref <- unit.ref %>% dplyr::filter(stringr::str_detect( Description, stringr::regex("\\bLength Distance") )) %>% - dplyr::filter(Target.Unit == unit) %>% - dplyr::rename(WQX.Depth.TargetUnit = Target.Unit) + dplyr::filter(Target.Unit == unit) #%>% + #dplyr::rename(WQX.Depth.TargetUnit = Target.Unit) - # define check.data (to preserve .data and avoid mistakes with if statements below) - check.data <- .data - # add WQX.Depth.TargetUnit column - - # append data based on fields argument input - # Columns to append - appCols <- c("WQX.ActDepth.ConversionFactor", - "WQX.ActTopDepth.ConversionFactor", - "WQX.ActBottomDepth.ConversionFactor", - "WQX.ResultDepth.ConversionFactor", - "WQX.Depth.TargetUnit") - for (i in seq_along(validFields)) { + for (i in seq(length(validFields)+1)) { field <- validFields[i] if ((field %in% fields) == TRUE) { # Old unit column unitCol <- paste(field, ".MeasureUnitCode", sep="") - # New column to append - appCol <- appCols[i] + # proceed only if unitCol has values other than NA if (sum(!is.na(check.data[unitCol])) > 0) { - targetUnit <- "WQX.Depth.TargetUnit" - # Join targetUnit and conversion factor from unit.ref to .data by unitCol - check.data <- merge(check.data, unit.ref[, c("Code", targetUnit, "Conversion.Factor")], + + # Join conversion factor from unit.ref to .data by unitCol + check.data <- merge(check.data, unit.ref[, c("Code", "Conversion.Factor")], by.x = unitCol, by.y = "Code", all.x = TRUE ) - # rename new columns - check.data <- check.data %>% - dplyr::rename(!!appCol := Conversion.Factor) + + # rename new columns + names(check.data)[names(check.data) == "Conversion.Factor"] <- paste('WQXConversionFactor.', field, sep="") - # If targetUnit column already exists combine columns - targetUnit.x <- paste(targetUnit, '.x', sep="") - targetUnit.y <- paste(targetUnit, '.y', sep="") - if (all(c(targetUnit.x, targetUnit.y) %in% colnames(check.data)) == TRUE) { - # coalesce WQX.Depth.TargetUnit columns - check.data[targetUnit] <- dplyr::coalesce( - check.data[targetUnit.x], - check.data[targetUnit.y] - ) - # remove extra columns - check.data <- dplyr::select(check.data, - -c(targetUnit.x, targetUnit.y) - ) } } } - } - + # check if any Conversion Factor columns were appended if (all(is.na(match(appCols, colnames(check.data)))) == TRUE) { stop("The dataset does not have any depth data.") @@ -493,28 +476,32 @@ DepthProfileData <- function(.data, } #function should always run all code above - } # if transform = FALSE, output data if (transform == FALSE) { + # add WQX.Depth.TargetUnit column + check.data[ , 'WQX.Depth.TargetUnit'] <- unit return(check.data) } # if transform = TRUE, apply conversion if (transform == TRUE) { # define clean.data - clean.data <- check.data + # add WQX.Depth.TargetUnit column + check.data[ , 'WQX.Depth.TargetUnit'] <- unit + + clean.data <- check.data - # if WQX.ActDepth.ConversionFactor exists... - if (("WQX.ActDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { - # multiply ActivityDepthHeightMeasure.MeasureValue by WQX.ActDepth.ConversionFactor - clean.data$ActivityDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityDepthHeightMeasure.MeasureValue) * (clean.data$WQX.ActDepth.ConversionFactor)) + # if WQXConversionFactor.ActivityDepthHeightMeasure exists... + if (("WQXConversionFactor.ActivityDepthHeightMeasure" %in% colnames(clean.data)) == TRUE) { + # multiply ActivityDepthHeightMeasure.MeasureValue by WQXConversionFactor.ActivityDepthHeightMeasure + clean.data$ActivityDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityDepthHeightMeasure.MeasureValue) * (clean.data$WQXConversionFactor.ActivityDepthHeightMeasure)) # replace ActivityDepthHeightMeasure.MeasureUnitCode values with unit argument clean.data$ActivityDepthHeightMeasure.MeasureUnitCode.Original <- clean.data$ActivityDepthHeightMeasure.MeasureUnitCode clean.data <- clean.data %>% dplyr::relocate("ActivityDepthHeightMeasure.MeasureUnitCode.Original", - .after = "WQX.ActDepth.ConversionFactor" + .after = "WQXConversionFactor.ActivityDepthHeightMeasure" ) clean.data$ActivityDepthHeightMeasure.MeasureUnitCode[which( @@ -525,20 +512,20 @@ DepthProfileData <- function(.data, dplyr::relocate("ActivityDepthHeightMeasure.MeasureUnitCode", .after = "ActivityDepthHeightMeasure.MeasureValue" ) - # uncoment below to delete ActDepth.Conversion.Unit column - #clean.data <- dplyr::select(clean.data, -"WQX.ActDepth.ConversionFactor") + # uncomment below to delete ActDepth.Conversion.Unit column + #clean.data <- dplyr::select(clean.data, -"WQXConversionFactor.ActivityDepthHeightMeasure") } - #WQX.ActTopDepth.ConversionFactor exists... - if (("WQX.ActTopDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { - # multiply ActivityTopDepthHeightMeasure.MeasureValue by WQX.ActTopDepth.ConversionFactor - clean.data$ActivityTopDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityTopDepthHeightMeasure.MeasureValue) * (clean.data$WQX.ActTopDepth.ConversionFactor)) + #WQXConversionFactor.ActivityTopDepthHeightMeasure exists... + if (("WQXConversionFactor.ActivityTopDepthHeightMeasure" %in% colnames(clean.data)) == TRUE) { + # multiply ActivityTopDepthHeightMeasure.MeasureValue by WQXConversionFactor.ActivityTopDepthHeightMeasure + clean.data$ActivityTopDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityTopDepthHeightMeasure.MeasureValue) * (clean.data$WQXConversionFactor.ActivityTopDepthHeightMeasure)) # replace ActivityTopDepthHeightMeasure.MeasureUnitCode values with unit argument clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode.Original <- clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode clean.data <- clean.data %>% dplyr::relocate("ActivityTopDepthHeightMeasure.MeasureUnitCode.Original", - .after = "WQX.ActTopDepth.ConversionFactor" + .after = "WQXConversionFactor.ActivityTopDepthHeightMeasure" ) clean.data$ActivityTopDepthHeightMeasure.MeasureUnitCode[which( @@ -549,20 +536,20 @@ DepthProfileData <- function(.data, dplyr::relocate("ActivityTopDepthHeightMeasure.MeasureUnitCode", .after = "ActivityTopDepthHeightMeasure.MeasureValue" ) - # uncoment below to delete ActTopDepth.Conversion.Unit column - #clean.data <- dplyr::select(clean.data, -"WQX.ActTopDepth.ConversionFactor") + # uncomment below to delete ActTopDepth.Conversion.Unit column + #clean.data <- dplyr::select(clean.data, -"WQXConversionFactor.ActivityTopDepthHeightMeasure") } - #WQX.ActBottomDepth.ConversionFactor exists... - if (("WQX.ActBottomDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { - # multiply ActivityBottomDepthHeightMeasure.MeasureValue by WQX.ActBottomDepth.ConversionFactor - clean.data$ActivityBottomDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityBottomDepthHeightMeasure.MeasureValue) * (clean.data$WQX.ActBottomDepth.ConversionFactor)) + #WQXConversionFactor.ActivityBottomDepthHeightMeasure exists... + if (("WQXConversionFactor.ActivityBottomDepthHeightMeasure" %in% colnames(clean.data)) == TRUE) { + # multiply ActivityBottomDepthHeightMeasure.MeasureValue by WQXConversionFactor.ActivityBottomDepthHeightMeasure + clean.data$ActivityBottomDepthHeightMeasure.MeasureValue <- ((clean.data$ActivityBottomDepthHeightMeasure.MeasureValue) * (clean.data$WQXConversionFactor.ActivityBottomDepthHeightMeasure)) # replace ActivityTopDepthHeightMeasure.MeasureUnitCode values with unit argument clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode.Original <- clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode clean.data <- clean.data %>% dplyr::relocate("ActivityBottomDepthHeightMeasure.MeasureUnitCode.Original", - .after = "WQX.ActBottomDepth.ConversionFactor" + .after = "WQXConversionFactor.ActivityBottomDepthHeightMeasure" ) clean.data$ActivityBottomDepthHeightMeasure.MeasureUnitCode[which( @@ -573,20 +560,20 @@ DepthProfileData <- function(.data, dplyr::relocate("ActivityBottomDepthHeightMeasure.MeasureUnitCode", .after = "ActivityBottomDepthHeightMeasure.MeasureValue" ) - # uncoment below to delete ActBottomDepth.Conversion.Unit column - #clean.data <- dplyr::select(clean.data, -"WQX.ActBottomDepth.ConversionFactor") + # uncomment below to delete ActBottomDepth.Conversion.Unit column + #clean.data <- dplyr::select(clean.data, -"WQXConversionFactor.ActivityBottomDepthHeightMeasure") } - #WQX.ResultDepth.ConversionFactor exists... - if (("WQX.ResultDepth.ConversionFactor" %in% colnames(clean.data)) == TRUE) { - # multiply ResultDepthHeightMeasure.MeasureValue by WQX.ResultDepth.ConversionFactor - clean.data$ResultDepthHeightMeasure.MeasureValue <- ((clean.data$ResultDepthHeightMeasure.MeasureValue) * (clean.data$WQX.ResultDepth.ConversionFactor)) + #WQXConversionFactor.ResultDepthHeightMeasure exists... + if (("WQXConversionFactor.ResultDepthHeightMeasure" %in% colnames(clean.data)) == TRUE) { + # multiply ResultDepthHeightMeasure.MeasureValue by WQXConversionFactor.ResultDepthHeightMeasure + clean.data$ResultDepthHeightMeasure.MeasureValue <- ((clean.data$ResultDepthHeightMeasure.MeasureValue) * (clean.data$WQXConversionFactor.ResultDepthHeightMeasure)) # replace ResultDepthHeightMeasure.MeasureUnitCode values with unit argument clean.data$ResultDepthHeightMeasure.MeasureUnitCode.Original <- clean.data$ResultDepthHeightMeasure.MeasureUnitCode clean.data <- clean.data %>% dplyr::relocate("ResultDepthHeightMeasure.MeasureUnitCode.Original", - .after = "WQX.ResultDepth.ConversionFactor" + .after = "WQXConversionFactor.ResultDepthHeightMeasure" ) clean.data$ResultDepthHeightMeasure.MeasureUnitCode[which( @@ -597,8 +584,8 @@ DepthProfileData <- function(.data, dplyr::relocate("ResultDepthHeightMeasure.MeasureUnitCode", .after = "ResultDepthHeightMeasure.MeasureUnitCode" ) - # uncoment below to delete WQX.ResultDepth.ConversionFactor column - #clean.data <- dplyr::select(clean.data, -"WQX.ResultDepth.ConversionFactor") + # uncomment below to delete WQXConversionFactor.ResultDepthHeightMeasure column + #clean.data <- dplyr::select(clean.data, -"WQXConversionFactor.ResultDepthHeightMeasure") } # uncomment below to delete WQX.Depth.TargetUnit column @@ -607,6 +594,7 @@ DepthProfileData <- function(.data, return(clean.data) } else { stop("'transform' argument must be Boolean (TRUE or FALSE)") + } } } From 8ace3eefa64747dee3b6d9ef059e228ed16fbb3c Mon Sep 17 00:00:00 2001 From: cristinamullin Date: Wed, 19 Oct 2022 15:32:45 -0400 Subject: [PATCH 08/10] update pages --- docs/articles/CONTRIBUTING.html | 2 +- docs/articles/WQPDataHarmonization.html | 2 +- docs/pkgdown.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/articles/CONTRIBUTING.html b/docs/articles/CONTRIBUTING.html index 0d366923..e4331977 100644 --- a/docs/articles/CONTRIBUTING.html +++ b/docs/articles/CONTRIBUTING.html @@ -71,7 +71,7 @@

    Contributing

    -

    2022-10-18

    +

    2022-10-19

    Source: vignettes/CONTRIBUTING.Rmd
    CONTRIBUTING.Rmd
    diff --git a/docs/articles/WQPDataHarmonization.html b/docs/articles/WQPDataHarmonization.html index 9a21a12a..6949d068 100644 --- a/docs/articles/WQPDataHarmonization.html +++ b/docs/articles/WQPDataHarmonization.html @@ -73,7 +73,7 @@

    Cristina A. Mullin

    -

    2022-10-18

    +

    2022-10-19

    Source: vignettes/WQPDataHarmonization.Rmd
    WQPDataHarmonization.Rmd
    diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 9681f792..82d5339c 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -4,7 +4,7 @@ pkgdown_sha: ~ articles: CONTRIBUTING: CONTRIBUTING.html WQPDataHarmonization: WQPDataHarmonization.html -last_built: 2022-10-18T21:55Z +last_built: 2022-10-19T19:15Z urls: reference: usepa.github.io/tada/reference article: usepa.github.io/tada/articles From f3d31c2612a551245b7faf4d80eedf32978bc5f9 Mon Sep 17 00:00:00 2001 From: cristinamullin Date: Wed, 19 Oct 2022 15:37:17 -0400 Subject: [PATCH 09/10] removes rlang req importFrom(rlang,":=") --- DESCRIPTION | 2 +- NAMESPACE | 1 - R/ResultFlagsDependent.R | 2 -- vignettes/WQPDataHarmonization.Rmd | 2 +- 4 files changed, 2 insertions(+), 5 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index e212f7bb..b3548f26 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -39,11 +39,11 @@ Imports: utils, RColorBrewer, stats, - rlang, lubridate Depends: R (>= 3.5.0) Suggests: + rlang, remotes, tidyverse, knitr, diff --git a/NAMESPACE b/NAMESPACE index eb6d9e8a..3ee28e33 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -30,4 +30,3 @@ export(TransformCensoredData) export(WQXTargetUnits) export(readWQPwebservice) importFrom(magrittr,"%>%") -importFrom(rlang,":=") diff --git a/R/ResultFlagsDependent.R b/R/ResultFlagsDependent.R index e01db306..5a495edb 100644 --- a/R/ResultFlagsDependent.R +++ b/R/ResultFlagsDependent.R @@ -325,8 +325,6 @@ InvalidResultUnit <- function(.data, clean = TRUE) { #' When transform = FALSE, the output is the full dataset with 'Conversion.Factor' #' columns and a 'WQX.Depth.TargetUnit' column. #' -#' @importFrom rlang := -#' #' @export #' diff --git a/vignettes/WQPDataHarmonization.Rmd b/vignettes/WQPDataHarmonization.Rmd index 1b1d38e5..0c647734 100644 --- a/vignettes/WQPDataHarmonization.Rmd +++ b/vignettes/WQPDataHarmonization.Rmd @@ -35,7 +35,7 @@ The following code will also install any packages you do not have, and load all packages required to run this vignette into your R session. ```{r, results = 'hide', message = FALSE, warning = FALSE} -list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes", "rlang") +list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])] if(length(new.packages)) install.packages(new.packages) From d041c8f8b845635c58fb3ef49253ff4d07081b7c Mon Sep 17 00:00:00 2001 From: cristinamullin Date: Wed, 19 Oct 2022 16:24:05 -0400 Subject: [PATCH 10/10] update pages --- docs/articles/WQPDataHarmonization.html | 8 ++++++-- docs/pkgdown.yml | 2 +- docs/search.json | 2 +- vignettes/WQPDataHarmonization.Rmd | 4 ++++ 4 files changed, 12 insertions(+), 4 deletions(-) diff --git a/docs/articles/WQPDataHarmonization.html b/docs/articles/WQPDataHarmonization.html index 6949d068..ed0ae626 100644 --- a/docs/articles/WQPDataHarmonization.html +++ b/docs/articles/WQPDataHarmonization.html @@ -98,7 +98,7 @@

