.Rhistory

library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
usethis::use_pkgdown()
library(pkgdown)
build_site()
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(pkgdown)
build_site()
library(spiR)
build_site()
library(spiR)
build_site()
library(spiR)
library(spiR)
build_site()
library(spiR)
#' sqs_spi_data
#'
#' @description This function allows you to find and display the Social Progress Index data according to the selected parameters.
#' If no arguments are filed, all data will be displayed.
#'
#' @param country country Countries' ISO code.
#' @param years Years for which you want data.
#' @param indicators Indicators from the Social Progress Index.
#'
#' @import gsheet
#' @import dplyr
#' @import reshape2
#'
#' @return Data for the country, indicator and year requested
#' @export
#'
#' @seealso \code{\link{sqs_spi_indicator}} for the SPI's indicator symbol and \code{\link{sqs_spi_country}} for the country's ISO code.
#'
#' @examples
#' myData<- sqs_spi_data(country = c("USA", "FRA"), years = "2018", )
#' myData<- sqs_spi_data(country = c("USA", "FRA"), year = c("2018", "2019"), indicators = "SPI")
#' myData<- sqs_spi_data("USA", "2019", c("SPI", "FOW"))
#' myData<- sqs_spi_data(, "2018", )
#' myData<- sqs_spi_data("USA", "2017", )
#' myData<- sqs_spi_data("USA", , )
#' myData<- sqs_spi_data(, , )
#' myData<- sqs_spi_data()
#'
#'
#
# Function 1: Data collection
spi_data <- gsheet::gsheet2tbl("https://docs.google.com/spreadsheets/d/1_nQ9mQU_4J0KDRc4_TMzTsJHMYBqLwwnPaMC5BVhkGc/edit#gid=0")
# Function 2: Indicators' symbols query
# If the user does not know the code of an indicator, s.he has access to the answer in natural language through this query
#' sqs_spi_indicator
#'
#' @description This function allows you to find and search the right indicator code from the Social Progress Index you want to use.
#' If no argument is filed, all indicators will be displayed.
#' @param indicators An indicator from the Social Progress Index.
#'
#' @return Indicator code from the Social Progress Index.
#' @export
#' @seealso \code{\link{sqs_spi_country}} for the SPI's country code and \code{\link{sqs_spi_data}} to collect data when you have both indicator and country code.
#'
#' @examples
#'myIndicator <- sqs_spi_indicator()
#'myIndicator <- sqs_spi_indicator(indicators = "mortality")
#'myIndicator <- sqs_spi_indicator("mortality")
#'
sqs_spi_indicator <- function(indicators) {
spi_indicators_natural_language <- gsheet::gsheet2tbl("https://docs.google.com/spreadsheets/d/1_nQ9mQU_4J0KDRc4_TMzTsJHMYBqLwwnPaMC5BVhkGc/edit#gid=400714513")
if (missing(indicators)) {
spi_indicators_natural_language
} else {
spi_indicators_natural_language[grep(indicators, spi_indicators_natural_language$indicator_name), ]
}
}
# Function 3: Countries' code reconciliation
# If the user does not know the ISO code of a country, s.he has access to the answer in natural language through this query
#' sqs_spi_country
#' @description This function allows you to find and search the right country code associated with the Social Progress Index's Data.
#' If no argument is filed, all indicators will be displayed.
#'
#' @param country The name of the country starting with a capital letter.
#'
#' @return Country's ISO code.
#' @export
#' @seealso \code{\link{sqs_spi_indicator}} for the SPI's indicators and \code{\link{sqs_spi_data}} to collect data when you have both indicator and country code.
