Nothing
#' Download a data frame containing the polygons of Australian federal electorates
#'
#' Downloads and returns a DataFrame containing the points that outline the polygons
#' for each of the Australian electorates in the desired federal election. The data were obtained from the
#' Australian Electoral Commission and the Australian Bureau of Statistics.
#'
#' @param year Desired year, must be one of 2001, 2004, 2007, 2010, 2011, 2013, 2016, 2019
#' @param ... Additional arguments passed to `download.file`
#'
#' @return A data frame consisting of points with the following variables:
#' \itemize{
#' \item id: Numeric identifier for the polygon
#' \item long: longitude coordinate of point in polygon
#' \item lat: latitude coordinate of point in polygon
#' \item order: order for polygon points
#' \item hole: whether polygon has a hole
#' \item piece: piece for polygon
#' \item group: group for polygon
#' \item elect_div: Electoral division name
#' \item state: Abbreviation for state name
#' }
#'
#' @examples
#' library(eechidna)
#' library(dplyr)
#' library(ggmap)
#'
#' nat_map16 <- nat_map_download(2016)
#'
#' nat_map16 %>%
#' filter(elect_div=='MELBOURNE') %>%
#' qmplot(long, lat, data=., color='red', size=5,
#' xlab=NA,ylab=NA) +
#' theme(legend.position = 'none')
#'@export
nat_map_download <- function(year, ...){
year = as.numeric(year)
suffix = substr(year, 3, 4)
url_git = paste0("https://github.com/jforbes14/eechidna/raw/master/extra-data/nat_map", suffix, ".rda")
if (year == 2001) {
nat_map01 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_map01
} else if (year == 2004) {
nat_map04 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_map04
} else if (year == 2007) {
nat_map07 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_map07
} else if (year == 2010) {
nat_map10 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_map10
} else if (year == 2011) {
nat_map11 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_map11
} else if (year == 2013) {
nat_map13 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_map13
} else if (year == 2016) {
nat_map16 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_map16
} else if (year == 2019) {
nat_map19 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_map19
} else {
warning("Desired year are not available: select from 2001, 2004, 2007, 2010, 2011, 2013, 2016, 2019")
return()
}
}
#' Download a data frame containing electorate centroids
#'
#' @description
#' Downloads and returns a data frame containing the points that make up the centroids
#' for each of the Australian electorates in the desired federal election.
#'
#' @param year Desired year, must be one of 2001, 2004, 2007, 2010, 2011, 2013, 2016, 2019
#' @param ... Additional arguments passed to `download.file`
#'
#'
#' @return A data frame with data associated with each of the Australian federal electorates
#'
#' \itemize{
#' \item id: Numeric identifier for the polygon
#' \item elect_div: Electorate division name
#' \item state: abbreviation of the state name
#' \item numccds: AEC variable that might be filled with meaning or a description down the road
#' \item area_sqkm: combined square kilometers of each electorate
#' \item long_c: longitude coordinate of electorate (polygon) centroid
#' \item lat_c: latitude coordinate of electorate (polygon) centroid
#' \item x: latitude coordinate for plotting a cartogram
#' \item y: longitude coordinate for plotting a cartogram
#' \item radius: variable used in the construction of cartogram points
#' }
#'
#' @examples
#' library(eechidna)
#' library(dplyr)
#' library(ggmap)
#'
#' nat_data19 <- nat_data_download(2019)
#'
#' nat_data19 %>%
#' qmplot(long_c, lat_c, data=.)
#' @export
nat_data_download <- function(year, ...){
year = as.numeric(year)
suffix = substr(year, 3, 4)
url_git = paste0("https://github.com/jforbes14/eechidna/raw/master/extra-data/nat_data", suffix, ".rda")
if (year == 2001) {
nat_data01 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_data01
} else if (year == 2004) {
nat_data04 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_data04
} else if (year == 2007) {
nat_data07 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_data07
} else if (year == 2010) {
nat_data10 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_data10
} else if (year == 2011) {
nat_data11 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_data11
} else if (year == 2013) {
nat_data13 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_data13
} else if (year == 2016) {
nat_data16 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_data16
} else if (year == 2019) {
nat_data19 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
nat_data19
} else {
warning("Desired year are not available: select from 2001, 2004, 2007, 2010, 2011, 2013, 2016, 2019")
return()
}
}
#' Download SpatialPolygonsDataFrame containing polygons of Australian federal electorates
#'
#' @param year Desired year, must be one of 2001, 2004, 2007, 2010, 2011, 2013, 2016, 2019
#' @param ... Additional arguments passed to `download.file`
#'
#' Downloads and returns a large SpatialPolygonsDataFrame containing the polygons
#' and associated data for each of the Australian electorates in the desired federal election.
