Package 'auspol'

Title: Australian Federal Election Results (2004-2022)
Description: Retrieve Australian Federal Election results for House of Representatives and Senate, from 2004 onwards.
Authors: Carlos Yáñez Santibáñez [aut, cre], Craig Alexander [ths], Kyle Walker [cph], Australian Electoral Commission [cph]
Maintainer: Carlos Yáñez Santibáñez <[email protected]>
License: MIT + file LICENSE
Version: 0.0.1.0004
Built: 2024-08-25 05:57:25 UTC
Source: https://github.com/carlosyanez/auspol

Help Index

Helper function generate colour palette

Description

Helper function generate colour palette

Usage

auspol_theme(
  p,
  type = c("colour", "fill"),
  extra_colours = NULL,
  extra_values = NULL,
  coord_flip = FALSE,
  palette = NULL,
  legend_pos = "none"
)

Arguments

p

ggplot object
type

type of scales: c("colour","fill)
extra_colours

named vector additional colour (hex) values
extra_values

vector with all unique combinations (to assign each a colour)
coord_flip

whether to flip coordinate axes
palette

additional colour palette for unnamed parties
legend_pos

legend position

Value

ggplot object

Helper function to update/download data

Description

Helper function to update/download data

Usage

data_delete(file = NULL)

Arguments

file

to delete - defaults to all of them

Value

nothing

Helper function to update/download data

Description

Helper function to update/download data

Usage

data_import(file)

Arguments

file

file to import to the cache

Value

nothing

Helper function to update/download data

Description

Helper function to update/download data

Usage

data_info()

Value

nothing

Helper function to update/download data

Description

Helper function to update/download data

Usage

data_update(file = NULL)

Arguments

file

vectors with file name from repository. By default, downloads all files

Value

nothing

Helper function to find cache folder

Description

Helper function to find cache folder

Usage

find_cache()

Value

nothing

Bar chart, customised for this package.

Description

Bar chart, customised for this package.

Usage

geom_auspol_bar(include_labels = TRUE, reference_line = NULL, nudge_x = 4, ...)

Arguments

include_labels

Whether to include numeric labels (TRUE by default)
reference_line

Value for reference line. If left empty, no line is added.
nudge_x

distance between label and bar
...

parameters for ggplot2 functions. Label parameters (geom_text_repel()) prefixed with "labels." Reference line parameters (geom_vline()) prefixed with "ref_line."

Line chart, customised for this package.

Description

Line chart, customised for this package.

Usage

geom_auspol_line(include_labels = TRUE, ...)

Arguments

include_labels

Whether to include numeric labels (TRUE by default)
...

parameters for ggplot2 functions. Label parameters (geom_text_repel()) prefixed with "labels."

Lollipop or bar chart, custommised for this package.

Description

Lollipop or bar chart, custommised for this package.

Usage

geom_auspol_lollipop(format = "lollipop", include_labels = TRUE, ...)

Arguments

format

Output format : "lollipop" (default) or "bar".
include_labels

Whether to include numeric labels (TRUE by default)
...

parameters for ggplot2 geom_segment() (segmnet.prefix), geom_point(), geom_col() and geom_text() (labels. prefix).

Two-party preferred flow

Description

Get flow from primary vote to finalists, for an division on a given election

Usage

get_house_2PF(division, year, aggregation = FALSE)

Arguments

division

character vector with division names. When left blank, returns all division.
year

number vector with election years. When left blank, returns all years.
aggregation

Whether to present division totals (defaults to FALSE)

Value

dataframe with list of elected MPs

Examples

## Not run: 
# get primary to finalist flow of preferences for Jagajaga in the 2013 election
get_house_2PF(division="Jagajaga",year=2013,aggregation = TRUE)

## End(Not run)

Two-party-preferred summary

Description

Get 2-party preferred party summary (Coalition vs ALP), as calculated by the AEC.