#' @examples
#'mycountry <- sqs_spi_country()
#'mycountry <- sqs_spi_country(country = "Canada")
#'mycountry <- sqs_spi_country("Canada")
#'
sqs_spi_country <- function(country) {
spi_countries_natural_language <- unique(spi_data[, 1:2])
if (missing(country)) {
spi_countries_natural_language
} else {
spi_countries_natural_language[grep(country, spi_countries_natural_language$countryName), ]
}
}
data_long <- reshape2::melt(spi_data,
# ID variables - all the variables to keep but not split apart on
id.vars = c("countryName", "code", "year"),
# The source columns
measure.vars = colnames(spi_data)[6:ncol(spi_data)],
# Name of the destination column that will identify the original
# column that the measurement came from
#variable.name = "var_indicator",
#value.name = "value"
)
base::names(data_long) = c("countryName", "var_code", "var_year", "var_indicator", "value")
# Creating the default values for the function query
# IF an entry is missing, all the observations of this variable will be displayed
data_long_country <- base::unique(data_long[, 2])
data_long_year <- base::unique(data_long[, 3])
data_long_indicator <- base::unique(data_long[, 4])
sqs_spi_data <- function(country = data_long_country,
years = data_long_year,
indicators = data_long_indicator) {
out <- dplyr::filter(data_long,
var_code %in% country,
var_year %in% years,
var_indicator %in% indicators)
return(out)
}
#' sqs_spi_data
#'
#' @description This function allows you to find and display the Social Progress Index data according to the selected parameters.
#' If no arguments are filed, all data will be displayed.
#'
#' @param country country Countries' ISO code.
#' @param years Years for which you want data.
#' @param indicators Indicators from the Social Progress Index.
#'
#' @import gsheet
#' @import dplyr
#' @import reshape2
#'
#' @return Data for the country, indicator and year requested
#' @export
#'
#' @seealso \code{\link{sqs_spi_indicator}} for the SPI's indicator symbol and \code{\link{sqs_spi_country}} for the country's ISO code.
#'
#' @examples
#' myData<- sqs_spi_data(country = c("USA", "FRA"), years = "2018", )
#' myData<- sqs_spi_data(country = c("USA", "FRA"), year = c("2018", "2019"), indicators = "SPI")
#' myData<- sqs_spi_data("USA", "2019", c("SPI", "FOW"))
#' myData<- sqs_spi_data(, "2018", )
#' myData<- sqs_spi_data("USA", "2017", )
#' myData<- sqs_spi_data("USA", , )
#' myData<- sqs_spi_data(, , )
#' myData<- sqs_spi_data()
#'
#'
#
# Function 1: Data collection
spi_data <- gsheet::gsheet2tbl("https://docs.google.com/spreadsheets/d/1_nQ9mQU_4J0KDRc4_TMzTsJHMYBqLwwnPaMC5BVhkGc/edit#gid=0")
data_long <- reshape2::melt(spi_data,
# ID variables - all the variables to keep but not split apart on
id.vars = c("countryName", "code", "year"),
# The source columns
measure.vars = colnames(spi_data)[6:ncol(spi_data)],
# Name of the destination column that will identify the original
# column that the measurement came from
#variable.name = "var_indicator",
#value.name = "value"
)
base::names(data_long) = c("countryName", "var_code", "var_year", "var_indicator", "value")
# Creating the default values for the function query
# IF an entry is missing, all the observations of this variable will be displayed
data_long_country <- base::unique(data_long[, 2])
data_long_year <- base::unique(data_long[, 3])
data_long_indicator <- base::unique(data_long[, 4])
sqs_spi_data <- function(country = data_long_country,
years = data_long_year,
indicators = data_long_indicator) {
out <- dplyr::filter(data_long,
var_code %in% country,
var_year %in% years,
var_indicator %in% indicators)
return(out)
}
# Function 2: Indicators' symbols query
# If the user does not know the code of an indicator, s.he has access to the answer in natural language through this query
#' sqs_spi_indicator
#'
#' @description This function allows you to find and search the right indicator code from the Social Progress Index you want to use.
#' If no argument is filed, all indicators will be displayed.
#' @param indicators An indicator from the Social Progress Index.
#'
#' @return Indicator code from the Social Progress Index.
