R/council_seats.R

In parlitools: Tools for Analysing UK Politics

#' Council Seats
#'
#' Downloads data from
#' <[opencouncildata.co.uk/](http://opencouncildata.co.uk/)>, with the
#' composition of each local council in Great Britain. If using this data,
#' please cite the above site as the source.
#'
#' @param councillors If `TRUE`, downloads details on each individual
#' councillor for each local council. If `FALSE`, downloads summary data
#' for each council. Defaults to `FALSE`.
#' @inheritParams current_mps
#'
#' @return A tibble with the most recent available council seat distribution
#' or councillor affiliations.
#' @export
#' @examples
#' \dontrun{
#' a <- council_seats(councillors = FALSE)
#' 
#' b <- council_seats(councillors = TRUE)
#' }
#' 
council_seats <- function(councillors = FALSE, tidy = TRUE,
                          tidy_style = "snake_case") {
  if (councillors == TRUE) {
    councillor_data <- readr::read_csv("http://opencouncildata.co.uk/csv2.php",
      col_types = readr::cols(
        .default = "c"
      )
    )
    council_data <- readr::read_csv("http://opencouncildata.co.uk/csv1.php",
      col_types = readr::cols(
        .default = "c"
      )
    )

    council_data <- council_data[c("id", "ons code", "name", "type")]

    df <- dplyr::left_join(councillor_data, council_data,
      by = c("councilID" = "id")
    )
  } else {
    council_data <- readr::read_csv("http://opencouncildata.co.uk/csv1.php",
      col_types = readr::cols(
        .default = "c"
      )
    )
    council_data$type <- NULL
    council_data$id <- NULL
    council_data$model <- NULL
    council_data <- dplyr::rename(council_data,
      majority_party = "majority",
      governing_coalition = "coalition",
      conservative_councillors = "con",
      labour_councillors = "lab",
      lib_dem_councillors = "ld",
      green_councillors = "grn",
      ukip_councillors = "ukip",
      plaid_cymru_councillors = "pc",
      snp_councillors = "snp",
      independent_councillors = "ind",
      vacant_seats = "vacant",
      total_councillors = "total",
      last_update = "last update"
    )

    names(council_data) <- snakecase::to_snake_case(names(council_data))

    party_list <- c(
      "conservative_councillors",
      "labour_councillors",
      "lib_dem_councillors",
      "green_councillors",
      "ukip_councillors",
      "snp_councillors",
      "independent_councillors",
      "vacant_seats"
    )

    council_data[party_list] <- lapply(council_data[party_list], as.numeric)

    council_data$total_councillors <- rowSums(
      council_data[, c(
        "conservative_councillors",
        "labour_councillors",
        "lib_dem_councillors",
        "green_councillors",
        "ukip_councillors",
        "snp_councillors",
        "independent_councillors",
        "vacant_seats"
      )]
    )

    ## Recoding council_data$majority_party into council_data$majority_party_rec
    council_data$majority_party <- dplyr::recode(council_data$majority_party,
      "IND" = "Independent",
      "CON" = "Conservative",
      "NOC" = "No Overall Control",
      "LAB" = "Labour",
      "LD" = "Liberal Democrat",
      "PC" = "Plaid Cymru"
    )

    council_data$name <- dplyr::recode(
      council_data$name,
      "Copeland (M)" = "Copeland",
      "Mansfield (M)" = "Mansfield",
      "Hackney (M)" = "Hackney",
      "Lewisham (M)" = "Lewisham",
      "Newham (M)" = "Newham",
      "Tower Hamlets (M)" = "Tower Hamlets",
      "Doncaster (M)" = "Doncaster",
      "Liverpool (M)" = "Liverpool",
      "Salford (M)" = "Salford",
      "Bedford (M)" = "Bedford",
      "Bristol (M)" = "Bristol",
      "Leicester (M)" = "Leicester",
      "Middlesbrough (M)" = "Middlesbrough",
      "Torbay (M)" = "Torbay",
      "Hinckley & Bosworth" = "Hinckley and Bosworth",
      "Newark & Sherwood" = "Newark and Sherwood",
      "Oadby & Wigston" = "Oadby and Wigston",
      "Tonbridge & Malling" = "Tonbridge and Malling",
      "Nuneaton & Bedworth" = "Nuneaton and Bedworth",
      "Basingstoke & Deane" = "Basingstoke and Deane",
      "Reigate & Banstead" = "Reigate and Banstead",
      "Weymouth & Portland" = "Weymouth and Portland",
      "Barking & Dagenham" = "Barking and Dagenham",
      "Hammersmith & Fulham" = "Hammersmith and Fulham",
      "Kensington & Chelsea" = "Kensington and Chelsea",
      "St. Helens" = "St Helens",
      "Aberdeen City" = "Aberdeen",
      "Argyll & Bute" = "Argyll and Bute",
      "Dumfries & Galloway" = "Dumfries and Galloway",
      "Dundee" = "Dundee",
      "Edinburgh" = "City of Edinburgh",
      "Glasgow" = "Glasgow City",
      "Orkney" = "Orkney Islands",
      "Perth & Kinross" = "Perth and Kinross",
      "Shetland" = "Shetland Islands",
      "Brighton & Hove" = "Brighton and Hove",
      "Bristol" = "City of Bristol",
      "Cheshire West & Chester" = "Cheshire West and Chester",
      "Durham" = "County Durham",
      "Redcar & Cleveland" = "Redcar and Cleveland",
      "Telford & Wrekin" = "Telford and Wrekin",
      "Windsor & Maidenhead" = "Windsor and Maidenhead"
    )

    la_codes <- parlitools::la_codes

    council_data <- dplyr::left_join(council_data, la_codes)

    rm(la_codes)

    df <- council_data[c(
      "la_code", "name", "type", "majority_party",
      "governing_coalition",
      "total_councillors", "conservative_councillors",
      "labour_councillors", "lib_dem_councillors",
      "green_councillors", "ukip_councillors",
      "plaid_cymru_councillors", "snp_councillors",
      "independent_councillors", "vacant_seats",
      "boundary", "url", "last_update"
    )]
  }

  if (tidy == TRUE) {
    df <- parlitools_tidy(df, tidy_style)
  }

  df
}