Usage

get_house_2PP(
  division = NULL,
  year = NULL,
  state_abb = NULL,
  aggregation = FALSE
)

Arguments

division

character vector with division names. When left blank, returns all division.
year

number vector with election years. When left blank, returns all years.
state_abb

vector with state/territory acronym (e.g. NSW,VIC,QLD,etc.)
aggregation

Whether to present division totals (defaults to FALSE)

Value

dataframe with list of elected MPs

Examples

## Not run: 
get_house_2PP(division = "Indi",
year=2016,
aggregation = TRUE)

## End(Not run)

Elected MPs

Description

Retrieve list of elected MPs, filterable by division and year

Usage

get_house_MPs(division = NULL, year = NULL)

get_MPs(division = NULL, year = NULL)

Arguments

division

character vector with division names. When left blank, returns all division.
year

number vector with election years. When left blank, returns all years.

Value

data frame with list of elected MPs

Examples

## Not run: 
# Elected MPs in Melbourne and Cooper, 2019 and 2022
get_house_MPs(division = c("Melbourne","Cooper"),
              year = c(2019,2022))

## End(Not run)

Preferences

Description

Retrieves preference flow, filterable by election and year. Results can be presented by polling place - as retrived from the AEC - or aggregated by electoral division.

Usage

get_house_preferences(
  division,
  year,
  polling_places = NULL,
  aggregation = FALSE
)

get_preferences(division, year, polling_places = NULL, aggregation = FALSE)

Arguments

division

vector with division names
year

vector with election years
polling_places

list of polling places
aggregation

whether to aggregate by division

Value

dataframe with list of elected MPs

Examples

## Not run: 
# basic use
get_house_preferences("Wills",2019) |> head(10)
# aggregated version
get_house_preferences("Wills",2019,aggregation = TRUE)
# filtered by polling place
get_house_preferences("Wills",2019, polling_places=c("ABSENT")) |> head(10)


## End(Not run)

Primary vote for House Elections

Description

Get primary vote for one or more divisions, for one or more elections. Data can be filtered by state, political party of polling locations. Results can be presented by polling station or aggregated by division.

Usage

get_house_primary_vote(
  division = NULL,
  year = NULL,
  state_abb = NULL,
  party_abb = NULL,
  aggregation = FALSE,
  polling_places = NULL
)

Arguments

division

character vector with division names. When left blank, returns all division.
year

number vector with election years. When left blank, returns all years.
state_abb

vector with state/territory acronym (e.g. NSW,VIC,QLD,etc.)
party_abb

vector with party abbreviation (e.g. ALP,LIB,NP,GRN,etc.)
aggregation

Whether to present division totals (defaults to FALSE)
polling_places

vector with regex for polling places

Value

sf object with selected polygons

Examples

## Not run: 
# Primary vote in Brisbane, 2022 election
get_house_primary_vote(division="Brisbane",year=2022)
# Primary vote in Perth and Brisbane in 2019 and 2022 (aggregated)
get_house_primary_vote(division=c("Brisbane","Perth"),year=c(2019,2022),aggregation = TRUE)
# Primary vote for Greens candidates in Tasmania and the Northern Territory, 2019
get_house_primary_vote(state=c("TAS","NT"),year=2019,aggregation = TRUE, party_abb=c("GRN"))

## End(Not run)

Election turn out

Description

Retrieve election turnout, filterable by division and year

Usage

get_house_turnout(division = NULL, year = NULL)

Arguments

division

character vector with division names. When left blank, returns all division.
year

number vector with election years. When left blank, returns all years.

Value

data frame turnout numbers

Examples

## Not run: 
# Turnout in Riverina
 get_house_turnout(division="Riverina",yeat)

## End(Not run)

Preferences flow from primary to finalists

Description

Plot representing flow of preferences from first preferences to candidates in last round. Can be present as alluvial plot or bar chart, showing votes count or percentages.

Usage

house_2PF_plot(
  division,
  year,
  var = "Percent",
  extra_colours = NULL,
  plot_format = "bar",
  include_data = FALSE,
  individualise_IND = TRUE
)

Arguments

division

Electoral division
year

Election year
var

Variable to be plotted "Percent" (default) or "Transfer Count"
extra_colours

manual mapping of colours for each party, as a named vector.
plot_format

Whether to plot alluvial chart ("alluvial") or a bar chart ("bar", default).
include_data

If set to TRUE, data will be included under <<output_var>>$source_data (defaults to FALSE)
individualise_IND

If set to TRUE, party abbreviations for each independent candidate will be changed from "IND" to "IND-<<candidate's surname>>", effectively separating them in party aggregations.