    Install and load packages 
    -list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes", "rlang")
+list.of.packages <- c("plyr", "data.table", "dataRetrieval", "dplyr", "ggplot2", "grDevices", "magrittr", "stringr", "utils", "RColorBrewer", "stats", "lubridate", "remotes")
 
 new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
 if(length(new.packages)) install.packages(new.packages)
    @@ -246,7 +246,11 @@

    Retrieve WQP data
    -#You can edit this to define your own WQP query inputs below
+# uncomment below if you would like to review differences between the profiles you get using readWQPdata vs. TADAdataRetrieval. This is because TADAdataRetrieval automatically joins in other data from different WQP profiles, and does some additional data cleaning as part of the data retrieval process
+
+#dataRetrievalProfile <- dataRetrieval::readWQPdata(statecode = "UT", characteristicName = c("Ammonia", "Nitrate", "Nitrogen"), startDate = "01-01-2021", ignore_attributes = TRUE)
+
+#You can edit this to define your own WQP query inputs below
 TADAProfile <- TADAdataRetrieval(statecode = "UT", characteristicName = c("Ammonia", "Nitrate", "Nitrogen"), startDate = "01-01-2021")

    Option 2: Alternatively, you can use the data.table::fread function to read in a web service call for any WQP profile (un-comment).

    diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 82d5339c..19d4fcfe 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -4,7 +4,7 @@ pkgdown_sha: ~ articles: CONTRIBUTING: CONTRIBUTING.html WQPDataHarmonization: WQPDataHarmonization.html -last_built: 2022-10-19T19:15Z +last_built: 2022-10-19T20:10Z urls: reference: usepa.github.io/tada/reference article: usepa.github.io/tada/articles diff --git a/docs/search.json b/docs/search.json index d850b736..326405a4 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contribute-to-tada","dir":"Articles","previous_headings":"","what":"Contribute to TADA!","title":"Contributing","text":"encourage read project’s CONTRIBUTING policy (), LICENSE, README. ’re glad ’re thinking contributing EPA open source project! ’re unsure anything, just ask — submit issue pull request anyway. worst can happen ’ll politely ask change something. appreciate friendly contributions. matter , spot error, omission, bug, ’re welcome open issue repo!","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"package-development","dir":"Articles","previous_headings":"","what":"Package Development","title":"Contributing","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"what-is-github","dir":"Articles","previous_headings":"","what":"What is GitHub?","title":"Contributing","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"required-installations","dir":"Articles","previous_headings":"","what":"Required Installations","title":"Contributing","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"issues","dir":"Articles","previous_headings":"","what":"Issues","title":"Contributing","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"branches","dir":"Articles","previous_headings":"","what":"Branches","title":"Contributing","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"additional-references","dir":"Articles","previous_headings":"","what":"Additional References","title":"Contributing","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"open-source-code-policy","dir":"Articles","previous_headings":"","what":"Open-Source Code Policy","title":"Contributing","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"license","dir":"Articles","previous_headings":"","what":"License","title":"Contributing","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"disclaimer","dir":"Articles","previous_headings":"","what":"Disclaimer","title":"Contributing","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contact","dir":"Articles","previous_headings":"","what":"Contact","title":"Contributing","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"WQP Data Harmonization","text":"vignette walk discover, wrangle, harmonize Water Quality Portal (WQP) data multiple organizations.","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"install-and-load-packages","dir":"Articles","previous_headings":"","what":"Install and load packages","title":"WQP Data Harmonization","text":"install TADA, currently need install GitHub using remotes (shown) devtools. dataRetrieval downloaded CRAN, development version can downloaded directly GitHub (un-comment). following code also install packages , load packages required run vignette R session. Load remotes library installing TADA dataRetrieval GitHub Uncomment lines install latest version TADA dataRetrieval GitHub. Load required libraries run vignette R session","code":"list.of.packages <- c(\"plyr\", \"data.table\", \"dataRetrieval\", \"dplyr\", \"ggplot2\", \"grDevices\", \"magrittr\", \"stringr\", \"utils\", \"RColorBrewer\", \"stats\", \"lubridate\", \"remotes\", \"rlang\") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,\"Package\"])] if(length(new.packages)) install.packages(new.packages) # If you have any issues loading the remotes library, uncomment the line below to install the \"remotes\" package specifying the repo # install.packages(\"remotes\", repos = \"http://cran.us.r-project.org\") library(remotes) # remotes::install_github(\"USGS-R/dataRetrieval\", dependencies=TRUE) remotes::install_github(\"USEPA/TADA\", dependencies=TRUE) library(plyr) library(data.table) library(dplyr) library(ggplot2) library(grDevices) library(magrittr) library(stringr) library(utils) library(RColorBrewer) library(stats) library(lubridate) library(rlang) library(dataRetrieval) library(TADA)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"retrieve-wqp-data","dir":"Articles","previous_headings":"","what":"Retrieve WQP data","title":"WQP Data Harmonization","text":"WQP data retrieved processed compatibility TADA. function, TADAdataRetrieval builds USGS dataRetrieval package functions. joins three WQP profiles (.e., station, narrow, phys/chem), changes data Characteristic, Speciation, Fraction, Unit fields uppercase, removes true duplicates, removes data non-water media types, cleans results special characters. function uses inputs dataRetrieval readWQPdata function. readWQPdata restrict characteristics pulled Water Quality Portal (WQP). may specify desired characteristics using, instance: characteristicName = “pH”. Data retrieval filters include: statecode endDate startDate countycode siteid siteType characteristicName ActivityMediaName Please aware TADAdataRetrieval function automatically runs TADA autoclean MeasureValueSpecialCharacters functions well, required subsequent functions within TADA R package run. functions alter /add following WQP columns (enter ?MeasureValueSpecialCharacters ?autoclean console details): Alters (e.g., ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric) ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue Adds (data cleaning transformations done directly “ResultMeasureValue” “DetectionLimitMeasureValue” columns, however original “ResultMeasureValue” “DetectionLimitMeasureValue” columns values WQP preserved new fields, “ResultMeasureValue.Original” “DetectionLimitMeasureValue.Original”. Additionally, “TADA.ResultMeasureValue.Flag” “TADA.DetectionLimitMeasureValue.Flag” created track changes made “ResultMeasureValue” “DetectionLimitMeasureValue” columns; provide information result values needed address censored data later (.e., nondetections). Specifically, new columns flag special characters included result values, specifies special characters . ResultMeasureValue.Original TADA.ResultMeasureValue.Flag DetectionLimitMeasureValue.Original TADA.DetectionLimitMeasureValue.Flag Downloads using TADAdataRetrieval columns time, aware data uploaded Water Quality Portal individual organizations, may may follow conventions. Data metadata quality guaranteed! Make sure carefully explore data make conservative quality assurance decisions information limited. Tips: query filters WQP work within fields ORs. example: Characteristics: choose pH & - ’s . means retrieve pH data available. States: Similarly, choose VA IL, ’s . means retrieve VA IL data available. Combinations fields ANDs, State/VA Characteristic/”. means receive data available VA. “Characteristic” “Characteristic Type” also work . means Characteristic must fall within CharacteristicGroup filters used, get error. “siteid” general term WQP uses describe Site IDs USGS databases Monitoring Location Identifiers (Water Quality Portal). monitoring location Water Quality Portal (WQP) unique Monitoring Location Identifier, regardless database derives. Monitoring Location Identifier WQP concatenated Organization Identifier plus Site ID number. Site IDs include number unique identifiers monitoring locations within USGS NWIS EPA’s WQX databases separately. Additional resources: Review function documentation entering following code console: ?TADAdataRetrieval Introduction dataRetrieval package General Data Import Water Quality Portal Water Quality Portal Web Services Guide dataRetrieval Tutorial Option 1: Use TADAdataRetrieval function. Option 2: Alternatively, can use data.table::fread function read web service call WQP profile (un-comment). Option 3: need download large amount data across large area, TADAdataRetrieval function working due WQP timeout issues, TADABigdataRetrieval function may work better. function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested. See ?TADABigdataRetrieval details. WARNING, can take multiple hours run. total run time depends query inputs. Review column names TADA Profile","code":"#You can edit this to define your own WQP query inputs below TADAProfile <- TADAdataRetrieval(statecode = \"UT\", characteristicName = c(\"Ammonia\", \"Nitrate\", \"Nitrogen\"), startDate = \"01-01-2021\") # New_Draft_fullphyschem <- data.table::fread(\"https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET\") #AllWaterTempData <- TADABigdataRetrieval(startDate = \"2019-01-01\", endDate = \"2021-12-31\", characteristicName = \"Temperature, water\", siteType = \"Stream\") colnames(TADAProfile) #> [1] \"OrganizationIdentifier\" #> [2] \"OrganizationFormalName\" #> [3] \"ActivityIdentifier\" #> [4] \"ActivityTypeCode\" #> [5] \"ActivityMediaName\" #> [6] \"ActivityMediaSubdivisionName\" #> [7] \"ActivityStartDate\" #> [8] \"ActivityStartTime.Time\" #> [9] \"ActivityStartTime.TimeZoneCode\" #> [10] \"ActivityEndDate\" #> [11] \"ActivityEndTime.Time\" #> [12] \"ActivityEndTime.TimeZoneCode\" #> [13] \"ActivityDepthHeightMeasure.MeasureValue\" #> [14] \"ActivityDepthHeightMeasure.MeasureUnitCode\" #> [15] \"ActivityDepthAltitudeReferencePointText\" #> [16] \"ActivityTopDepthHeightMeasure.MeasureValue\" #> [17] \"ActivityTopDepthHeightMeasure.MeasureUnitCode\" #> [18] \"ActivityBottomDepthHeightMeasure.MeasureValue\" #> [19] \"ActivityBottomDepthHeightMeasure.MeasureUnitCode\" #> [20] \"ProjectIdentifier\" #> [21] \"ActivityConductingOrganizationText\" #> [22] \"MonitoringLocationIdentifier\" #> [23] \"ActivityCommentText\" #> [24] \"SampleAquifer\" #> [25] \"HydrologicCondition\" #> [26] \"HydrologicEvent\" #> [27] \"SampleCollectionMethod.MethodIdentifier\" #> [28] \"SampleCollectionMethod.MethodIdentifierContext\" #> [29] \"SampleCollectionMethod.MethodName\" #> [30] \"SampleCollectionEquipmentName\" #> [31] \"ResultDetectionConditionText\" #> [32] \"CharacteristicName\" #> [33] \"ResultSampleFractionText\" #> [34] \"ResultMeasureValue\" #> [35] \"ResultMeasureValue.Original\" #> [36] \"TADA.ResultMeasureValue.Flag\" #> [37] \"ResultMeasure.MeasureUnitCode\" #> [38] \"MeasureQualifierCode\" #> [39] \"ResultStatusIdentifier\" #> [40] \"StatisticalBaseCode\" #> [41] \"ResultValueTypeName\" #> [42] \"ResultWeightBasisText\" #> [43] \"ResultTimeBasisText\" #> [44] \"ResultTemperatureBasisText\" #> [45] \"ResultParticleSizeBasisText\" #> [46] \"PrecisionValue\" #> [47] \"ResultCommentText\" #> [48] \"USGSPCode\" #> [49] \"ResultDepthHeightMeasure.MeasureValue\" #> [50] \"ResultDepthHeightMeasure.MeasureUnitCode\" #> [51] \"ResultDepthAltitudeReferencePointText\" #> [52] \"SubjectTaxonomicName\" #> [53] \"SampleTissueAnatomyName\" #> [54] \"ResultAnalyticalMethod.MethodIdentifier\" #> [55] \"ResultAnalyticalMethod.MethodIdentifierContext\" #> [56] \"ResultAnalyticalMethod.MethodName\" #> [57] \"MethodDescriptionText\" #> [58] \"LaboratoryName\" #> [59] \"AnalysisStartDate\" #> [60] \"ResultLaboratoryCommentText\" #> [61] \"DetectionQuantitationLimitTypeName\" #> [62] \"DetectionQuantitationLimitMeasure.MeasureValue\" #> [63] \"DetectionLimitMeasureValue.Original\" #> [64] \"TADA.DetectionLimitMeasureValue.Flag\" #> [65] \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" #> [66] \"PreparationStartDate\" #> [67] \"ProviderName\" #> [68] \"timeZoneStart\" #> [69] \"timeZoneEnd\" #> [70] \"ActivityStartDateTime\" #> [71] \"ActivityEndDateTime\" #> [72] \"MonitoringLocationName\" #> [73] \"MonitoringLocationTypeName\" #> [74] \"MonitoringLocationDescriptionText\" #> [75] \"HUCEightDigitCode\" #> [76] \"DrainageAreaMeasure.MeasureValue\" #> [77] \"DrainageAreaMeasure.MeasureUnitCode\" #> [78] \"ContributingDrainageAreaMeasure.MeasureValue\" #> [79] \"ContributingDrainageAreaMeasure.MeasureUnitCode\" #> [80] \"LatitudeMeasure\" #> [81] \"LongitudeMeasure\" #> [82] \"SourceMapScaleNumeric\" #> [83] \"HorizontalAccuracyMeasure.MeasureValue\" #> [84] \"HorizontalAccuracyMeasure.MeasureUnitCode\" #> [85] \"HorizontalCollectionMethodName\" #> [86] \"HorizontalCoordinateReferenceSystemDatumName\" #> [87] \"VerticalMeasure.MeasureValue\" #> [88] \"VerticalMeasure.MeasureUnitCode\" #> [89] \"VerticalAccuracyMeasure.MeasureValue\" #> [90] \"VerticalAccuracyMeasure.MeasureUnitCode\" #> [91] \"VerticalCollectionMethodName\" #> [92] \"VerticalCoordinateReferenceSystemDatumName\" #> [93] \"CountryCode\" #> [94] \"StateCode\" #> [95] \"CountyCode\" #> [96] \"AquiferName\" #> [97] \"LocalAqfrName\" #> [98] \"FormationTypeText\" #> [99] \"AquiferTypeName\" #> [100] \"ConstructionDateText\" #> [101] \"WellDepthMeasure.MeasureValue\" #> [102] \"WellDepthMeasure.MeasureUnitCode\" #> [103] \"WellHoleDepthMeasure.MeasureValue\" #> [104] \"WellHoleDepthMeasure.MeasureUnitCode\" #> [105] \"MethodSpecificationName\" #> [106] \"ProjectName\" #> [107] \"ProjectDescriptionText\" #> [108] \"SamplingDesignTypeCode\" #> [109] \"QAPPApprovedIndicator\" #> [110] \"QAPPApprovalAgencyName\" #> [111] \"ProjectFileUrl\" #> [112] \"ProjectMonitoringLocationWeightingUrl\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"depth-unit-conversions","dir":"Articles","previous_headings":"","what":"Depth unit conversions","title":"WQP Data Harmonization","text":"Converts depth units consistent unit. ActivityDepthHeightMeasure.MeasureValue provides depth information. crucial column lake data less often river data. Function checks dataset depth profile data. depth profile columns populated, function appends ‘Conversion Factor’ columns populates columns based original unit (MeasureUnitCode columns) target unit, defined ‘unit’ argument. ‘Depth Target Unit’ column also appended, indicating unit selected depth data converted . transform = FALSE, output includes ‘Conversion Factor’ columns ‘Depth Target Unit’ column. transform = TRUE, output includes converted depth data ‘Depth Target Unit’ column, acts flag indicating rows converted. Default transform = TRUE. depth profile function can harmonize depth units across following fields (specific one): “ActivityDepthHeightMeasure”, “ActivityTopDepthHeightMeasure”, “ActivityBottomDepthHeightMeasure”, “ResultDepthHeightMeasure”). default . Allowable values ‘unit’ either ‘m’ (meter), ‘ft’ (feet), ‘’ (inch). ‘unit’ accepts one allowable value input. Default unit = “m”. See additional function documentation additional function options entering following code console: ?DepthProfileData","code":"#converts all depth profile data to meters TADAProfileClean1 <- DepthProfileData(TADAProfile, unit = \"m\", transform = TRUE) #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"result-unit-conversions","dir":"Articles","previous_headings":"","what":"Result unit conversions","title":"WQP Data Harmonization","text":"Converts results WQX target units. WQX target units pulled MeasureUnit domain table: https://cdx.epa.gov/wqx/download/DomainValues/MeasureUnit.CSV See additional function documentation additional function options entering following code console: ?WQXTargetUnits","code":"#Converts all results to WQX target units TADAProfileClean2 <- WQXTargetUnits(TADAProfileClean1, transform = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"statistically-aggregated-data","dir":"Articles","previous_headings":"","what":"Statistically aggregated data","title":"WQP Data Harmonization","text":"Checks removes statistically aggregated high frequency (.e., continuous) data, present. Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = “Reported Raw Data (attached)” clean = TRUE, rows aggregated continuous data removed dataset column appended Default clean = TRUE See function documentation additional function options entering following code console: ?DepthProfileData","code":"TADAProfileClean3 <- AggregatedContinuousData(TADAProfileClean2, clean = TRUE) #> [1] \"The dataset does not contain aggregated continuous data.\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-qaqc-service-result-flags","dir":"Articles","previous_headings":"","what":"WQX QAQC Service Result Flags","title":"WQP Data Harmonization","text":"Run following result functions address invalid method, fraction, speciation, unit metadata characteristic. default clean = TRUE, remove invalid results. can change clean = FALSE flag results, remove . See documentation details: ?InvalidMethod Clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidSpeciation clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidResultUnit clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidFraction clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended.","code":"TADAProfileClean4 <- InvalidMethod(TADAProfileClean3, clean = TRUE) #> [1] \"No changes were made, because we did not find any invalid method/characteristic combinations in your dataset.\" TADAProfileClean5 <- InvalidFraction(TADAProfileClean4, clean = TRUE) #> [1] \"All data is valid, therefore the function cannot be applied.\" TADAProfileClean6 <- InvalidSpeciation(TADAProfileClean5, clean = FALSE) TADAProfileClean7 <- InvalidResultUnit(TADAProfileClean6, clean = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-national-upper-and-lower-thresholds","dir":"Articles","previous_headings":"","what":"WQX national upper and lower thresholds","title":"WQP Data Harmonization","text":"Run following code flag remove results national upper lower bound characteristic unit combination. See documentation details: ?AboveNationalWQXUpperThreshold clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset. ?BelowNationalWQXUpperThreshold clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset. default clean=TRUE, can change flag results desired. Results flagged, removed, clean=FALSE.","code":"TADAProfileClean8 <- AboveNationalWQXUpperThreshold(TADAProfileClean7, clean = TRUE) TADAProfileClean9 <- BelowNationalWQXUpperThreshold(TADAProfileClean8, clean = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"potential-duplicates","dir":"Articles","previous_headings":"","what":"Potential duplicates","title":"WQP Data Harmonization","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. information, review documentation entering following console: ?PotentialDuplicateRowID clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":"TADAProfileClean10 <- PotentialDuplicateRowID(TADAProfileClean9)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"invalid-coordinates","dir":"Articles","previous_headings":"","what":"Invalid coordinates","title":"WQP Data Harmonization","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled “TADA.InvalidCoordinates” following flags (relevant dataset). latitude less zero, row flagged “LAT_OutsideUSA”. longitude greater zero less 145, row flagged “LONG_OutsideUSA”. latitude longitude contains string, “999”, row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged “Imprecise”.","code":"TADAProfileClean11 <- InvalidCoordinates(TADAProfileClean10, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"review-qapp-information","dir":"Articles","previous_headings":"","what":"Review QAPP information","title":"WQP Data Harmonization","text":"Check data approved QAPP function checks see information column “QAPPApprovedIndicator”. organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . field, Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. defaults remove rows data QAPPApprovedIndicator equals “N”. Users alternatively remove N’s NA’s using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function anything. Check see QAPP Doc Available function checks data submitted “ProjectFileUrl” column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":"TADAProfileClean12 <- QAPPapproved(TADAProfileClean11, clean = TRUE, cleanNA = FALSE) TADAProfileClean13 <- QAPPDocAvailable(TADAProfileClean12, clean = FALSE) #> Warning in QAPPDocAvailable(TADAProfileClean12, clean = FALSE): The dataset does #> not contain QAPP document url data."},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field","dir":"Articles","previous_headings":"","what":"Filter data by field","title":"WQP Data Harmonization","text":"section TADA user want review unique values specific fields may choose remove data particular values. start, review list fields number unique values field. Next, choose field list see unique values field, well number times value appears dataset. ’ll start ActivityTypeCode. list fields review: ResultCommentText often details relating additional QA. MeasureQualifierCode Contains information data flags 3. codes may designate suspect data flags may described detail ResultLaboratoryCommentText another column ActivityTypeCode field four unique values – “Sample-Routine”, “Quality Control Sample-Field Replicate”, “Field Msr/Obs”, “Quality Control Sample-Field Blank.” example want remove quality control values ActivityTypeCode field, therefore, ’ll specify want remove “Quality Control Sample-Field Replicate” “Quality Control Sample-Field Blank” values ActivityTypeCode field. ’ve completed review ActivityTypeCode field. Let’s move different field see values want remove – ’ll look values ResultStatusIdentifier field. ActivityMediaSubdivisionName field two unique values, “Surface Water” “Groundwater.” example want remove “Groundwater” values.","code":"FilterFields(TADAProfileClean13) #> FieldName Count #> 1 OrganizationFormalName 7 #> 2 ActivityTypeCode 7 #> 3 ActivityMediaName 1 #> 4 ActivityMediaSubdivisionName 4 #> 5 ActivityCommentText 4 #> 6 HydrologicCondition 8 #> 7 HydrologicEvent 4 #> 8 CharacteristicName 3 #> 9 MeasureQualifierCode 4 #> 10 SampleTissueAnatomyName 1 #> 11 LaboratoryName 11 #> 12 DetectionQuantitationLimitTypeName 7 #> 13 MonitoringLocationTypeName 14 #> 14 ProjectName 8 FilterFieldReview(\"ActivityTypeCode\", TADAProfileClean13) #> FieldValue Count #> 7 Sample-Routine 5268 #> 6 Sample-Integrated Vertical Profile 474 #> 4 Quality Control Sample-Field Replicate 454 #> 2 Quality Control Sample-Equipment Blank 276 #> 3 Quality Control Sample-Field Blank 60 #> 1 Field Msr/Obs 4 #> 5 Quality Control Sample-Lab Duplicate 2 TADAProfileClean14 <- dplyr::filter(TADAProfileClean13, !(ActivityTypeCode %in% c(\"Quality Control Sample-Field Replicate\", \"Quality Control Sample-Field Blank\", \"Quality Control Sample-Lab Duplicate\", \"Quality Control Sample-Equipment Blank\"))) FilterFieldReview(\"ActivityMediaSubdivisionName\", TADAProfileClean14) #> FieldValue Count #> 3 Surface Water 687 #> 2 Groundwater 106 #> 1 Bulk deposition 1 TADAProfileClean15 <- dplyr::filter(TADAProfileClean14, !