#' @export
#' @seealso \code{\link{sqs_spi_country}} for the SPI's country code and \code{\link{sqs_spi_data}} to collect data when you have both indicator and country code.
#'
#' @examples
#'myIndicator <- sqs_spi_indicator()
#'myIndicator <- sqs_spi_indicator(indicators = "mortality")
#'myIndicator <- sqs_spi_indicator("mortality")
#'
sqs_spi_indicator <- function(indicators) {
spi_indicators_natural_language <- gsheet::gsheet2tbl("https://docs.google.com/spreadsheets/d/1_nQ9mQU_4J0KDRc4_TMzTsJHMYBqLwwnPaMC5BVhkGc/edit#gid=400714513")
if (missing(indicators)) {
spi_indicators_natural_language
} else {
spi_indicators_natural_language[grep(indicators, spi_indicators_natural_language$indicator_name), ]
}
}
# Function 3: Countries' code reconciliation
# If the user does not know the ISO code of a country, s.he has access to the answer in natural language through this query
#' sqs_spi_country
#' @description This function allows you to find and search the right country code associated with the Social Progress Index's Data.
#' If no argument is filed, all indicators will be displayed.
#'
#' @param country The name of the country starting with a capital letter.
#'
#' @return Country's ISO code.
#' @export
#' @seealso \code{\link{sqs_spi_indicator}} for the SPI's indicators and \code{\link{sqs_spi_data}} to collect data when you have both indicator and country code.
#' @examples
#'mycountry <- sqs_spi_country()
#'mycountry <- sqs_spi_country(country = "Canada")
#'mycountry <- sqs_spi_country("Canada")
#'
sqs_spi_country <- function(country) {
spi_countries_natural_language <- unique(spi_data[, 1:2])
if (missing(country)) {
spi_countries_natural_language
} else {
spi_countries_natural_language[grep(country, spi_countries_natural_language$countryName), ]
}
}
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
aa <- sqs_spi_data()
aa <- sqs_spi_data()
View(aa)
ab <- sqs_spi_indicator()
View(ab)
as <- sqs_spi_data("USA",2016)
View(as)
aass <- sqs_spi_country("Canada","Germany","Iceland")
aass <- sqs_spi_country("Canada")
View(aass)
usethis::use_appveyor()
library(pkgdown)
build_site()
library(spiR)
library(devtools)
check_win_release()
build_site()
build_site()
library(spiR)
library(spiR)
use_cran_comments()
library(spiR)
rela
e
release()
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(spiR)
library(pkgdown)
build_site()
library(spiR)
library(spiR)
build_site()
library(spiR)
build_site()
library(spiR)
library(pkgdown)
build_site()
library(devtools)
submit_cran()
library(spiR)
library(spiR)
library(spiR)
build_site()
library(devtools)
build_site()
pkgdown::build_site()
library(spiR)
pkgdown::build_site()
pkgdown::build_site()
devtools::submit_cran()
pkgdown::build_site()
library(spiR)
devtools::submit_cran()
library(spiR)
library(spiR)
pkgdown::build_site()
devtools::submit_cran()
pkgdown::build_site()
pkgdown::build_site()
library(spiR)
pkgdown::build_site()
devtools::submit_cran()
pkgdown::build_site()
pkgdown::build_site()
pkgdown::build_site()
library(spiR)
pkgdown::build_site()
# Loading data
url <- paste0("https://warin.ca/datalake/spiR/SPI_data.csv")
path <- file.path(tempdir(), "temp.csv")
curl::curl_download(url, path)
csv_file <- file.path(paste0(tempdir(), "/temp.csv"))
SPI_data <- readr::read_csv(csv_file)
url <- paste0("https://warin.ca/datalake/spiR/SPI_indicator.csv")
path <- file.path(tempdir(), "temp.csv")
curl::curl_download(url, path)
csv_file <- file.path(paste0(tempdir(), "/temp.csv"))
SPI_indicator <- readr::read_csv(csv_file)
spi_country <- base::unique(SPI_data$country_code)
spi_year <- base::unique(SPI_data$year)
spi_indicator <- base::unique(SPI_data$indicator_code)
spir_data <- function(country = spi_country,
years = spi_year,
indicators = spi_indicator) {
country_code <- year <- indicator_code <- NULL
out <- dplyr::filter(SPI_data,
country_code %in% country,
