Download two candidate preference voting data from each polling booth, from the five Australian Federal elections between 2004 and 2016.

twocand_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

  • CandidateID: Candidate ID

  • Surname: Candidate surname

  • GivenNm: Candidate given name

  • BallotPosition: Candidate's position on the ballot

  • Elected: Whether the candidate was elected (Y/N)

  • HistoricElected: Whether the candidate is the incumbent member

  • PartyAb: Abbreviation for political party name

  • PartyNm: Political party name

  • OrdinaryVotes: Number of ordinary votes cast at the polling place for the candidate

  • Swing: Percentage point change in ordinary votes for the party 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 candidate preferred votes for candidates in the House of Representatives, for each polling both, in the five Australian Federal elections between 2004 and 2016.

Value

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,

Examples

if (FALSE) {
tcp_pp <- twocand_pollingbooth_download()
library(dplyr)
tcp_pp %>% filter(year == 2016) %>% arrange(-OrdinaryVotes) %>% head
}