(ActivityMediaSubdivisionName %in% c(\"Groundwater\", \"Bulk deposition\")))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field-subset-by-parameter","dir":"Articles","previous_headings":"","what":"Filter data by field, subset by parameter","title":"WQP Data Harmonization","text":"section TADA user want select parameter, review unique values associated parameter specific fields, choose remove particular values. start, review list parameters dataset. (list sorted highest lowest counts. first rows displayed save space page) Next, select parameter. Let’s explore fields associated Nitrogen: Selecting parameter generates list , subset selected parameter, fields number unique values field. choose field list. example ’ll remove certain values HydrologicEvent field. HydrologicEvent field three unique values. example want remove samples collected “Storm” events. Therefore, ’ll specify want remove rows CharacteristicName “NITROGEN” HydrologicEvent field “Storm.”","code":"FilterParList(TADAProfileClean15) #> FieldValue Count #> 3 NITROGEN 4130 #> 2 NITRATE 1479 #> 1 AMMONIA 30 FilterParFields(TADAProfileClean15, \"NITROGEN\") #> FieldName Count #> 1 ActivityTypeCode 2 #> 2 ActivityMediaName 1 #> 3 ActivityMediaSubdivisionName 2 #> 4 ActivityCommentText 3 #> 5 HydrologicCondition 7 #> 6 HydrologicEvent 2 #> 7 SampleCollectionMethod.MethodIdentifier 6 #> 8 SampleCollectionMethod.MethodIdentifierContext 2 #> 9 SampleCollectionMethod.MethodName 6 #> 10 SampleCollectionEquipmentName 6 #> 11 ResultSampleFractionText 3 #> 12 ResultMeasure.MeasureUnitCode 2 #> 13 MeasureQualifierCode 3 #> 14 ResultStatusIdentifier 2 #> 15 ResultValueTypeName 1 #> 16 ResultWeightBasisText 1 #> 17 ResultTemperatureBasisText 1 #> 18 ResultParticleSizeBasisText 1 #> 19 ResultCommentText 7 #> 20 ResultAnalyticalMethod.MethodIdentifier 2 #> 21 ResultAnalyticalMethod.MethodIdentifierContext 2 #> 22 ResultAnalyticalMethod.MethodName 2 #> 23 MethodDescriptionText 1 #> 24 LaboratoryName 2 #> 25 ResultLaboratoryCommentText 5 #> 26 DetectionQuantitationLimitTypeName 2 #> 27 MonitoringLocationTypeName 11 FilterParFieldReview(\"HydrologicEvent\", TADAProfileClean15, \"NITROGEN\") #> FieldValue Count #> 1 Routine sample 59 TADAProfileClean16 <- dplyr::filter(TADAProfileClean15, !(CharacteristicName %in% \"NITROGEN\" & HydrologicEvent %in% \"Storm\"))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"transform-characteristic-speciation-and-unit-values-to-tada-standards","dir":"Articles","previous_headings":"","what":"Transform Characteristic, Speciation, and Unit values to TADA Standards","title":"WQP Data Harmonization","text":"HarmonizeRefTable function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values following elements: CharacteristicName ResultSampleFractionText MethodSpecicationName ResultMeasure.MeasureUnitCode HarmonizeData function compares input dataset TADA Harmonization Reference Table. purpose function make similar data consistent therefore easier compare analyze. Users can also edit reference file meet needs desired. download argument can used save harmonization file current working directory download = TRUE, default download = FALSE. Optional outputs include: dataset Harmonization columns appended, dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE. examples HarmonizeData function can used: ResultSampleFractionText specifies forms constituents. cases, single CharacteristicName “Total” “Dissolved” forms specified, combined. cases, CharacteristicName ResultSampleFractionText combination given different identifier. identifier can used later identify comparable data groups calculating statistics creating figures combination. variables different names represent constituent (e.g., “Total Kjeldahl nitrogen (Organic N & NH3)” “Kjeldahl nitrogen”). HarmonizeData function gives consistent name (identifier) synonyms.","code":"UniqueHarmonizationRef <- HarmonizationRefTable(TADAProfileClean16, download = FALSE) TADAProfileClean17 <- HarmonizeData(TADAProfileClean16, ref = UniqueHarmonizationRef, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Cristina Mullin. Author, maintainer. Michelle Thawley. Author. Laura Shumway. Author. Jacob Greif. Author.","code":""},{"path":"usepa.github.io/tada/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Mullin, C.., Greif, J., Thawley, M., Shumway, L., 2022, TADA: R Tools Automated Data Assessment, U.S. Environmental Protection Agency, Washington, DC","code":"@Manual{, author = {Cristina A. Mullin and Jacob Greif and Michelle Thawley and Laura Shumway}, title = {TADA: R Tools for Automated Data Assessment}, address = {Washington, DC}, institution = {U.S. Environmental Protection Agency}, year = {2022}, url = {https://github.com/USEPA/TADA}, }"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"package-development","dir":"","previous_headings":"","what":"Package Development","title":"NA","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"what-is-github","dir":"","previous_headings":"","what":"What is GitHub?","title":"NA","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"required-installations","dir":"","previous_headings":"","what":"Required Installations","title":"NA","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"NA","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"branches","dir":"","previous_headings":"","what":"Branches","title":"NA","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"additional-references","dir":"","previous_headings":"","what":"Additional References","title":"NA","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/index.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"Tools for Automated Data Assessment R Package","text":"encourage read package’s CONTRIBUTING, LICENSE, README files (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/index.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"Tools for Automated Data Assessment R Package","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Tools for Automated Data Assessment R Package","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/index.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"Tools for Automated Data Assessment R Package","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Tools for Automated Data Assessment R Package","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/index.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"Tools for Automated Data Assessment R Package","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Tools for Automated Data Assessment R Package","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":[]},{"path":"usepa.github.io/tada/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"CC0 1.0 Universal","title":"CC0 1.0 Universal","text":"CREATIVE COMMONS CORPORATION LAW FIRM PROVIDE LEGAL SERVICES. DISTRIBUTION DOCUMENT CREATE ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES INFORMATION “-” BASIS. CREATIVE COMMONS MAKES WARRANTIES REGARDING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER, DISCLAIMS LIABILITY DAMAGES RESULTING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER.","code":""},{"path":"usepa.github.io/tada/LICENSE.html","id":"statement-of-purpose","dir":"","previous_headings":"","what":"Statement of Purpose","title":"CC0 1.0 Universal","text":"laws jurisdictions throughout world automatically confer exclusive Copyright Related Rights (defined ) upon creator subsequent owner(s) (, “owner”) original work authorship /database (, “Work”). Certain owners wish permanently relinquish rights Work purpose contributing commons creative, cultural scientific works (“Commons”) public can reliably without fear later claims infringement build upon, modify, incorporate works, reuse redistribute freely possible form whatsoever purposes, including without limitation commercial purposes. owners may contribute Commons promote ideal free culture production creative, cultural scientific works, gain reputation greater distribution Work part use efforts others. /purposes motivations, without expectation additional consideration compensation, person associating CC0 Work (“Affirmer”), extent owner Copyright Related Rights Work, voluntarily elects apply CC0 Work publicly distribute Work terms, knowledge Copyright Related Rights Work meaning intended legal effect CC0 rights. Copyright Related Rights. Work made available CC0 may protected copyright related neighboring rights (“Copyright Related Rights”). 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Affirmer disclaims responsibility clearing rights persons may apply Work use thereof, including without limitation person’s Copyright Related Rights Work. , Affirmer disclaims responsibility obtaining necessary consents, permissions rights required use Work. Affirmer understands acknowledges Creative Commons party document duty obligation respect CC0 use Work.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"NA","text":"encourage read package’s CONTRIBUTING, LICENSE, README files (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"NA","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"NA","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/readme.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data upper threshold result values submitted WQX given characteristic. clean = TRUE, rows values upper WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"","code":"AboveNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data upper WQX threshold dataset clean = TRUE. Default clean = TRUE","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Aggregated Continuous Data — AggregatedContinuousData","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = \"Reported Raw Data (attached)\". clean = TRUE, rows aggregated continuous data removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"","code":"AggregatedContinuousData(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":".data TADA dataframe clean Boolean argument; removes aggregated continuous data dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"clean = FALSE, column flagging rows aggregated continuous data appended input data set. clean = TRUE, aggregated continuous data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — autoclean","title":"autoclean — autoclean","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — autoclean","text":"","code":"autoclean(.data)"},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — autoclean","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — autoclean","text":"autocleaned TADA data profile","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — autoclean","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":null,"dir":"Reference","previous_headings":"","what":"AutoFilter — AutoFilter","title":"AutoFilter — AutoFilter","text":"Function can used autofilter simplify WQP dataset. applying function, dataset contain result values water media types chemicals tissue (e.g. mercury fish tissue). complex biological data (counts macroinvertebrates) removed. function looks following fields autofilter: ActivityMediaName, ActivityMediaSubDivisionName, AssemblageSampledName","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AutoFilter — AutoFilter","text":"","code":"AutoFilter(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AutoFilter — AutoFilter","text":".data TADA dataframe clean Indicates whether flag columns appended data (clean = FALSE), flagged data transformed/filtered dataset columns appended (clean = TRUE).","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"AutoFilter — AutoFilter","text":"clean = FALSE, flag column appended dataset. clean = TRUE, flag column appended relevant rows removed.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data lower threshold result values submitted WQX given characteristic. clean = TRUE, rows values lower WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"","code":"BelowNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data lower WQX threshold dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalnumcount — decimalnumcount","title":"decimalnumcount — decimalnumcount","text":"character data type","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalnumcount — decimalnumcount","text":"","code":"decimalnumcount(x)"},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalnumcount — decimalnumcount","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalnumcount — decimalnumcount","text":"Number values right decimal point character type data.","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalplaces — decimalplaces","title":"decimalplaces — decimalplaces","text":"numeric data type","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalplaces — decimalplaces","text":"","code":"decimalplaces(x)"},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalplaces — decimalplaces","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalplaces — decimalplaces","text":"Number values right decimal point numeric type data.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":null,"dir":"Reference","previous_headings":"","what":"Depth Profile Flag & Unit Conversion — DepthProfileData","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Function checks dataset depth profile data. depth profile columns populated, function appends 'Conversion.Factor' columns populates columns based original unit (MeasureUnitCode columns) target unit, defined 'unit' argument. 'WQX.Depth.TargetUnit' column also appended, indicating unit selected depth data converted . transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"","code":"DepthProfileData( .data, unit = \"m\", fields = c(\"ActivityDepthHeightMeasure\", \"ActivityTopDepthHeightMeasure\", \"ActivityBottomDepthHeightMeasure\", \"ResultDepthHeightMeasure\"), transform = TRUE )"},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":".data TADA dataframe unit Character string input indicating uniform unit depth data converted . Allowable values 'unit' either 'm' (meter), 'ft' (feet), '' (inch). 'unit' accepts one allowable value input. Default unit = \"m\". fields Character string input indicating depth fields checked data. Allowable values 'fields' 'ActivityDepthHeightMeasure,' 'ActivityTopDepthHeightMeasure,' 'ActivityBottomDepthHeightMeasure,' 'ResultDepthHeightMeasure.'. Default include allowable values. transform Boolean argument; transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'Depth Target Unit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Full dataset converted uniform depth units 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. transform = FALSE, output full dataset 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field — FilterFieldReview","title":"Generate list of unique values in a given field — FilterFieldReview","text":"Function creates table pie chart unique values, counts values chosen field dataframe.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field — FilterFieldReview","text":"","code":"FilterFieldReview(field, .data)"},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field — FilterFieldReview","text":"field Field name .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field — FilterFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names — FilterFields","title":"Generate list of field names — FilterFields","text":"Function creates list fields input dataframe well number unique values field. list intended inform users specific fields explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names — FilterFields","text":"","code":"FilterFields(.data)"},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names — FilterFields","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names — FilterFields","text":"table fields count unique values field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"Function creates table pie chart unique values, counts values, chosen field dataframe subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"","code":"FilterParFieldReview(field, .data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"field Field name .data Optional argument; TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names subset by parameter — FilterParFields","title":"Generate list of field names subset by parameter — FilterParFields","text":"Function subsets input dataframe input parameter creates list fields subset dataframe well number unique values field. list intended inform users specific fields explore filter subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names subset by parameter — FilterParFields","text":"","code":"FilterParFields(.data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names subset by parameter — FilterParFields","text":".data TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names subset by parameter — FilterParFields","text":"table fields count unique values field, subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of parameters — FilterParList","title":"Generate list of parameters — FilterParList","text":"Function generates list characteristics input dataset, well number records . list intended inform users parameters explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of parameters — FilterParList","text":"","code":"FilterParList(.data)"},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of parameters — FilterParList","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of parameters — FilterParList","text":"list unique characteristics counts","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":null,"dir":"Reference","previous_headings":"","what":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Function summarizes censored data dataset, including substitutions made.","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"","code":"GenerateCensoredDataStats(.data)"},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":".data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Summary table","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table — GetMeasureUnitRef","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"Function downloads returns latest WQX MeasureUnit Domain table, adds additional target unit information, writes data sysdata.rda.","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"","code":"GetMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"sysdata.rda updated WQXunitRef object (unit conversion reference table)","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Function downloads returns newest available (cleaned) raw Water Quality Exchange (WQX) QAQC Characteristic Validation reference table. WQXcharValRef data frame contains information four functions: InvalidFraction, InvalidResultUnit, InvalidSpeciation, UncommonAnalyticalMethodID.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"","code":"GetWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Updated sysdata.rda updated WQXcharValRef object","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode can optionally edit reference file meet needs.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"","code":"HarmonizationRefTable(.data, download = FALSE)"},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":".data TADA dataframe download Boolean argument; download = TRUE, output downloaded current working directory.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Harmonization Reference Table unique input dataset","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"Function compares input dataset TADA Harmonization Reference Table, makes synonymous data consistent. Optional outputs include: 1) dataset Harmonization columns appended, 2) dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards 3) four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"","code":"HarmonizeData(.data, ref, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":".data TADA dataframe ref Optional argument specify dataframe use reference file. primary use argument user generated harmonization reference file unique data, made changes file. transform Boolean argument; transforms /converts original values dataset TADA Harmonization Reference Table values following fields: CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode. Default transform = TRUE. flag Boolean argument; appends columns TADA Harmonization Reference Table dataframe. Default flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"transform = FALSE flag = TRUE, Harmonization Reference Table columns appended dataset . transform = TRUE flag = TRUE, Harmonization columns appended dataset transformations executed. transform = TRUE flag = FALSE, transformations executed . transform = FALSE flag = FALSE, error returned (function return input dataframe unchanged input allowed).","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":null,"dir":"Reference","previous_headings":"","what":"Invalid coordinates — InvalidCoordinates","title":"Invalid coordinates — InvalidCoordinates","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled \"TADA.InvalidCoordinates\" following flags (relevant dataset). latitude less zero, row flagged \"LAT_OutsideUSA\". longitude greater zero less 145, row flagged \"LONG_OutsideUSA\". latitude longitude contains string, \"999\", row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged \"Imprecise\".","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Invalid coordinates — InvalidCoordinates","text":"","code":"InvalidCoordinates(.data, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Invalid coordinates — InvalidCoordinates","text":".data TADA dataframe clean_outsideUSA Boolean argument; removes data coordinates outside United States clean_outsideUSA = TRUE. Default clean = FALSE. clean_imprecise Boolean arguments; removes imprecise data clean_imprecise = TRUE. Default clean_imprecise = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Invalid coordinates — InvalidCoordinates","text":"either clean_outsideUSA clean_imprecise argument FALSE, column flagging rows respective QA check appended input dataset. either argument TRUE, \"invalid\" \"imprecise\" data removed, respectively.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Sample Fraction Validity — InvalidFraction","title":"Check Sample Fraction Validity — InvalidFraction","text":"Function checks validity characteristic-fraction combination dataset. clean = TRUE, rows invalid characteristic-fraction combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Sample Fraction Validity — InvalidFraction","text":"","code":"InvalidFraction(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Sample Fraction Validity — InvalidFraction","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-fraction combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Sample Fraction Validity — InvalidFraction","text":"clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Invalid Analytical Methods — InvalidMethod","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"Function checks validity characteristic-analytical method combination dataset. clean = TRUE, rows invalid characteristic-analytical method combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"","code":"InvalidMethod(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Invalid Analytical Methods — InvalidMethod","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-analytical method combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Unit Validity — InvalidResultUnit","title":"Check Result Unit Validity — InvalidResultUnit","text":"Function checks validity characteristic-media-result unit combination dataset. clean = TRUE, rows invalid characteristic-media-result unit combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Unit Validity — InvalidResultUnit","text":"","code":"InvalidResultUnit(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Unit Validity — InvalidResultUnit","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-media-result unit combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Unit Validity — InvalidResultUnit","text":"clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Method Speciation Validity — InvalidSpeciation","title":"Check Method Speciation Validity — InvalidSpeciation","text":"Function checks validity characteristic-method speciation combination dataset. clean = TRUE, rows invalid characteristic-method speciation combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Method Speciation Validity — InvalidSpeciation","text":"","code":"InvalidSpeciation(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Method Speciation Validity — InvalidSpeciation","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-method speciation combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Method Speciation Validity — InvalidSpeciation","text":"#'clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Function checks special characters non-numeric values ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields appends flag columns indicating special characters included , special characters . ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields also converted class numeric.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"","code":"MeasureValueSpecialCharacters(.data)"},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Full dataset column indicating presence special characters ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields. Additionally, ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric, copies column created preserve original character values.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"usepa.github.io/tada/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Potential Duplicates — PotentialDuplicateRowID","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"","code":"PotentialDuplicateRowID(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":".data TADA dataframe clean Boolean argument; removes potential duplicate data dataset clean = TRUE. clean = FALSE, column indicating potential duplicate rows unique number linking rows appended input data set. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":null,"dir":"Reference","previous_headings":"","what":"Check data for an approved QAPP — QAPPapproved","title":"Check data for an approved QAPP — QAPPapproved","text":"Function checks data submitted column \"QAPPApprovedIndicator\". organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. default removes rows data QAPPApprovedIndicator equals \"N\". Users alternatively remove N's NA's using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function make changes data.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check data for an approved QAPP — QAPPapproved","text":"","code":"QAPPapproved(.data, clean = TRUE, cleanNA = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check data for an approved QAPP — QAPPapproved","text":".data TADA dataframe clean Boolean argument two possible values called \"TRUE\" \"FALSE\". clean=TRUE, rows data QAPPApprovedIndicator equals \"N\" removed. , clean=FALSE, rows data QAPPApprovedIndicator equals \"N\" retained. cleanNA Boolean argument two possible values called \"TRUE\" \"FALSE\". cleanNA=TRUE, rows data QAPPApprovedIndicator equals \"NA\" removed. , cleanNA=FALSE, rows data QAPPApprovedIndicator equals \"NA\" retained.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check data for an approved QAPP — QAPPapproved","text":"clean = FALSE cleanNA = FALSE, data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check data for an approved QAPP — QAPPapproved","text":"Note: required field, often left blank (NA) even data associated QAPP. states tribes collect monitoring data using 106 funding (almost state tribal data WQX) required EPA approved QAPP receive 106 funding. Therefore, organizations data approved QAPP even data submitted WQP NA.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"Function checks data submitted \"ProjectFileUrl\" column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"","code":"QAPPDocAvailable(.data, clean = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":".data TADA dataframe clean Boolean argument; removes data without associated QAPP document dataset clean = TRUE. Default clean = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"clean = FALSE, column appended input data set flags rows associated QAPP document. clean = TRUE, data without associated QAPP document removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":null,"dir":"Reference","previous_headings":"","what":"Read in WQP data using WQP web services directly — readWQPwebservice","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Go WQP website (https://www.waterqualitydata.us/) fill advanced query form. Choose Full Physical Chemical Data Profile, data sources, file format Comma-Separated. finished, hit download button. Instead, copy web service URL located bottom page header \"Result\". Use \"Result\" web service URL input function download data directly R.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"","code":"readWQPwebservice(webservice)"},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"webservice WQP Web Service URL, entered within quotes \"url\"","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"WQP Full Physical Chemical Results Data Profile","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Note: may useful save Query URL well comment within code. URL return WQP query page original data filters.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"RemoveEmptyColumns — RemoveEmptyColumns","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Removes columns NA values. Used quickly reduce number columns dataframe improve management readability dataset.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"","code":"RemoveEmptyColumns(.data)"},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":".data Dataframe","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Full dataset empty data columns removed","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"TADABigdataRetrieval( startDate = \"null\", endDate = \"null\", characteristicName = \"null\", siteType = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"startDate Start Date YYYY-MM-DD format, example, \"1995-01-01\" endDate end date YYYY-MM-DD format, example, \"2020-12-31\" characteristicName Name water quality parameter siteType Name water body type (e.g., \"Stream\", \"Lake, Reservoir, Impoundment\")","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"Similarly TADAdataRetrieval function, function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"if (FALSE) { tada2 <- TADABigdataRetrieval(startDate = \"01-01-2021\", endDate = \"01-01-2022\", characteristicName = \"Nitrogen\", siteType = \"Stream\") }"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Retrieve data Water Quality Portal (WQP) output TADA-compatible dataset.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"TADAdataRetrieval( statecode = \"null\", startDate = \"null\", countycode = \"null\", siteid = \"null\", siteType = \"null\", characteristicName = \"null\", ActivityMediaName = \"null\", endDate = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"statecode Code identifies state startDate Start Date countycode Code identifies county siteid Unique monitoring station identifier siteType Type waterbody characteristicName Name parameter ActivityMediaName Sampling substrate water, air, sediment endDate End Date","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Keep mind query filters WQP work within fields ORs. example, characteristics – choose pH & – ’s . Similarly, choose VA IL, ’s . combo fields ANDs. State/VA Characteristic/\". \"Characteristic\" \"Characteristic Group\" also work . function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"if (FALSE) { tada1 <- TADAdataRetrieval(statecode = \"WI\", countycode = \"Dane\", characteristicName = \"Phosphorus\") }"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — TADAprofileCheck","title":"autoclean — TADAprofileCheck","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — TADAprofileCheck","text":"","code":"TADAprofileCheck(.data)"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — TADAprofileCheck","text":".data dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — TADAprofileCheck","text":"cleaned TADA data profile TADA Profile Check function checks column names dataframe include TADA profile fields. used beginning TADA functions ensure input data frame suitable (.e. either full physical/chemical results profile downloaded WQP TADA profile template downloaded EPA TADA webpage.) Boolean result indicating whether input dataframe contains TADA profile fields.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — TADAprofileCheck","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":null,"dir":"Reference","previous_headings":"","what":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"Function substitutes monitoring device/method detection limits (available) result values applicable.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"","code":"TransformCensoredData(transform, .data)"},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE. .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform=TRUE, monitoring device/method detection limits (available) substituted result values units. transform = FALSE, monitoring device/method detection limits (available) substituted result values units - Instead, columns appended rows may include censored data. flag indicates 1) row contains censored data, 2) monitoring device/method detection limits available.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Existing Data in sysdata.rda — UpdateInternalData","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Function internal use . used internal functions used update internal data (e.g. reference tables). function adapted stackoverflow.com thread, can accessed .","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"","code":"UpdateInternalData(..., list = character())"},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"... Objects updated sysdata.rda. list Argument indicating data class list.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Updated sysdata.rda file","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"Update Measure Unit Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"","code":"UpdateMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"Update Characteristic Validation Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"","code":"UpdateWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"Used store cached WQX QAQC Characteristic Validation Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"","code":"WQXCharValRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"object class NULL length 0.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Units to WQX Target Units — WQXTargetUnits","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function compares measure units input data Water Quality Exchange (WQX) 3.0 QAQC Characteristic Validation table.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"","code":"WQXTargetUnits(.data, transform = TRUE)"},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":".data TADA dataset transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"transform=TRUE, result values units converted WQX target units. function changes values within \"ResultMeasure.MeasureUnitCode\" \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" WQX target units converts respective values within \"ResultMeasureValue\" \"DetectionQuantitationLimitMeasure.MeasureValue\" fields. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=TRUE add following two fields input dataset, \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\", retain original result unit values. transform = FALSE, result values units converted WQX target units, columns appended indicate target units conversion factors , data can converted. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=FALSE add following two fields input dataset: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function ALWAYS add following two columns input dataset: \"WQX.ResultMeasureValue.UnitConversion\", \"WQX.DetectionLimitMeasureValue.UnitConversion\" two fields indicate data can converted.\"NoResultValue\" means data converted ResultMeasureValue, \"NoTargetUnit\" means data converted original unit associated target unit WQX. \"Convert\" means data can transformed, \"Converted\" means function run input transform = TRUE, values already converted. also uses following six fields input dataset: \"CharacteristicName\", \"ActivityMediaName\", \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" function adds following two fields transforms values within following four fields transform=TRUE: Adds: \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\". Transforms: \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\". function adds following two fields transform=FALSE: Adds: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"Used store cached Measure Unit Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"","code":"WQXunitRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"object class NULL length 0.","code":""}] +[{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contribute-to-tada","dir":"Articles","previous_headings":"","what":"Contribute to TADA!","title":"Contributing","text":"encourage read project’s CONTRIBUTING policy (), LICENSE, README. ’re glad ’re thinking contributing EPA open source project! ’re unsure anything, just ask — submit issue pull request anyway. worst can happen ’ll politely ask change something. appreciate friendly contributions. matter , spot error, omission, bug, ’re welcome open issue repo!","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"package-development","dir":"Articles","previous_headings":"","what":"Package Development","title":"Contributing","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"what-is-github","dir":"Articles","previous_headings":"","what":"What is GitHub?","title":"Contributing","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"required-installations","dir":"Articles","previous_headings":"","what":"Required Installations","title":"Contributing","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"issues","dir":"Articles","previous_headings":"","what":"Issues","title":"Contributing","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"branches","dir":"Articles","previous_headings":"","what":"Branches","title":"Contributing","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"additional-references","dir":"Articles","previous_headings":"","what":"Additional References","title":"Contributing","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"open-source-code-policy","dir":"Articles","previous_headings":"","what":"Open-Source Code Policy","title":"Contributing","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"license","dir":"Articles","previous_headings":"","what":"License","title":"Contributing","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"disclaimer","dir":"Articles","previous_headings":"","what":"Disclaimer","title":"Contributing","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/articles/CONTRIBUTING.html","id":"contact","dir":"Articles","previous_headings":"","what":"Contact","title":"Contributing","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"overview","dir":"Articles","previous_headings":"","what":"Overview","title":"WQP Data Harmonization","text":"vignette walk discover, wrangle, harmonize Water Quality Portal (WQP) data multiple organizations.","code":""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"install-and-load-packages","dir":"Articles","previous_headings":"","what":"Install and load packages","title":"WQP Data Harmonization","text":"install TADA, currently need install GitHub using remotes (shown) devtools. dataRetrieval downloaded CRAN, development version can downloaded directly GitHub (un-comment). following code also install packages , load packages required run vignette R session. Load remotes library installing TADA dataRetrieval GitHub Uncomment lines install latest version TADA dataRetrieval GitHub. Load required libraries run vignette R session","code":"list.of.packages <- c(\"plyr\", \"data.table\", \"dataRetrieval\", \"dplyr\", \"ggplot2\", \"grDevices\", \"magrittr\", \"stringr\", \"utils\", \"RColorBrewer\", \"stats\", \"lubridate\", \"remotes\") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,\"Package\"])] if(length(new.packages)) install.packages(new.packages) # If you have any issues loading the remotes library, uncomment the line below to install the \"remotes\" package specifying the repo # install.packages(\"remotes\", repos = \"http://cran.us.r-project.org\") library(remotes) # remotes::install_github(\"USGS-R/dataRetrieval\", dependencies=TRUE) remotes::install_github(\"USEPA/TADA\", dependencies=TRUE) library(plyr) library(data.table) library(dplyr) library(ggplot2) library(grDevices) library(magrittr) library(stringr) library(utils) library(RColorBrewer) library(stats) library(lubridate) library(rlang) library(dataRetrieval) library(TADA)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"retrieve-wqp-data","dir":"Articles","previous_headings":"","what":"Retrieve WQP data","title":"WQP Data Harmonization","text":"WQP data retrieved processed compatibility TADA. function, TADAdataRetrieval builds USGS dataRetrieval package functions. joins three WQP profiles (.e., station, narrow, phys/chem), changes data Characteristic, Speciation, Fraction, Unit fields uppercase, removes true duplicates, removes data non-water media types, cleans results special characters. function uses inputs dataRetrieval readWQPdata function. readWQPdata restrict characteristics pulled Water Quality Portal (WQP). may specify desired characteristics using, instance: characteristicName = “pH”. Data retrieval filters include: statecode endDate startDate countycode siteid siteType characteristicName ActivityMediaName Please aware TADAdataRetrieval function automatically runs TADA autoclean MeasureValueSpecialCharacters functions well, required subsequent functions within TADA R package run. functions alter /add following WQP columns (enter ?MeasureValueSpecialCharacters ?autoclean console details): Alters (e.g., ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric) ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue Adds (data cleaning transformations done directly “ResultMeasureValue” “DetectionLimitMeasureValue” columns, however original “ResultMeasureValue” “DetectionLimitMeasureValue” columns values WQP preserved new fields, “ResultMeasureValue.Original” “DetectionLimitMeasureValue.Original”. Additionally, “TADA.ResultMeasureValue.Flag” “TADA.DetectionLimitMeasureValue.Flag” created track changes made “ResultMeasureValue” “DetectionLimitMeasureValue” columns; provide information result values needed address censored data later (.e., nondetections). Specifically, new columns flag special characters included result values, specifies special characters . ResultMeasureValue.Original TADA.ResultMeasureValue.Flag DetectionLimitMeasureValue.Original TADA.DetectionLimitMeasureValue.Flag Downloads using TADAdataRetrieval columns time, aware data uploaded Water Quality Portal individual organizations, may may follow conventions. Data metadata quality guaranteed! Make sure carefully explore data make conservative quality assurance decisions information limited. Tips: query filters WQP work within fields ORs. example: Characteristics: choose pH & - ’s . means retrieve pH data available. States: Similarly, choose VA IL, ’s . means retrieve VA IL data available. Combinations fields ANDs, State/VA Characteristic/”. means receive data available VA. “Characteristic” “Characteristic Type” also work . means Characteristic must fall within CharacteristicGroup filters used, get error. “siteid” general term WQP uses describe Site IDs USGS databases Monitoring Location Identifiers (Water Quality Portal). monitoring location Water Quality Portal (WQP) unique Monitoring Location Identifier, regardless database derives. Monitoring Location Identifier WQP concatenated Organization Identifier plus Site ID number. Site IDs include number unique identifiers monitoring locations within USGS NWIS EPA’s WQX databases separately. Additional resources: Review function documentation entering following code console: ?TADAdataRetrieval Introduction dataRetrieval package General Data Import Water Quality Portal Water Quality Portal Web Services Guide dataRetrieval Tutorial Option 1: Use TADAdataRetrieval function. Option 2: Alternatively, can use data.table::fread function read web service call WQP profile (un-comment). Option 3: need download large amount data across large area, TADAdataRetrieval function working due WQP timeout issues, TADABigdataRetrieval function may work better. function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested. See ?TADABigdataRetrieval details. WARNING, can take multiple hours run. total run time depends query inputs. Review column names TADA Profile","code":"# uncomment below if you would like to review differences between the profiles you get using readWQPdata vs. TADAdataRetrieval. This is because TADAdataRetrieval automatically joins in other data from different WQP profiles, and does some additional data cleaning as part of the data retrieval process #dataRetrievalProfile <- dataRetrieval::readWQPdata(statecode = \"UT\", characteristicName = c(\"Ammonia\", \"Nitrate\", \"Nitrogen\"), startDate = \"01-01-2021\", ignore_attributes = TRUE) #You can edit this to define your own WQP query inputs below TADAProfile <- TADAdataRetrieval(statecode = \"UT\", characteristicName = c(\"Ammonia\", \"Nitrate\", \"Nitrogen\"), startDate = \"01-01-2021\") # New_Draft_fullphyschem <- data.table::fread(\"https://www.waterqualitydata.us/data/Result/search?countrycode=US&statecode=US%3A49&siteid=UTAHDWQ_WQX-4925610&startDateLo=01-01-2015&startDateHi=12-31-2016&mimeType=csv&zip=no&sorted=yes&dataProfile=fullPhysChem&providers=NWIS&providers=STEWARDS&providers=STORET\") #AllWaterTempData <- TADABigdataRetrieval(startDate = \"2019-01-01\", endDate = \"2021-12-31\", characteristicName = \"Temperature, water\", siteType = \"Stream\") colnames(TADAProfile) #> [1] \"OrganizationIdentifier\" #> [2] \"OrganizationFormalName\" #> [3] \"ActivityIdentifier\" #> [4] \"ActivityTypeCode\" #> [5] \"ActivityMediaName\" #> [6] \"ActivityMediaSubdivisionName\" #> [7] \"ActivityStartDate\" #> [8] \"ActivityStartTime.Time\" #> [9] \"ActivityStartTime.TimeZoneCode\" #> [10] \"ActivityEndDate\" #> [11] \"ActivityEndTime.Time\" #> [12] \"ActivityEndTime.TimeZoneCode\" #> [13] \"ActivityDepthHeightMeasure.MeasureValue\" #> [14] \"ActivityDepthHeightMeasure.MeasureUnitCode\" #> [15] \"ActivityDepthAltitudeReferencePointText\" #> [16] \"ActivityTopDepthHeightMeasure.MeasureValue\" #> [17] \"ActivityTopDepthHeightMeasure.MeasureUnitCode\" #> [18] \"ActivityBottomDepthHeightMeasure.MeasureValue\" #> [19] \"ActivityBottomDepthHeightMeasure.MeasureUnitCode\" #> [20] \"ProjectIdentifier\" #> [21] \"ActivityConductingOrganizationText\" #> [22] \"MonitoringLocationIdentifier\" #> [23] \"ActivityCommentText\" #> [24] \"SampleAquifer\" #> [25] \"HydrologicCondition\" #> [26] \"HydrologicEvent\" #> [27] \"SampleCollectionMethod.MethodIdentifier\" #> [28] \"SampleCollectionMethod.MethodIdentifierContext\" #> [29] \"SampleCollectionMethod.MethodName\" #> [30] \"SampleCollectionEquipmentName\" #> [31] \"ResultDetectionConditionText\" #> [32] \"CharacteristicName\" #> [33] \"ResultSampleFractionText\" #> [34] \"ResultMeasureValue\" #> [35] \"ResultMeasureValue.Original\" #> [36] \"TADA.ResultMeasureValue.Flag\" #> [37] \"ResultMeasure.MeasureUnitCode\" #> [38] \"MeasureQualifierCode\" #> [39] \"ResultStatusIdentifier\" #> [40] \"StatisticalBaseCode\" #> [41] \"ResultValueTypeName\" #> [42] \"ResultWeightBasisText\" #> [43] \"ResultTimeBasisText\" #> [44] \"ResultTemperatureBasisText\" #> [45] \"ResultParticleSizeBasisText\" #> [46] \"PrecisionValue\" #> [47] \"ResultCommentText\" #> [48] \"USGSPCode\" #> [49] \"ResultDepthHeightMeasure.MeasureValue\" #> [50] \"ResultDepthHeightMeasure.MeasureUnitCode\" #> [51] \"ResultDepthAltitudeReferencePointText\" #> [52] \"SubjectTaxonomicName\" #> [53] \"SampleTissueAnatomyName\" #> [54] \"ResultAnalyticalMethod.MethodIdentifier\" #> [55] \"ResultAnalyticalMethod.MethodIdentifierContext\" #> [56] \"ResultAnalyticalMethod.MethodName\" #> [57] \"MethodDescriptionText\" #> [58] \"LaboratoryName\" #> [59] \"AnalysisStartDate\" #> [60] \"ResultLaboratoryCommentText\" #> [61] \"DetectionQuantitationLimitTypeName\" #> [62] \"DetectionQuantitationLimitMeasure.MeasureValue\" #> [63] \"DetectionLimitMeasureValue.Original\" #> [64] \"TADA.DetectionLimitMeasureValue.Flag\" #> [65] \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" #> [66] \"PreparationStartDate\" #> [67] \"ProviderName\" #> [68] \"timeZoneStart\" #> [69] \"timeZoneEnd\" #> [70] \"ActivityStartDateTime\" #> [71] \"ActivityEndDateTime\" #> [72] \"MonitoringLocationName\" #> [73] \"MonitoringLocationTypeName\" #> [74] \"MonitoringLocationDescriptionText\" #> [75] \"HUCEightDigitCode\" #> [76] \"DrainageAreaMeasure.MeasureValue\" #> [77] \"DrainageAreaMeasure.MeasureUnitCode\" #> [78] \"ContributingDrainageAreaMeasure.MeasureValue\" #> [79] \"ContributingDrainageAreaMeasure.MeasureUnitCode\" #> [80] \"LatitudeMeasure\" #> [81] \"LongitudeMeasure\" #> [82] \"SourceMapScaleNumeric\" #> [83] \"HorizontalAccuracyMeasure.MeasureValue\" #> [84] \"HorizontalAccuracyMeasure.MeasureUnitCode\" #> [85] \"HorizontalCollectionMethodName\" #> [86] \"HorizontalCoordinateReferenceSystemDatumName\" #> [87] \"VerticalMeasure.MeasureValue\" #> [88] \"VerticalMeasure.MeasureUnitCode\" #> [89] \"VerticalAccuracyMeasure.MeasureValue\" #> [90] \"VerticalAccuracyMeasure.MeasureUnitCode\" #> [91] \"VerticalCollectionMethodName\" #> [92] \"VerticalCoordinateReferenceSystemDatumName\" #> [93] \"CountryCode\" #> [94] \"StateCode\" #> [95] \"CountyCode\" #> [96] \"AquiferName\" #> [97] \"LocalAqfrName\" #> [98] \"FormationTypeText\" #> [99] \"AquiferTypeName\" #> [100] \"ConstructionDateText\" #> [101] \"WellDepthMeasure.MeasureValue\" #> [102] \"WellDepthMeasure.MeasureUnitCode\" #> [103] \"WellHoleDepthMeasure.MeasureValue\" #> [104] \"WellHoleDepthMeasure.MeasureUnitCode\" #> [105] \"MethodSpecificationName\" #> [106] \"ProjectName\" #> [107] \"ProjectDescriptionText\" #> [108] \"SamplingDesignTypeCode\" #> [109] \"QAPPApprovedIndicator\" #> [110] \"QAPPApprovalAgencyName\" #> [111] \"ProjectFileUrl\" #> [112] \"ProjectMonitoringLocationWeightingUrl\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"depth-unit-conversions","dir":"Articles","previous_headings":"","what":"Depth unit conversions","title":"WQP Data Harmonization","text":"Converts depth units consistent unit. ActivityDepthHeightMeasure.MeasureValue provides depth information. crucial column lake data less often river data. Function checks dataset depth profile data. depth profile columns populated, function appends ‘Conversion Factor’ columns populates columns based original unit (MeasureUnitCode columns) target unit, defined ‘unit’ argument. ‘Depth Target Unit’ column also appended, indicating unit selected depth data converted . transform = FALSE, output includes ‘Conversion Factor’ columns ‘Depth Target Unit’ column. transform = TRUE, output includes converted depth data ‘Depth Target Unit’ column, acts flag indicating rows converted. Default transform = TRUE. depth profile function can harmonize depth units across following fields (specific one): “ActivityDepthHeightMeasure”, “ActivityTopDepthHeightMeasure”, “ActivityBottomDepthHeightMeasure”, “ResultDepthHeightMeasure”). default . Allowable values ‘unit’ either ‘m’ (meter), ‘ft’ (feet), ‘’ (inch). ‘unit’ accepts one allowable value input. Default unit = “m”. See additional function documentation additional function options entering following code console: ?DepthProfileData","code":"#converts all depth profile data to meters TADAProfileClean1 <- DepthProfileData(TADAProfile, unit = \"m\", transform = TRUE) #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables #> Warning in `[<-.data.frame`(`*tmp*`, targetUnit, value = structure(list(: #> provided 2 variables to replace 1 variables"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"result-unit-conversions","dir":"Articles","previous_headings":"","what":"Result unit conversions","title":"WQP Data Harmonization","text":"Converts results WQX target units. WQX target units pulled MeasureUnit domain table: https://cdx.epa.gov/wqx/download/DomainValues/MeasureUnit.CSV See additional function documentation additional function options entering following code console: ?WQXTargetUnits","code":"#Converts all results to WQX target units TADAProfileClean2 <- WQXTargetUnits(TADAProfileClean1, transform = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"statistically-aggregated-data","dir":"Articles","previous_headings":"","what":"Statistically aggregated data","title":"WQP Data Harmonization","text":"Checks removes statistically aggregated high frequency (.e., continuous) data, present. Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = “Reported Raw Data (attached)” clean = TRUE, rows aggregated continuous data removed dataset column appended Default clean = TRUE See function documentation additional function options entering following code console: ?DepthProfileData","code":"TADAProfileClean3 <- AggregatedContinuousData(TADAProfileClean2, clean = TRUE) #> [1] \"The dataset does not contain aggregated continuous data.\""},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-qaqc-service-result-flags","dir":"Articles","previous_headings":"","what":"WQX QAQC Service Result Flags","title":"WQP Data Harmonization","text":"Run following result functions address invalid method, fraction, speciation, unit metadata characteristic. default clean = TRUE, remove invalid results. can change clean = FALSE flag results, remove . See documentation details: ?InvalidMethod Clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidSpeciation clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidResultUnit clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended. ?InvalidFraction clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either “Nonstandardized”, “Invalid”, “Valid”. clean = TRUE, “Invalid” rows removed dataset column appended.","code":"TADAProfileClean4 <- InvalidMethod(TADAProfileClean3, clean = TRUE) #> [1] \"No changes were made, because we did not find any invalid method/characteristic combinations in your dataset.\" TADAProfileClean5 <- InvalidFraction(TADAProfileClean4, clean = TRUE) #> [1] \"All data is valid, therefore the function cannot be applied.\" TADAProfileClean6 <- InvalidSpeciation(TADAProfileClean5, clean = FALSE) TADAProfileClean7 <- InvalidResultUnit(TADAProfileClean6, clean = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"wqx-national-upper-and-lower-thresholds","dir":"Articles","previous_headings":"","what":"WQX national upper and lower thresholds","title":"WQP Data Harmonization","text":"Run following code flag remove results national upper lower bound characteristic unit combination. See documentation details: ?AboveNationalWQXUpperThreshold clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset. ?BelowNationalWQXUpperThreshold clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset. default clean=TRUE, can change flag results desired. Results flagged, removed, clean=FALSE.","code":"TADAProfileClean8 <- AboveNationalWQXUpperThreshold(TADAProfileClean7, clean = TRUE) TADAProfileClean9 <- BelowNationalWQXUpperThreshold(TADAProfileClean8, clean = TRUE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"potential-duplicates","dir":"Articles","previous_headings":"","what":"Potential duplicates","title":"WQP Data Harmonization","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. information, review documentation entering following console: ?PotentialDuplicateRowID clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":"TADAProfileClean10 <- PotentialDuplicateRowID(TADAProfileClean9)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"invalid-coordinates","dir":"Articles","previous_headings":"","what":"Invalid coordinates","title":"WQP Data Harmonization","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled “TADA.InvalidCoordinates” following flags (relevant dataset). latitude less zero, row flagged “LAT_OutsideUSA”. longitude greater zero less 145, row flagged “LONG_OutsideUSA”. latitude longitude contains string, “999”, row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged “Imprecise”.","code":"TADAProfileClean11 <- InvalidCoordinates(TADAProfileClean10, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"review-qapp-information","dir":"Articles","previous_headings":"","what":"Review QAPP information","title":"WQP Data Harmonization","text":"Check data approved QAPP function checks see information column “QAPPApprovedIndicator”. organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . field, Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. defaults remove rows data QAPPApprovedIndicator equals “N”. Users alternatively remove N’s NA’s using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function anything. Check see QAPP Doc Available function checks data submitted “ProjectFileUrl” column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":"TADAProfileClean12 <- QAPPapproved(TADAProfileClean11, clean = TRUE, cleanNA = FALSE) TADAProfileClean13 <- QAPPDocAvailable(TADAProfileClean12, clean = FALSE) #> Warning in QAPPDocAvailable(TADAProfileClean12, clean = FALSE): The dataset does #> not contain QAPP document url data."},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field","dir":"Articles","previous_headings":"","what":"Filter data by field","title":"WQP Data Harmonization","text":"section TADA user want review unique values specific fields may choose remove data particular values. start, review list fields number unique values field. Next, choose field list see unique values field, well number times value appears dataset. ’ll start ActivityTypeCode. list fields review: ResultCommentText often details relating additional QA. MeasureQualifierCode Contains information data flags 3. codes may designate suspect data flags may described detail ResultLaboratoryCommentText another column ActivityTypeCode field four unique values – “Sample-Routine”, “Quality Control Sample-Field Replicate”, “Field Msr/Obs”, “Quality Control Sample-Field Blank.” example want remove quality control values ActivityTypeCode field, therefore, ’ll specify want remove “Quality Control Sample-Field Replicate” “Quality Control Sample-Field Blank” values ActivityTypeCode field. ’ve completed review ActivityTypeCode field. Let’s move different field see values want remove – ’ll look values ResultStatusIdentifier field. ActivityMediaSubdivisionName field two unique values, “Surface Water” “Groundwater.” example want remove “Groundwater” values.","code":"FilterFields(TADAProfileClean13) #> FieldName Count #> 1 OrganizationFormalName 7 #> 2 ActivityTypeCode 7 #> 3 ActivityMediaName 1 #> 4 ActivityMediaSubdivisionName 4 #> 5 ActivityCommentText 4 #> 6 HydrologicCondition 8 #> 7 HydrologicEvent 4 #> 8 CharacteristicName 3 #> 9 MeasureQualifierCode 4 #> 10 SampleTissueAnatomyName 1 #> 11 LaboratoryName 11 #> 12 DetectionQuantitationLimitTypeName 7 #> 13 MonitoringLocationTypeName 14 #> 14 ProjectName 8 FilterFieldReview(\"ActivityTypeCode\", TADAProfileClean13) #> FieldValue Count #> 7 Sample-Routine 5268 #> 6 Sample-Integrated Vertical Profile 474 #> 4 Quality Control Sample-Field Replicate 454 #> 2 Quality Control Sample-Equipment Blank 276 #> 3 Quality Control Sample-Field Blank 60 #> 1 Field Msr/Obs 4 #> 5 Quality Control Sample-Lab Duplicate 2 TADAProfileClean14 <- dplyr::filter(TADAProfileClean13, !(ActivityTypeCode %in% c(\"Quality Control Sample-Field Replicate\", \"Quality Control Sample-Field Blank\", \"Quality Control Sample-Lab Duplicate\", \"Quality Control Sample-Equipment Blank\"))) FilterFieldReview(\"ActivityMediaSubdivisionName\", TADAProfileClean14) #> FieldValue Count #> 3 Surface Water 687 #> 2 Groundwater 106 #> 1 Bulk deposition 1 TADAProfileClean15 <- dplyr::filter(TADAProfileClean14, !(ActivityMediaSubdivisionName %in% c(\"Groundwater\", \"Bulk deposition\")))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"filter-data-by-field-subset-by-parameter","dir":"Articles","previous_headings":"","what":"Filter data by field, subset by parameter","title":"WQP Data Harmonization","text":"section TADA user want select parameter, review unique values associated parameter specific fields, choose remove particular values. start, review list parameters dataset. (list sorted highest lowest counts. first rows displayed save space page) Next, select parameter. Let’s explore fields associated Nitrogen: Selecting parameter generates list , subset selected parameter, fields number unique values field. choose field list. example ’ll remove certain values HydrologicEvent field. HydrologicEvent field three unique values. example want remove samples collected “Storm” events. Therefore, ’ll specify want remove rows CharacteristicName “NITROGEN” HydrologicEvent field “Storm.”","code":"FilterParList(TADAProfileClean15) #> FieldValue Count #> 3 NITROGEN 4130 #> 2 NITRATE 1479 #> 1 AMMONIA 30 FilterParFields(TADAProfileClean15, \"NITROGEN\") #> FieldName Count #> 1 ActivityTypeCode 2 #> 2 ActivityMediaName 1 #> 3 ActivityMediaSubdivisionName 2 #> 4 ActivityCommentText 3 #> 5 HydrologicCondition 7 #> 6 HydrologicEvent 2 #> 7 SampleCollectionMethod.MethodIdentifier 6 #> 8 SampleCollectionMethod.MethodIdentifierContext 2 #> 9 SampleCollectionMethod.MethodName 6 #> 10 SampleCollectionEquipmentName 6 #> 11 ResultSampleFractionText 3 #> 12 ResultMeasure.MeasureUnitCode 2 #> 13 MeasureQualifierCode 3 #> 14 ResultStatusIdentifier 2 #> 15 ResultValueTypeName 1 #> 16 ResultWeightBasisText 1 #> 17 ResultTemperatureBasisText 1 #> 18 ResultParticleSizeBasisText 1 #> 19 ResultCommentText 7 #> 20 ResultAnalyticalMethod.MethodIdentifier 2 #> 21 ResultAnalyticalMethod.MethodIdentifierContext 2 #> 22 ResultAnalyticalMethod.MethodName 2 #> 23 MethodDescriptionText 1 #> 24 LaboratoryName 2 #> 25 ResultLaboratoryCommentText 5 #> 26 DetectionQuantitationLimitTypeName 2 #> 27 MonitoringLocationTypeName 11 FilterParFieldReview(\"HydrologicEvent\", TADAProfileClean15, \"NITROGEN\") #> FieldValue Count #> 1 Routine sample 59 TADAProfileClean16 <- dplyr::filter(TADAProfileClean15, !(CharacteristicName %in% \"NITROGEN\" & HydrologicEvent %in% \"Storm\"))"},{"path":"usepa.github.io/tada/articles/WQPDataHarmonization.html","id":"transform-characteristic-speciation-and-unit-values-to-tada-standards","dir":"Articles","previous_headings":"","what":"Transform Characteristic, Speciation, and Unit values to TADA Standards","title":"WQP Data Harmonization","text":"HarmonizeRefTable function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values following elements: CharacteristicName ResultSampleFractionText MethodSpecicationName ResultMeasure.MeasureUnitCode HarmonizeData function compares input dataset TADA Harmonization Reference Table. purpose function make similar data consistent therefore easier compare analyze. Users can also edit reference file meet needs desired. download argument can used save harmonization file current working directory download = TRUE, default download = FALSE. Optional outputs include: dataset Harmonization columns appended, dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE. examples HarmonizeData function can used: ResultSampleFractionText specifies forms constituents. cases, single CharacteristicName “Total” “Dissolved” forms specified, combined. cases, CharacteristicName ResultSampleFractionText combination given different identifier. identifier can used later identify comparable data groups calculating statistics creating figures combination. variables different names represent constituent (e.g., “Total Kjeldahl nitrogen (Organic N & NH3)” “Kjeldahl nitrogen”). HarmonizeData function gives consistent name (identifier) synonyms.","code":"UniqueHarmonizationRef <- HarmonizationRefTable(TADAProfileClean16, download = FALSE) TADAProfileClean17 <- HarmonizeData(TADAProfileClean16, ref = UniqueHarmonizationRef, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Cristina Mullin. Author, maintainer. Michelle Thawley. Author. Laura Shumway. Author. Jacob Greif. Author.","code":""},{"path":"usepa.github.io/tada/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Mullin, C.., Greif, J., Thawley, M., Shumway, L., 2022, TADA: R Tools Automated Data Assessment, U.S. Environmental Protection Agency, Washington, DC","code":"@Manual{, author = {Cristina A. Mullin and Jacob Greif and Michelle Thawley and Laura Shumway}, title = {TADA: R Tools for Automated Data Assessment}, address = {Washington, DC}, institution = {U.S. Environmental Protection Agency}, year = {2022}, url = {https://github.com/USEPA/TADA}, }"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"package-development","dir":"","previous_headings":"","what":"Package Development","title":"NA","text":"article walk contribute TADA package. use git-forking workflow, full git tutorial. also complete guide R package development (comprehensive guide R Packages), instead meant checklist general steps. Several references included bottom information R-package development git workflows.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"what-is-github","dir":"","previous_headings":"","what":"What is GitHub?","title":"NA","text":"GitHub third-party website offers version-controlled repositories developers scientists can use collaborate projects (e.g., software, text, manuscripts, etc.) real-time. GitHub also provides social networking features allow developers follow open-source projects, share code learn code changes made throughout development process. GitHub named utilizes open-source version control system (VCS) known Git. Setting Git Git Basics Comprehensive Guide: Happy Git GitHub useR","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"required-installations","dir":"","previous_headings":"","what":"Required Installations","title":"NA","text":"several programs needed work can begin. admin access computer, can install , otherwise create ticket group following requests. links provided assume Windows computer. Adjustments might needed Mac Linux OS: R RStudio Rtools Git installed, following R packages needed R-package development work:","code":"install.packages(c(\"devtools\", \"rmarkdown\"))"},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"NA","text":"see error feedback, best way let us know file issue. Issues labeled help indicate . example, using “Good First Issue” indicate issues good first pickings first contribution open-source project. Pull requests can directly linked specific issue. linked, Repository Administrators can easily review pull request issue time contributor submits pull request. issue can closed pull request merged.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"branches","dir":"","previous_headings":"","what":"Branches","title":"NA","text":"new development currently happens develop branch. contribute specific change new code, outside contributors can fork repo develop branch. Contributors work personal fork one specific “task” time. complete, submit pull request request changes merged TADA develop branch. Contributors submit separate pull request “task”. “Tasks” small scope. example, may pertain bug fix update relevant single function. single “task” may also encompass changes made across many functions needed. Another example single “task” make changes documentation improve clarity, example. Furthermore, task may include developing new function, series related functions. cases, tasks can also synonymous issues, pull requests can directly linked specific issue (case, Repository Administrators review pull request issue time issue can closed pull request merged). Complete pull request detailing fixes contributions, tagging TADA repo admins review work. package, please tag cristinamullin (Cristina Mullin) mthawley (Shelly Thawley). Repository Administrators review code contributions external collaborators integrate code commits source code. done ensure code stability consistency prevent degradation code performance. review, admin either accept submission, recommend specific improvements submission, cases reject submission. avoid issues, developers contributing code contact repository admins (Cristina ) early development process maintain contact throughout help ensure submission compatible code base robust addition.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"additional-references","dir":"","previous_headings":"","what":"Additional References","title":"NA","text":"R Packages testthat R markdown","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/CONTRIBUTING.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/index.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"Tools for Automated Data Assessment R Package","text":"encourage read package’s CONTRIBUTING, LICENSE, README files (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/index.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"Tools for Automated Data Assessment R Package","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Tools for Automated Data Assessment R Package","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/index.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"Tools for Automated Data Assessment R Package","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Tools for Automated Data Assessment R Package","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/index.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"Tools for Automated Data Assessment R Package","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Tools for Automated Data Assessment R Package","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":[]},{"path":"usepa.github.io/tada/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"CC0 1.0 Universal","title":"CC0 1.0 Universal","text":"CREATIVE COMMONS CORPORATION LAW FIRM PROVIDE LEGAL SERVICES. DISTRIBUTION DOCUMENT CREATE ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES INFORMATION “-” BASIS. CREATIVE COMMONS MAKES WARRANTIES REGARDING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER, DISCLAIMS LIABILITY DAMAGES RESULTING USE DOCUMENT INFORMATION WORKS PROVIDED HEREUNDER.","code":""},{"path":"usepa.github.io/tada/LICENSE.html","id":"statement-of-purpose","dir":"","previous_headings":"","what":"Statement of Purpose","title":"CC0 1.0 Universal","text":"laws jurisdictions throughout world automatically confer exclusive Copyright Related Rights (defined ) upon creator subsequent owner(s) (, “owner”) original work authorship /database (, “Work”). Certain owners wish permanently relinquish rights Work purpose contributing commons creative, cultural scientific works (“Commons”) public can reliably without fear later claims infringement build upon, modify, incorporate works, reuse redistribute freely possible form whatsoever purposes, including without limitation commercial purposes. owners may contribute Commons promote ideal free culture production creative, cultural scientific works, gain reputation greater distribution Work part use efforts others. /purposes motivations, without expectation additional consideration compensation, person associating CC0 Work (“Affirmer”), extent owner Copyright Related Rights Work, voluntarily elects apply CC0 Work publicly distribute Work terms, knowledge Copyright Related Rights Work meaning intended legal effect CC0 rights. Copyright Related Rights. Work made available CC0 may protected copyright related neighboring rights (“Copyright Related Rights”). 