#' This object is obtained using the `sF_download` function. The data were obtained from the
#' Australian Electoral Commission and the Australian Bureau of Statistics.
#'
#' @return A SpatialPolygonsDataFrame containing polygons of the Australian federal electorates
#'
#' @examples
#' \dontrun{
#' sF_16 <- sF_download(year = 2016)
#' # Plot a map of the electorates
#' library(sp)
#' plot(sF_16)
#' }
#'
#' @export
sF_download <- function(year, ...){
year = as.numeric(year)
suffix = substr(year, 3, 4)
url_git = paste0("https://github.com/jforbes14/eechidna/raw/master/extra-data/sF_", suffix, ".rda")
if (year == 2001) {
sF_01 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
sF_01
} else if (year == 2004) {
sF_04 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
sF_04
} else if (year == 2007) {
sF_07 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
sF_07
} else if (year == 2010) {
sF_10 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
sF_10
} else if (year == 2011) {
sF_11 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
sF_11
} else if (year == 2013) {
sF_13 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
sF_13
} else if (year == 2016) {
sF_16 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
sF_16
} else if (year == 2019) {
sF_19 <- 1
tmp <- tempfile()
utils::download.file(url_git, tmp, ...)
load(tmp)
sF_19
} else {
warning("Electoral boundaries for desired year are not available: select from 2001, 2004, 2007, 2010, 2011, 2013, 2016, 2019")
return()
}
}
#' Download first preference voting data from each polling booth, from the six
#' Australian Federal elections between 2001 and 2016.
#'
#' @param ... Additional arguments passed to `download.file`
#'
#' Downloads and returns first preference votes for candidates in the House of
#' Representatives, for each polling both, in the seven Australian Federal elections
#' between 2001 and 2016.
#'
#' @return A data frame containing first preference votes
#'
#' A dataset containing first preference vote counts, candidate names, polling place locations,
#' and other results for the House of Representatives from the 2001, 2004, 2007, 2010,
#' 2013 and 2016 Australian federal elections. This data set is obtained using the
#' `firstpref_pollingbooth_download` function. The data were obtained from the Australian Electoral
#' Commission.
#'
#' @format A data frame with the following variables:
#' \itemize{
#' \item StateAb: Abbreviation for state name
#' \item DivisionID: Electoral division ID
#' \item DivisionNm: Electoral division name
#' \item PollingPlaceID: Polling place ID
#' \item PollingPlace: Polling place name
#' \item CandidateID: Candidate ID
#' \item Surname: Candidate surname
#' \item GivenNm: Candidate given name
#' \item BallotPosition: Candidate's position on the ballot
#' \item Elected: Whether the candidate was elected (Y/N)
#' \item HistoricElected: Whether the candidate is the incumbent member
#' \item PartyAb: Abbreviation for political party name
#' \item PartyNm: Political party name
#' \item OrdinaryVotes: Number of ordinary votes cast at the polling place
#' for the candidate
#' \item Swing: Percentage point change in ordinary votes for the party
#' from the previous election
#' \item PremisesPostCode: Post code of polling booth
#' \item Latitude: Coordinates
#' \item Longitude: Coordinates
#' \item year: Election year
#' }
#'
#' @examples
#' \dontrun{
#' fp_pp <- firstpref_pollingbooth_download()
#' library(dplyr)
#' fp_pp %>% filter(year == 2016) %>% arrange(-OrdinaryVotes) %>% head
#' }
#'
#' @export
firstpref_pollingbooth_download <- function(...){
fp_pp <- 1
tmp <- tempfile()
utils::download.file("https://github.com/jforbes14/eechidna/raw/master/extra-data/fp_pp.rda", tmp)
load(tmp)
fp_pp
}
#' Download two party preference voting data from each polling booth, from the seven
#' Australian Federal elections between 2001 and 2016.
#'
#' @param ... Additional arguments passed to `download.file`
#'
#' Downloads and returns the two party preferred votes for candidates in the House of
#' Representatives, for each polling both, in the six Australian Federal elections between
#' 2001 and 2016.
