Download two party preference voting data from each polling booth, from the seven Australian Federal elections between 2001 and 2016.

Source: R/git-download.R

Download two party preference voting data from each polling booth, from the seven Australian Federal elections between 2001 and 2016.

twoparty_pollingbooth_download(...)

Format

A data frame with the following variables:

  • StateAb: Abbreviation for state name

  • DivisionID: Electoral division ID

  • DivisionNm: Electoral division name

  • PollingPlaceID: Polling place ID

  • PollingPlace: Polling place name

  • LNP_Votes: Count of two party preferred vote in favour of the Liberal National coalition

  • LNP_Percent: Percentage of two party preferred vote in favour of the Liberal National coalition

  • ALP_Votes: Count of two party preferred vote in favour of the Labor party

  • ALP_Percent: Percentage of two party preferred vote in favour of the Labor party

  • TotalVotes: Total number of votes cast

  • Swing: Percentage point change in two party preferred vote from the previous election

  • PremisesPostCode: Post code of polling booth

  • Latitude: Coordinates

  • Longitude: Coordinates

  • year: Election year

Arguments

...

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.

Value

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.

Examples

if (FALSE) {
tpp_pp <- twoparty_pollingbooth_download()
library(dplyr)
tpp_pp %>% filter(year == 2016) %>% arrange(-LNP_Percent) %>% head
}