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Affirmer disclaims responsibility clearing rights persons may apply Work use thereof, including without limitation person’s Copyright Related Rights Work. , Affirmer disclaims responsibility obtaining necessary consents, permissions rights required use Work. Affirmer understands acknowledges Creative Commons party document duty obligation respect CC0 use Work.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"welcome-to-tada","dir":"","previous_headings":"","what":"Welcome to TADA!","title":"NA","text":"encourage read package’s CONTRIBUTING, LICENSE, README files (). TADA draft R package developed help States, Tribes, Tribal Nations, Pueblos, stakeholders efficiently compile evaluate Water Quality Portal (WQP) data collected surface water monitoring sites. TADA building block support future development TADA R Shiny application. encourage stakeholders test functionality provide feedback. Moreover, open source software provides avenue water quality data originators users develop share code, welcome contributions! information contribute can found CONTRIBUTING file. file explains users can contribute R package submitting issue, requesting change, submitting inquiry. hope build collaborative community dedicated effort contributors can discover, share build package functionality time.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"water-quality-portal","dir":"","previous_headings":"","what":"Water Quality Portal","title":"NA","text":"2012, WQP deployed U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (USEPA), National Water Quality Monitoring Council combine serve water-quality data numerous sources standardized format. WQP holds 420 million water quality sample results 1000 federal, state, tribal partners, nation’s largest source single point access water-quality data. Participating organizations submit data WQP using EPA’s Water Quality Exchange (WQX), framework designed map data holdings common data structure.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"NA","text":"can install load recent version TADA R Package GitHub running:","code":"library (remotes) remotes::install_github(\"USEPA/TADA\")"},{"path":"usepa.github.io/tada/readme.html","id":"open-source-code-policy","dir":"","previous_headings":"","what":"Open-Source Code Policy","title":"NA","text":"Effective August 8, 2016, OMB Mandate: M-16-21; Federal Source Code Policy: Achieving Efficiency, Transparency, Innovation Reusable Open Source Software applies new custom-developed code created procured EPA consistent scope applicability requirements Office Management Budget’s (OMB’s) Federal Source Code Policy. general, states new custom-developed code Federal Agencies made available reusable open-source code. EPA specific implementation OMB Mandate M-16-21 addressed System Life Cycle Management Procedure. EPA chosen use GitHub version control system well inventory open-source code projects. EPA uses GitHub inventory custom-developed, open-source code generate necessary metadata file posted code.gov broad reuse compliance OMB Mandate M-16-21. questions want read , check EPA Open Source Project Repo EPA’s Interim Open Source Code Guidance.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"license","dir":"","previous_headings":"","what":"License","title":"NA","text":"contributions project released CCO-1.0 license file dedication. submitting pull request issue, agreeing comply waiver copyright interest.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"NA","text":"United States Environmental Protection Agency (EPA) GitHub project code provided “” basis user assumes responsibility use. EPA relinquished control information longer responsibility protect integrity, confidentiality, availability information. reference specific commercial products, processes, services service mark, trademark, manufacturer, otherwise, constitute imply endorsement, recommendation favoring EPA. EPA seal logo shall used manner imply endorsement commercial product activity EPA United States Government.","code":""},{"path":"usepa.github.io/tada/readme.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"NA","text":"questions, please reach Cristina Mullin (mullin.cristina@epa.gov).","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data upper threshold result values submitted WQX given characteristic. clean = TRUE, rows values upper WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"","code":"AboveNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data upper WQX threshold dataset clean = TRUE. Default clean = TRUE","code":""},{"path":"usepa.github.io/tada/reference/AboveNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Upper Threshold — AboveNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: AboveWQXUpperThreshold. column flags rows data upper WQX threshold. clean = TRUE, data upper WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Aggregated Continuous Data — AggregatedContinuousData","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"Water Quality Portal (WQP) designed store high-frequency sensor data. However, sometimes data providers choose aggregate continuous data submit WQP one value. type data may suitable integration discrete water quality data assessments. Therefore, function uses metadata submitted data providers flags rows aggregated continuous data. done flagging results ResultDetectionConditionText = \"Reported Raw Data (attached)\". clean = TRUE, rows aggregated continuous data removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"","code":"AggregatedContinuousData(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":".data TADA dataframe clean Boolean argument; removes aggregated continuous data dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/AggregatedContinuousData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Aggregated Continuous Data — AggregatedContinuousData","text":"clean = FALSE, column flagging rows aggregated continuous data appended input data set. clean = TRUE, aggregated continuous data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — autoclean","title":"autoclean — autoclean","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — autoclean","text":"","code":"autoclean(.data)"},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — autoclean","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — autoclean","text":"autocleaned TADA data profile","code":""},{"path":"usepa.github.io/tada/reference/autoclean.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — autoclean","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":null,"dir":"Reference","previous_headings":"","what":"AutoFilter — AutoFilter","title":"AutoFilter — AutoFilter","text":"Function can used autofilter simplify WQP dataset. applying function, dataset contain result values water media types chemicals tissue (e.g. mercury fish tissue). complex biological data (counts macroinvertebrates) removed. function looks following fields autofilter: ActivityMediaName, ActivityMediaSubDivisionName, AssemblageSampledName","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"AutoFilter — AutoFilter","text":"","code":"AutoFilter(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"AutoFilter — AutoFilter","text":".data TADA dataframe clean Indicates whether flag columns appended data (clean = FALSE), flagged data transformed/filtered dataset columns appended (clean = TRUE).","code":""},{"path":"usepa.github.io/tada/reference/AutoFilter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"AutoFilter — AutoFilter","text":"clean = FALSE, flag column appended dataset. clean = TRUE, flag column appended relevant rows removed.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"EPA's Water Quality Exchange (WQX) generated statistics data millions water quality data points around country. functions leverages statistical data WQX flag data lower threshold result values submitted WQX given characteristic. clean = TRUE, rows values lower WQX threshold removed dataset column appended. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"","code":"BelowNationalWQXUpperThreshold(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":".data TADA dataframe clean Boolean argument; removes data lower WQX threshold dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/BelowNationalWQXUpperThreshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Value Against WQX Lower Threshold — BelowNationalWQXUpperThreshold","text":"clean = FALSE, following column added dataset: BelowWQXUpperThreshold. column flags rows data lower WQX threshold. clean = TRUE, data lower WQX threshold removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalnumcount — decimalnumcount","title":"decimalnumcount — decimalnumcount","text":"character data type","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalnumcount — decimalnumcount","text":"","code":"decimalnumcount(x)"},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalnumcount — decimalnumcount","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalnumcount.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalnumcount — decimalnumcount","text":"Number values right decimal point character type data.","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":null,"dir":"Reference","previous_headings":"","what":"decimalplaces — decimalplaces","title":"decimalplaces — decimalplaces","text":"numeric data type","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"decimalplaces — decimalplaces","text":"","code":"decimalplaces(x)"},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"decimalplaces — decimalplaces","text":"x Numeric data field TADA profile","code":""},{"path":"usepa.github.io/tada/reference/decimalplaces.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"decimalplaces — decimalplaces","text":"Number values right decimal point numeric type data.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":null,"dir":"Reference","previous_headings":"","what":"Depth Profile Flag & Unit Conversion — DepthProfileData","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Function checks dataset depth profile data. depth profile columns populated, function appends 'Conversion.Factor' columns populates columns based original unit (MeasureUnitCode columns) target unit, defined 'unit' argument. 'WQX.Depth.TargetUnit' column also appended, indicating unit selected depth data converted . transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"","code":"DepthProfileData( .data, unit = \"m\", fields = c(\"ActivityDepthHeightMeasure\", \"ActivityTopDepthHeightMeasure\", \"ActivityBottomDepthHeightMeasure\", \"ResultDepthHeightMeasure\"), transform = TRUE )"},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":".data TADA dataframe unit Character string input indicating uniform unit depth data converted . Allowable values 'unit' either 'm' (meter), 'ft' (feet), '' (inch). 'unit' accepts one allowable value input. Default unit = \"m\". fields Character string input indicating depth fields checked data. Allowable values 'fields' 'ActivityDepthHeightMeasure,' 'ActivityTopDepthHeightMeasure,' 'ActivityBottomDepthHeightMeasure,' 'ResultDepthHeightMeasure.'. Default include allowable values. transform Boolean argument; transform = FALSE, output includes 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column. transform = TRUE, output includes converted depth data 'Depth Target Unit' column, acts flag indicating rows converted. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/DepthProfileData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Depth Profile Flag & Unit Conversion — DepthProfileData","text":"Full dataset converted uniform depth units 'WQX.Depth.TargetUnit' column, acts flag indicating rows converted. transform = FALSE, output full dataset 'Conversion.Factor' columns 'WQX.Depth.TargetUnit' column.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field — FilterFieldReview","title":"Generate list of unique values in a given field — FilterFieldReview","text":"Function creates table pie chart unique values, counts values chosen field dataframe.","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field — FilterFieldReview","text":"","code":"FilterFieldReview(field, .data)"},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field — FilterFieldReview","text":"field Field name .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field — FilterFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names — FilterFields","title":"Generate list of field names — FilterFields","text":"Function creates list fields input dataframe well number unique values field. list intended inform users specific fields explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names — FilterFields","text":"","code":"FilterFields(.data)"},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names — FilterFields","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names — FilterFields","text":"table fields count unique values field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"Function creates table pie chart unique values, counts values, chosen field dataframe subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"","code":"FilterParFieldReview(field, .data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"field Field name .data Optional argument; TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFieldReview.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of unique values in a given field subset by parameter — FilterParFieldReview","text":"table pie chart unique values selected field.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of field names subset by parameter — FilterParFields","title":"Generate list of field names subset by parameter — FilterParFields","text":"Function subsets input dataframe input parameter creates list fields subset dataframe well number unique values field. list intended inform users specific fields explore filter subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of field names subset by parameter — FilterParFields","text":"","code":"FilterParFields(.data, parameter)"},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of field names subset by parameter — FilterParFields","text":".data TADA dataframe parameter Characteristic name (parameter name) dataset.","code":""},{"path":"usepa.github.io/tada/reference/FilterParFields.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of field names subset by parameter — FilterParFields","text":"table fields count unique values field, subset parameter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate list of parameters — FilterParList","title":"Generate list of parameters — FilterParList","text":"Function generates list characteristics input dataset, well number records . list intended inform users parameters explore filter.","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate list of parameters — FilterParList","text":"","code":"FilterParList(.data)"},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate list of parameters — FilterParList","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/FilterParList.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate list of parameters — FilterParList","text":"list unique characteristics counts","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":null,"dir":"Reference","previous_headings":"","what":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Function summarizes censored data dataset, including substitutions made.","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"","code":"GenerateCensoredDataStats(.data)"},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":".data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/GenerateCensoredDataStats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function summarizes censored data in dataset, including any substitutions made. — GenerateCensoredDataStats","text":"Summary table","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table — GetMeasureUnitRef","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"Function downloads returns latest WQX MeasureUnit Domain table, adds additional target unit information, writes data sysdata.rda.","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"","code":"GetMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"sysdata.rda updated WQXunitRef object (unit conversion reference table)","code":""},{"path":"usepa.github.io/tada/reference/GetMeasureUnitRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Update Measure Unit Reference Table — GetMeasureUnitRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Function downloads returns newest available (cleaned) raw Water Quality Exchange (WQX) QAQC Characteristic Validation reference table. WQXcharValRef data frame contains information four functions: InvalidFraction, InvalidResultUnit, InvalidSpeciation, UncommonAnalyticalMethodID.","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"","code":"GetWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"Updated sysdata.rda updated WQXcharValRef object","code":""},{"path":"usepa.github.io/tada/reference/GetWQXCharValRef.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"WQX QAQC Characteristic Validation Reference Table — GetWQXCharValRef","text":"function caches table called subsequent calls faster.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Function generates harmonization reference table specific input dataset. Users can review input data relates standard TADA values CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode can optionally edit reference file meet needs.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"","code":"HarmonizationRefTable(.data, download = FALSE)"},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":".data TADA dataframe download Boolean argument; download = TRUE, output downloaded current working directory.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizationRefTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate Unique Harmonization Reference Table — HarmonizationRefTable","text":"Harmonization Reference Table unique input dataset","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"Function compares input dataset TADA Harmonization Reference Table, makes synonymous data consistent. Optional outputs include: 1) dataset Harmonization columns appended, 2) dataset CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode converted TADA standards 3) four fields converted Harmonization Reference Table columns appended. Default transform = TRUE flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"","code":"HarmonizeData(.data, ref, transform = TRUE, flag = TRUE)"},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":".data TADA dataframe ref Optional argument specify dataframe use reference file. primary use argument user generated harmonization reference file unique data, made changes file. transform Boolean argument; transforms /converts original values dataset TADA Harmonization Reference Table values following fields: CharacteristicName, ResultSampleFractionText, MethodSpecificationName, ResultMeasure.MeasureUnitCode. Default transform = TRUE. flag Boolean argument; appends columns TADA Harmonization Reference Table dataframe. Default flag = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/HarmonizeData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform CharacteristicName, ResultSampleFractionText, MethodSpecificationName,\r\nand ResultMeasure.MeasureUnitCode values to TADA standards. — HarmonizeData","text":"transform = FALSE flag = TRUE, Harmonization Reference Table columns appended dataset . transform = TRUE flag = TRUE, Harmonization columns appended dataset transformations executed. transform = TRUE flag = FALSE, transformations executed . transform = FALSE flag = FALSE, error returned (function return input dataframe unchanged input allowed).","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":null,"dir":"Reference","previous_headings":"","what":"Invalid coordinates — InvalidCoordinates","title":"Invalid coordinates — InvalidCoordinates","text":"Function identifies flags invalid coordinate data. clean_outsideUSA = FALSE clean_imprecise = FALSE, column appended titled \"TADA.InvalidCoordinates\" following flags (relevant dataset). latitude less zero, row flagged \"LAT_OutsideUSA\". longitude greater zero less 145, row flagged \"LONG_OutsideUSA\". latitude longitude contains string, \"999\", row flagged invalid. Finally, precision can measured number decimal places latitude longitude provided. either numbers right decimal point, row flagged \"Imprecise\".","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Invalid coordinates — InvalidCoordinates","text":"","code":"InvalidCoordinates(.data, clean_outsideUSA = FALSE, clean_imprecise = FALSE)"},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Invalid coordinates — InvalidCoordinates","text":".data TADA dataframe clean_outsideUSA Boolean argument; removes data coordinates outside United States clean_outsideUSA = TRUE. Default clean = FALSE. clean_imprecise Boolean arguments; removes imprecise data clean_imprecise = TRUE. Default clean_imprecise = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidCoordinates.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Invalid coordinates — InvalidCoordinates","text":"either clean_outsideUSA clean_imprecise argument FALSE, column flagging rows respective QA check appended input dataset. either argument TRUE, \"invalid\" \"imprecise\" data removed, respectively.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Sample Fraction Validity — InvalidFraction","title":"Check Sample Fraction Validity — InvalidFraction","text":"Function checks validity characteristic-fraction combination dataset. clean = TRUE, rows invalid characteristic-fraction combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Sample Fraction Validity — InvalidFraction","text":"","code":"InvalidFraction(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Sample Fraction Validity — InvalidFraction","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-fraction combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidFraction.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Sample Fraction Validity — InvalidFraction","text":"clean = FALSE, function adds following column dataframe: WQX.SampleFractionValidity. column flags CharacteristicName ResultSampleFractionText combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Invalid Analytical Methods — InvalidMethod","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"Function checks validity characteristic-analytical method combination dataset. clean = TRUE, rows invalid characteristic-analytical method combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"","code":"InvalidMethod(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Invalid Analytical Methods — InvalidMethod","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-analytical method combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidMethod.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Invalid Analytical Methods — InvalidMethod","text":"clean = FALSE, function adds following column dataframe: WQX.AnalyticalMethodValidity. column flags invalid CharacteristicName, ResultAnalyticalMethod/MethodIdentifier, ResultAnalyticalMethod/MethodIdentifierContext combinations dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Result Unit Validity — InvalidResultUnit","title":"Check Result Unit Validity — InvalidResultUnit","text":"Function checks validity characteristic-media-result unit combination dataset. clean = TRUE, rows invalid characteristic-media-result unit combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Result Unit Validity — InvalidResultUnit","text":"","code":"InvalidResultUnit(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Result Unit Validity — InvalidResultUnit","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-media-result unit combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidResultUnit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Result Unit Validity — InvalidResultUnit","text":"clean = FALSE, following column added dataset: WQX.ResultUnitValidity. column flags CharacteristicName, ActivityMediaName, ResultMeasure/MeasureUnitCode combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":null,"dir":"Reference","previous_headings":"","what":"Check Method Speciation Validity — InvalidSpeciation","title":"Check Method Speciation Validity — InvalidSpeciation","text":"Function checks validity characteristic-method speciation combination dataset. clean = TRUE, rows invalid characteristic-method speciation combinations removed. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check Method Speciation Validity — InvalidSpeciation","text":"","code":"InvalidSpeciation(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check Method Speciation Validity — InvalidSpeciation","text":".data TADA dataframe clean Boolean argument; removes \"Invalid\" characteristic-method speciation combinations dataset clean = TRUE. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/InvalidSpeciation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check Method Speciation Validity — InvalidSpeciation","text":"#'clean = FALSE, function adds following column dataframe: WQX.MethodSpeciationValidity. column flags CharacteristicName MethodSpecificationName combination dataset either \"Nonstandardized\", \"Invalid\", \"Valid\". clean = TRUE, \"Invalid\" rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Function checks special characters non-numeric values ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields appends flag columns indicating special characters included , special characters . ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields also converted class numeric.","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"","code":"MeasureValueSpecialCharacters(.data)"},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":".data TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/MeasureValueSpecialCharacters.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Special Characters in Measure Value Fields — MeasureValueSpecialCharacters","text":"Full dataset column indicating presence special characters ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields. Additionally, ResultMeasureValue DetectionQuantitationLimitMeasure.MeasureValue fields converted class numeric, copies column created preserve original character values.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"usepa.github.io/tada/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"usepa.github.io/tada/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":null,"dir":"Reference","previous_headings":"","what":"Check for Potential Duplicates — PotentialDuplicateRowID","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"Sometimes multiple organizations submit exact data Water Quality Portal (WQP), can affect water quality analyses assessments. function checks identifies data identical fields excluding organization-specific comment text fields. pair group potential duplicate rows flagged unique ID. clean = TRUE, function retains first occurrence potential duplicate dataset. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"","code":"PotentialDuplicateRowID(.data, clean = TRUE)"},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":".data TADA dataframe clean Boolean argument; removes potential duplicate data dataset clean = TRUE. clean = FALSE, column indicating potential duplicate rows unique number linking rows appended input data set. Default clean = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/PotentialDuplicateRowID.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check for Potential Duplicates — PotentialDuplicateRowID","text":"clean = FALSE, following column added dataframe: TADA.PotentialDupRowID. column flags potential duplicate rows data dataset, assigns potential duplicate combination unique number linking two potential duplication rows. clean = FALSE first group potential duplicate rows removed dataset column appended.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":null,"dir":"Reference","previous_headings":"","what":"Check data for an approved QAPP — QAPPapproved","title":"Check data for an approved QAPP — QAPPapproved","text":"Function checks data submitted column \"QAPPApprovedIndicator\". organizations submit data field indicate data produced approved Quality Assurance Project Plan (QAPP) . Y indicates yes, N indicates . function two default inputs: clean = TRUE cleanNA = FALSE. default removes rows data QAPPApprovedIndicator equals \"N\". Users alternatively remove N's NA's using inputs clean = TRUE cleanNA = TRUE. clean = FALSE cleanNA = FALSE, function make changes data.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check data for an approved QAPP — QAPPapproved","text":"","code":"QAPPapproved(.data, clean = TRUE, cleanNA = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check data for an approved QAPP — QAPPapproved","text":".data TADA dataframe clean Boolean argument two possible values called \"TRUE\" \"FALSE\". clean=TRUE, rows data QAPPApprovedIndicator equals \"N\" removed. , clean=FALSE, rows data QAPPApprovedIndicator equals \"N\" retained. cleanNA Boolean argument two possible values called \"TRUE\" \"FALSE\". cleanNA=TRUE, rows data QAPPApprovedIndicator equals \"NA\" removed. , cleanNA=FALSE, rows data QAPPApprovedIndicator equals \"NA\" retained.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check data for an approved QAPP — QAPPapproved","text":"clean = FALSE cleanNA = FALSE, data removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/QAPPapproved.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check data for an approved QAPP — QAPPapproved","text":"Note: required field, often left blank (NA) even data associated QAPP. states tribes collect monitoring data using 106 funding (almost state tribal data WQX) required EPA approved QAPP receive 106 funding. Therefore, organizations data approved QAPP even data submitted WQP NA.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"Function checks data submitted \"ProjectFileUrl\" column determine QAPP document available review. clean = FALSE, column appended flag results associated QAPP document URL provided. clean = TRUE, rows associated QAPP document removed dataset column appended. function used remove data accompanying QAPP document required use data assessments.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"","code":"QAPPDocAvailable(.data, clean = FALSE)"},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":".data TADA dataframe clean Boolean argument; removes data without associated QAPP document dataset clean = TRUE. Default clean = FALSE.","code":""},{"path":"usepa.github.io/tada/reference/QAPPDocAvailable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if an approved QAPP document URL is provided — QAPPDocAvailable","text":"clean = FALSE, column appended input data set flags rows associated QAPP document. clean = TRUE, data without associated QAPP document removed dataset.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":null,"dir":"Reference","previous_headings":"","what":"Read in WQP data using WQP web services directly — readWQPwebservice","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Go WQP website (https://www.waterqualitydata.us/) fill advanced query form. Choose Full Physical Chemical Data Profile, data sources, file format Comma-Separated. finished, hit download button. Instead, copy web service URL located bottom page header \"Result\". Use \"Result\" web service URL input function download data directly R.","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"","code":"readWQPwebservice(webservice)"},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"webservice WQP Web Service URL, entered within quotes \"url\"","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"WQP Full Physical Chemical Results Data Profile","code":""},{"path":"usepa.github.io/tada/reference/readWQPwebservice.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read in WQP data using WQP web services directly — readWQPwebservice","text":"Note: may useful save Query URL well comment within code. URL return WQP query page original data filters.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"RemoveEmptyColumns — RemoveEmptyColumns","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Removes columns NA values. Used quickly reduce number columns dataframe improve management readability dataset.","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"","code":"RemoveEmptyColumns(.data)"},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":".data Dataframe","code":""},{"path":"usepa.github.io/tada/reference/RemoveEmptyColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"RemoveEmptyColumns — RemoveEmptyColumns","text":"Full dataset empty data columns removed","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"function multiple synchronous data calls WQP (waterqualitydata.us). uses WQP summary service limit amount downloaded relevant data, pulls back data 100 stations time joins data back together produces single TADA compatible dataframe output. large data sets, can save lot time ultimately reduce complexity subsequent data processing. Using function, able download data available sites contiguous United States available time period, characteristicName, siteType requested.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"TADABigdataRetrieval( startDate = \"null\", endDate = \"null\", characteristicName = \"null\", siteType = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"startDate Start Date YYYY-MM-DD format, example, \"1995-01-01\" endDate end date YYYY-MM-DD format, example, \"2020-12-31\" characteristicName Name water quality parameter siteType Name water body type (e.g., \"Stream\", \"Lake, Reservoir, Impoundment\")","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"Similarly TADAdataRetrieval function, function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADABigdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Large WQP data pulls using dataRetrieval — TADABigdataRetrieval","text":"","code":"if (FALSE) { tada2 <- TADABigdataRetrieval(startDate = \"01-01-2021\", endDate = \"01-01-2022\", characteristicName = \"Nitrogen\", siteType = \"Stream\") }"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Retrieve data Water Quality Portal (WQP) output TADA-compatible dataset.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"TADAdataRetrieval( statecode = \"null\", startDate = \"null\", countycode = \"null\", siteid = \"null\", siteType = \"null\", characteristicName = \"null\", ActivityMediaName = \"null\", endDate = \"null\" )"},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"statecode Code identifies state startDate Start Date countycode Code identifies county siteid Unique monitoring station identifier siteType Type waterbody characteristicName Name parameter ActivityMediaName Sampling substrate water, air, sediment endDate End Date","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"TADA-compatible dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"Keep mind query filters WQP work within fields ORs. example, characteristics – choose pH & – ’s . Similarly, choose VA IL, ’s . combo fields ANDs. State/VA Characteristic/\". \"Characteristic\" \"Characteristic Group\" also work . function create /edit following columns: TADA.DetectionLimitMeasureValue.Flag DetectionQuantitationLimitMeasure.MeasureValue DetectionLimitMeasureValue.Original ResultMeasureValue.Original TADA.ResultMeasureValue.Flag ResultMeasureValue data cleaning transformations done directly \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns, however original \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns values WQP preserved new fields, \"ResultMeasureValue.Original\" \"DetectionLimitMeasureValue.Original\". Additionally, \"TADA.ResultMeasureValue.Flag\" \"TADA.DetectionLimitMeasureValue.Flag\" created track changes made \"ResultMeasureValue\" \"DetectionLimitMeasureValue\" columns; provide information result values needed address censored data later (.e., nondetections) See ?MeasureValueSpecialCharacters ?autoclean documentation information.","code":""},{"path":"usepa.github.io/tada/reference/TADAdataRetrieval.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate TADA-Compatible Dataset with WQP Data — TADAdataRetrieval","text":"","code":"if (FALSE) { tada1 <- TADAdataRetrieval(statecode = \"WI\", countycode = \"Dane\", characteristicName = \"Phosphorus\") }"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":null,"dir":"Reference","previous_headings":"","what":"autoclean — TADAprofileCheck","title":"autoclean — TADAprofileCheck","text":"Removes complex biological data. Removes non-water media samples. Removes rows data true duplicates. Capitalizes fields harmonize data. function includes runs TADA \"MeasureValueSpecialCharacters\" function well.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"autoclean — TADAprofileCheck","text":"","code":"TADAprofileCheck(.data)"},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"autoclean — TADAprofileCheck","text":".data dataframe","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"autoclean — TADAprofileCheck","text":"cleaned TADA data profile TADA Profile Check function checks column names dataframe include TADA profile fields. used beginning TADA functions ensure input data frame suitable (.e. either full physical/chemical results profile downloaded WQP TADA profile template downloaded EPA TADA webpage.) Boolean result indicating whether input dataframe contains TADA profile fields.","code":""},{"path":"usepa.github.io/tada/reference/TADAprofileCheck.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"autoclean — TADAprofileCheck","text":"Within \"BiologicalIntentName\", allowable values \"tissue\", \"toxicity\", \"NA\" apply non-biological data (function removes others). Toxicity fish tissue data kept, types biological monitoring data . decided make fields uppercase way compatible WQX validation reference tables avoid issues case-sensitivity joining data. Therefore, might need tack immediate QA steps (removing true duplicates, converting result values numeric, capitalizing letters, etc.) function, well retrieval functions.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":null,"dir":"Reference","previous_headings":"","what":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"Function substitutes monitoring device/method detection limits (available) result values applicable.","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"","code":"TransformCensoredData(transform, .data)"},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE. .data Optional argument; TADA dataframe","code":""},{"path":"usepa.github.io/tada/reference/TransformCensoredData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Function substitutes monitoring device/method detection limits (if available) as result values when applicable. — TransformCensoredData","text":"transform=TRUE, monitoring device/method detection limits (available) substituted result values units. transform = FALSE, monitoring device/method detection limits (available) substituted result values units - Instead, columns appended rows may include censored data. flag indicates 1) row contains censored data, 2) monitoring device/method detection limits available.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Existing Data in sysdata.rda — UpdateInternalData","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Function internal use . used internal functions used update internal data (e.g. reference tables). function adapted stackoverflow.com thread, can accessed .","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"","code":"UpdateInternalData(..., list = character())"},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"... Objects updated sysdata.rda. list Argument indicating data class list.","code":""},{"path":"usepa.github.io/tada/reference/UpdateInternalData.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Update Existing Data in sysdata.rda — UpdateInternalData","text":"Updated sysdata.rda file","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"Update Measure Unit Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateMeasureUnitRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Measure Unit Reference Table internal file (for internal use only) — UpdateMeasureUnitRef","text":"","code":"UpdateMeasureUnitRef()"},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":null,"dir":"Reference","previous_headings":"","what":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"Update Characteristic Validation Reference Table internal file (internal use )","code":""},{"path":"usepa.github.io/tada/reference/UpdateWQXCharValRef.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update Characteristic Validation Reference Table internal file\r\n(for internal use only) — UpdateWQXCharValRef","text":"","code":"UpdateWQXCharValRef()"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"Used store cached WQX QAQC Characteristic Validation Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"","code":"WQXCharValRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXCharValRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached WQX QAQC Characteristic Validation Reference Table — WQXCharValRef_Cached","text":"object class NULL length 0.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":null,"dir":"Reference","previous_headings":"","what":"Transform Units to WQX Target Units — WQXTargetUnits","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function compares measure units input data Water Quality Exchange (WQX) 3.0 QAQC Characteristic Validation table.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"","code":"WQXTargetUnits(.data, transform = TRUE)"},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":".data TADA dataset transform Boolean argument two possible values, “TRUE” “FALSE”. Default transform = TRUE.","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"transform=TRUE, result values units converted WQX target units. function changes values within \"ResultMeasure.MeasureUnitCode\" \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" WQX target units converts respective values within \"ResultMeasureValue\" \"DetectionQuantitationLimitMeasure.MeasureValue\" fields. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=TRUE add following two fields input dataset, \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\", retain original result unit values. transform = FALSE, result values units converted WQX target units, columns appended indicate target units conversion factors , data can converted. addition \"WQX.ResultMeasureValue.UnitConversion\" \"WQX.DetectionLimitMeasureValue.UnitConversion\", transform=FALSE add following two fields input dataset: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXTargetUnits.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Transform Units to WQX Target Units — WQXTargetUnits","text":"function ALWAYS add following two columns input dataset: \"WQX.ResultMeasureValue.UnitConversion\", \"WQX.DetectionLimitMeasureValue.UnitConversion\" two fields indicate data can converted.\"NoResultValue\" means data converted ResultMeasureValue, \"NoTargetUnit\" means data converted original unit associated target unit WQX. \"Convert\" means data can transformed, \"Converted\" means function run input transform = TRUE, values already converted. also uses following six fields input dataset: \"CharacteristicName\", \"ActivityMediaName\", \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\" function adds following two fields transforms values within following four fields transform=TRUE: Adds: \"ResultMeasureUnitCode.Original\", \"DetectionLimitMeasureUnitCode.Original\". Transforms: \"ResultMeasureValue\", \"ResultMeasure.MeasureUnitCode\", \"DetectionQuantitationLimitMeasure.MeasureValue\", \"DetectionQuantitationLimitMeasure.MeasureUnitCode\". function adds following two fields transform=FALSE: Adds: \"WQX.ConversionFactor\" \"WQX.TargetUnit\".","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":null,"dir":"Reference","previous_headings":"","what":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"Used store cached Measure Unit Reference Table","code":""},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"","code":"WQXunitRef_Cached"},{"path":"usepa.github.io/tada/reference/WQXunitRef_Cached.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Used to store cached Measure Unit Reference Table — WQXunitRef_Cached","text":"object class NULL length 0.","code":""}] diff --git a/vignettes/WQPDataHarmonization.Rmd b/vignettes/WQPDataHarmonization.Rmd index 0c647734..3abf30d9 100644 --- a/vignettes/WQPDataHarmonization.Rmd +++ b/vignettes/WQPDataHarmonization.Rmd @@ -205,6 +205,10 @@ Additional resources: Option 1: Use the TADAdataRetrieval function. ```{r} +# uncomment below if you would like to review differences between the profiles you get using readWQPdata vs. TADAdataRetrieval. This is because TADAdataRetrieval automatically joins in other data from different WQP profiles, and does some additional data cleaning as part of the data retrieval process + +#dataRetrievalProfile <- dataRetrieval::readWQPdata(statecode = "UT", characteristicName = c("Ammonia", "Nitrate", "Nitrogen"), startDate = "01-01-2021", ignore_attributes = TRUE) + #You can edit this to define your own WQP query inputs below TADAProfile <- TADAdataRetrieval(statecode = "UT", characteristicName = c("Ammonia", "Nitrate", "Nitrogen"), startDate = "01-01-2021")