#'
#' @return A data frame containing two party preference votes
#'
#' A dataset containing two party preferred vote counts, winning candidate names,
#' polling place locations, and other results for the House of Representatives from
#' each of the 2001, 2004, 2007, 2010, 2013 and 2016 Australian federal elections.
#' Includes the count of votes for the Australian Labor Party and the count of votes
#' for the Liberal-National Coalition for each polling place. This data set is obtained
#' using the `twoparty_pollingbooth_download` function. The data were obtained from the
#' Australian Electoral Commission.
#'
#' @format A data frame with the following variables:
#' \itemize{
#' \item StateAb: Abbreviation for state name
#' \item DivisionID: Electoral division ID
#' \item DivisionNm: Electoral division name
#' \item PollingPlaceID: Polling place ID
#' \item PollingPlace: Polling place name
#' \item LNP_Votes: Count of two party preferred vote in favour of the
#' Liberal National coalition
#' \item LNP_Percent: Percentage of two party preferred vote in favour
#' of the Liberal National coalition
#' \item ALP_Votes: Count of two party preferred vote in favour of the
#' Labor party
#' \item ALP_Percent: Percentage of two party preferred vote in favour
#' of the Labor party
#' \item TotalVotes: Total number of votes cast
#' \item Swing: Percentage point change in two party preferred vote from
#' the previous election
#' \item PremisesPostCode: Post code of polling booth
#' \item Latitude: Coordinates
#' \item Longitude: Coordinates
#' \item year: Election year
#' }
#'
#' @examples
#' \dontrun{
#' tpp_pp <- twoparty_pollingbooth_download()
#' library(dplyr)
#' tpp_pp %>% filter(year == 2016) %>% arrange(-LNP_Percent) %>% head
#' }
#'
#' @export
twoparty_pollingbooth_download <- function(...){
tpp_pp <- 1
tmp <- tempfile()
utils::download.file("https://github.com/jforbes14/eechidna/raw/master/extra-data/tpp_pp.rda", tmp)
load(tmp)
tpp_pp
}
#' Download two candidate preference voting data from each polling booth, from the five
#' Australian Federal elections between 2004 and 2016.
#'
#' @param ... Additional arguments passed to `download.file`
#'
#' Downloads and returns the two candidate preferred votes for candidates in the House of
#' Representatives, for each polling both, in the five Australian Federal elections between
#' 2004 and 2016.
#'
#' @return A data frame containing two candidate preference votes
#'
#' A dataset containing two candidate preferred vote counts, polling place locations,
#' and other results for the House of Representatives from each of the 2004,
#' 2007, 2010, 2013 and 2016 Australian federal elections. Includes the count of votes
#' for the leading two candidates in the electorate after distribution of preferences
#' for each polling place. Note that 2001 two candidate preferred vote is not available
#' in this package. This data set is obtained using the `twocand_pollingbooth_download` function.
#' The data were obtained from the Australian Electoral Commission,
#'
#' @format A data frame with the following variables:
#' \itemize{
#' \item StateAb: Abbreviation for state name
#' \item DivisionID: Electoral division ID
#' \item DivisionNm: Electoral division name
#' \item PollingPlaceID: Polling place ID
#' \item PollingPlace: Polling place name
#' \item CandidateID: Candidate ID
#' \item Surname: Candidate surname
#' \item GivenNm: Candidate given name
#' \item BallotPosition: Candidate's position on the ballot
#' \item Elected: Whether the candidate was elected (Y/N)
#' \item HistoricElected: Whether the candidate is the incumbent member
#' \item PartyAb: Abbreviation for political party name
#' \item PartyNm: Political party name
#' \item OrdinaryVotes: Number of ordinary votes cast at the polling place
#' for the candidate
#' \item Swing: Percentage point change in ordinary votes for the party
#' from the previous election
#' \item PremisesPostCode: Post code of polling booth
#' \item Latitude: Coordinates
#' \item Longitude: Coordinates
#' \item year: Election year
#' }
#'
#' @examples
#' \dontrun{
#' tcp_pp <- twocand_pollingbooth_download()
#' library(dplyr)
#' tcp_pp %>% filter(year == 2016) %>% arrange(-OrdinaryVotes) %>% head
#' }
#'
#' @export
twocand_pollingbooth_download <- function(...){
tcp_pp <- 1
tmp <- tempfile()
utils::download.file("https://github.com/jforbes14/eechidna/raw/master/extra-data/tcp_pp.rda", tmp)
load(tmp)
tcp_pp
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.