dsbox: Data Science Course in a Box

#' Foreign-Connected PAC Contributions, all years, clean data
#'
#' Every election cycle brings its own brand of excitement – and lots of money.
#' Political donations are of particular interest to political scientists and
#' other researchers studying politics and voting patterns.
#' They are also of interest to citizens who want to stay informed of how much
#' money their candidates raise and where that money comes from.
#'
#' In the United States, “only American citizens (and immigrants with green
#' cards) can contribute to federal politics, but the American divisions of
#' foreign companies can form political action committees (PACs) and collect
#' contributions from their American employees.” (source: OpenSecrets.org)
#'
#' The data come from the
#' [OpenSecrets.org](https://www.opensecrets.org/political-action-committees-pacs/foreign-connected-pacs/2022).
#'
#' The data were scraped from the OpenSecrets.org website in June 2020.
#' It is part of a series of similar datasets in this package consisting of
#' datasets collected from OpenSecrets via webscraping.
#'
#' This particular dataset consists of the data for foreign-connected PAC
#' contributions for all available elections cycles, in raw form as it was when
#' scraped from the website on 11 Nov 2020.
#'
#' @source https://www.opensecrets.org/political-action-committees-pacs/foreign-connected-pacs/2022
#' @format A tibble with 2156 rows and 7 variables:
#' \describe{
#'   \item{name}{Name of company (American divisions of a foreign company)}
#'   \item{country}{Country of origin}
#'   \item{parent}{PAC parent company}
#'   \item{total}{Total PAC contributions to all parties}
#'   \item{dems}{PAC contributions to the Democratic Party}
#'   \item{repubs}{PAC contributions to the Republican Party}
#'   \item{year}{Election cycle year}
#' }
#' @seealso pac_2020_raw, pac_2020, pac_all_raw
#' @examples
#'
#' library(dplyr)
#' library(ggplot2)
#'
#' pac_all |>
#'   filter(country %in% c("Canada", "UK")) |>
#'   group_by(country, year) |>
#'   summarise(tot = sum(total)) |>
#'   ggplot(aes(x = year, y = tot, group = country, color = country)) +
#'   geom_line() +
#'   labs(
#'     x = "Year",
#'     y = "Total Contributions",
#'     color = "Country"
#'   )
#'
#'
"pac_all"