us_temp data (to use in place of climate70)

R/data-us_temp.R

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+#' US temperatures in 1950 and 2022
+#'
+#' A representative set of monitoring locations were taken from NOAA
+#' data in 1950 and 2022 such that the locations are sampled roughly
+#' geographically across the continental US (the observations do not
+#' represent a random sample of geographical locations).
+#'
+#' Please keep in mind that the data represent two annual snapshots, and a complete
+#' analysis would consider more than two years of data and a random or more
+#' complete sampling of weather stations across the US.
+#'
+#' @name us_temp
+#' @docType data
+#' @format A data frame with 18759 observations on the following 9 variables.
+#' \describe{
+#'   \item{location}{Location of the NOAA weather station.}
+#'   \item{station}{Formal ID of the NOAA weather station.}
+#'   \item{latitude}{Latitude of the NOAA weather station.}
+#'   \item{longitude}{Longitude of the NOAA weather station.}
+#'   \item{date}{Date the measurement was taken (Y-m-d).}
+#'   \item{tmax}{Maximum daily temperature (Farenheit).}
+#'   \item{tmin}{Minimum daily temperature (Farenheit).}
+#'   \item{year}{Year of the measurement.}
+#'  }
+#' @source [NOAA Climate Data Online](https://www.ncdc.noaa.gov/cdo-web/). Retrieved 23 September, 2023.
+#' @keywords datasets
+#' @examples
+#' library(ggplot2)
+#' library(sf)
+#'
+#' summarized_temp <- us_temp |>
+#'   group_by(station, year, latitude, longitude) |>
+#'   summarize(tmax_med = median(tmax, na.rm = TRUE)) |>
+#'   mutate(plot_shift = ifelse(year == "1950", 0, 1))
+#'
+#' usa <- st_as_sf(maps::map("state", fill = TRUE, plot = FALSE))
+#' ggplot(data = usa) +
+#'   geom_sf() +
+#'   geom_point(data = summarized_temp,
+#'              aes(x = longitude + plot_shift, y = latitude,
+#'                  color = tmax_med, shape = year)) +
+#'   scale_color_gradient(high = IMSCOL["red", 1], low = IMSCOL["yellow", 1]) +
+#'   ggtitle("Median of the daily high temp, 1950 & 2022") +
+#'   labs(x = "longitude",
+#'        color = "median high temp") +
+#'   guides(shape = guide_legend(override.aes = list(color = "black")))
+"us_temp"

data-raw/us_temp/us_temp-dataprep.R

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+# Load packages ----------------------------------------------------------------
+
+library(openintro)
+library(tidyverse)
+library(usethis)
+library(lubridate)
+
+# Load data --------------------------------------------------------------------
+
+us_temp <- read_csv("data-raw/us_temp/us_temp.csv") |>
+  select(location, everything())
+
+# Add to package
+use_data(us_temp, overwrite = TRUE)
+