year %in% years,
indicator_code %in% indicators)
return(out)
}
spir_indicator <- function(indicators) {
spi_indicators_natural_language <- SPI_indicator
if (missing(indicators)) {
spi_indicators_natural_language
} else {
spi_indicators_natural_language[grep(indicators, spi_indicators_natural_language$indicator_name, ignore.case = TRUE), ]
}
}
spir_country <- function(country) {
spi_countries_natural_language <- unique(SPI_data[, 2:3])
if (missing(country)) {
spi_countries_natural_language
} else {
spi_countries_natural_language[grep(country, spi_countries_natural_language$country_name, ignore.case = TRUE), ]
}
}
spir_visual <- function(chart = "bar_1", indicator = "SPI", years = max(SPI_data$year), title = TRUE){
year <- value <- indicator_code <- country_name <- country_code <- NULL
if(years > 2020 | years < 2011){
stop("no available data for the requested year")
}
if(chart == "bar_1"){
barchart1 <- SPI_data
barchart1 <- dplyr::filter(barchart1, year == years)
barchart1 <- dplyr::filter(barchart1, indicator_code == indicator)
barchart1 <- dplyr::arrange(barchart1, desc(value))
countries <- barchart1[1:9, 3]
countries <- countries$country_code
barchart1 <- dplyr::filter(barchart1, country_code %in% countries)
barchart1$country_name <- factor(barchart1$country_name, levels = unique(barchart1$country_name)[order(barchart1$value)])
barchart1$value <- format(round(barchart1$value, 2), nsmall = 2)
if(title == TRUE){
ggplot2::ggplot(data = barchart1, aes(x = country_name, y = value, fill = country_name)) +
ggplot2::geom_col() +
ggplot2::geom_text(aes(label=value), vjust=0.2, hjust = 1.1, colour = "white", size = 3.2, fontface = "bold") +
ggplot2::ylab("")  +
ggplot2::xlab("") +
ggplot2::ggtitle(paste(unique(barchart1$indicator_name), "in", years)) +
ggplot2::theme_minimal() +
ggplot2::guides(fill=FALSE) +
ggsci::scale_fill_uchicago() +
ggplot2::theme(legend.position="none", plot.title = element_text(size=12))  +
ggplot2::labs(fill = "Countries", caption="Source: Warin (2020) & Social Progress Index.") +
ggplot2::coord_flip() +
ggplot2::theme(axis.title.x=element_blank(),
axis.ticks.x=element_blank(),
axis.text.x=element_blank())
} else {
ggplot2::ggplot(data = barchart1, aes(x = country_name, y = value, fill = country_name)) +
ggplot2::geom_col() +
ggplot2::geom_text(aes(label=value), vjust=0.2, hjust = 1.1, colour = "white", size = 3.2, fontface = "bold") +
ggplot2::ylab("")  +
ggplot2::xlab("") +
ggtitle("") +
ggplot2::theme_minimal() +
ggplot2::guides(fill=FALSE) +
ggsci::scale_fill_uchicago() +
ggplot2:: theme(legend.position="none", plot.title = element_text(size=12))  +
ggplot2::labs(fill = "Countries", caption="Source: Warin (2020) & Social Progress Index.") +
ggplot2::coord_flip() +
ggplot2::theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
}
} else if(chart == "line_1"){
linechart1 <- SPI_data
linechart1 <- dplyr::filter(linechart1, indicator_code == indicator)
linechart1 <- dplyr::arrange(linechart1, desc(year), desc(value))
countries <- linechart1[1:6, 3]
countries <- countries$country_code
linechart1 <- dplyr::filter(linechart1, country_code %in% countries)
linechart1$year <- lubridate::ymd(linechart1$year, truncated = 2L)
if(title == TRUE){
ggplot2::ggplot(data = linechart1, aes(x = year, y = value, color = country_name, shape = country_name)) +
ggplot2::geom_line() +
ggplot2::geom_point(size = 2, stroke = 1) +
ggplot2::ylab("")  +
ggplot2:: xlab("") +
ggplot2::ggtitle(paste0(unique(linechart1$indicator_name), ": \nEvolution of the ", max(SPI_data$year), " most represented countries")) +
ggplot2::theme_minimal() +
ggplot2::guides(fill=FALSE) +
ggsci::scale_color_uchicago() +
ggplot2::theme(legend.position="right", plot.title = element_text(size=12))  +
ggplot2::labs(shape = "Countries", color = "Countries", caption="Source: Warin (2020) & Social Progress Index.")
} else {
ggplot2::ggplot(data = linechart1, aes(x = year, y = value, color = country_name, shape = country_name)) +
ggplot2::geom_line() +
ggplot2::ylab("")  +
ggplot2::xlab("") +
ggplot2::ggtitle("") +
ggplot2::theme_minimal() +
ggplot2::guides(fill=FALSE) +
ggplot2::geom_point(size = 2, stroke = 1) +
ggsci::scale_color_uchicago() +
ggplot2::theme(legend.position="right", plot.title = element_text(size=12))  +
ggplot2::labs(shape = "Countries", color = "Countries", caption="Source: Warin (2020) & Social Progress Index.")
}
} else{
stop("invalid arguments")
}
}
aa <- EpiBibR::epibibr_data()
pkgdown::build_site()
test <- EpiBibR::epibibr_data()
pkgdown::build_site()
aa <- EpiBibR::epibibr_data()
pkgdown::build_site()
aa <-EpiBibR::epibib_data()
knitr::opts_chunk$set(echo = TRUE)
aa <- EpiBibR::epibibr_data()
pkgdown::build_site()
EpiBibR::epibibr_data()
aa <- EpiBibR::epibibr_data()
pkgdown::build_site()
aa <- EpiBibR::epibibr_data()
aa <- EpiBibR::epibibr_data()
pkgdown::build_site()
aa <-EpiBibR::epibib_data()
aa <- EpiBibR::epibibr_data()
library(EpiBibR)
aa <-epibibr_data()
pkgdown::build_site()
pkgdown::build_site()
pkgdown::build_site()
pkgdown::build_site()
pkgdown::build_site()
pkgdown::build_site()
pkgdown::build_site()
library(EpiBibR)
aa <-EpiBibR::epibibr_data()
pkgdown::build_site()
devtools::check_win_release()
library(EpiBibR)
library(EpiBibR)
url <- paste0("https://warin.ca/datalake/epiBib/EpiBib.Rdata")
path <- file.path(tempdir(), "temp.Rdata")
if (httr::http_error(url)) { # network is down = message (not an error anymore)
message("No Internet connection or the server is in maintenance mode.")
return(NULL)
} else { # network is up = proceed to download via curl
message("EpiBibR: downloading remote dataset.")
with(options(timeout = max(300, getOption("timeout"))),curl::curl_download(url, path))
} # /if - network up or down
curl::curl_download(url, path)
#reading the data
rData <- file.path(paste0(tempdir(), "/temp.Rdata"))
load(rData)
#reading the data
rData <- file.path(paste0(tempdir(), "/temp.Rdata"))
EpiBib_data <-load(rData)
load(rData)
EpiBib_data <-EpiBib_data
library(EpiBibR)
library(EpiBibR)
library(EpiBibR)
pkgdown::build_site()
devtools::submit_cran()
devtools::submit_cran()
EpiBibR::epibibr_data()
aa <- epibibr_data()