Value

preference flow, ggplot2 object

Examples

## Not run: 
# Preference flow for Burt, 2022
house_2PF_plot("Burt",2022,plot_format = "alluvial")
# Preference flow for Warringah 2022,
house_2PF_plot("Spence",2013,plot_format = "bar")

## End(Not run)

Two Party-Preferred Comparison

Description

Plot with two-party preferred values for one of more divisions, for a given year Can be present as alluvial plot or bar chart, showing votes count or percentages.

Usage

house_2PP_comparison_plot(
  division = NULL,
  year,
  state = NULL,
  var = "Percentage",
  include_data = TRUE
)

Arguments

division

Electoral division
year

Election year
state

If division is left null, use this to select all divisions in one of more states.
var

Variable to be plotted "Percentage" (default) or "Votes"
include_data

If set to TRUE, data will be included under <<output_var>>$source_data (defaults to FALSE)

Value

ggplot2 object

Examples

## Not run: 
# Two party preferred plot for Victoria, 2022
house_2PP_comparison_plot(year=2022,state="VIC")

## End(Not run)

Two Party-Preferred Comparison

Description

Plot with two-party preferred values for one of more divisions, for a given year Can be present as alluvial plot or bar chart, showing votes count or percentages.

Usage

house_2PP_historical_plot(
  division,
  year = NULL,
  var = "Percentage",
  include_labels = TRUE,
  include_data = TRUE
)

Arguments

division

Electoral division
year

Election year
var

Variable to be plotted "Percentage" (default) or "Votes"
include_labels

If set to TRUE, the plot will include each value.
include_data

If set to TRUE, data will be included under <<output_var>>$source_data (defaults to FALSE)

Value

ggplot2 object

Examples

## Not run: 
# Plot historical 2PP for Aston
house_2PP_historical_plot(division="Aston")

## End(Not run)

Flow of preferences in a division.

Description

retrieves data containing preferential voting rounds for a division in a particular election (as published by the AEC). Can be filtered by polling place (including special modes of voting) or it can be presented as an aggregate per division.

Usage

house_preference_flow_data(
  division,
  year,
  individualise_IND = TRUE,
  exclude_parties = NULL,
  exclude_rounds = 0
)

Arguments

division

division
year

election year
individualise_IND

If set to TRUE, party abbreviations for each independent candidate will be changed from "IND" to "IND-<<candidate's surname>>", effectively separating them in party aggregations.
exclude_parties

vector with party acronyms to exclude from plot
exclude_rounds

If parties are excluded, include vector indicating from which rounds should them be excluded

Value

list with data frames with results for each round

Examples

## Not run: 
#get preferences for Wills, 2019
get_house_preferences("Wills",2019)
show results for absent votes only
get_house_preferences("Wills",2019, polling_places=c("ABSENT"),aggregation = FALSE)


## End(Not run)

Plot House of reps preferences flow

Description

Plot flow of preferences in a division as an alluvial plot.

Usage

house_preference_flow_plot(
  division,
  year,
  var = "Percent",
  exclude_parties = NULL,
  merge_parties = NULL,
  extra_colours = NULL,
  include_data = FALSE
)

Arguments

division

Electoral division
year

Election year
var

Variable to be plotted "Percent" (default) or "Preference Count"
exclude_parties

vector with party acronyms to exclude from plot
merge_parties

list of parties to merge in one line following, the format list(NEWCODE=c(code1,code2,etc.))
extra_colours

manual mapping of colours for each party, as a named vector.
include_data

If set to TRUE, output of primary_vote_summary(), will be included under <<output_var>>$source_data (defaults to FALSE)

Value

preference flow, ggplot2 object

Examples

## Not run: 
# Preference flow for Wills, 2019
house_preference_flow_plot(division = "Wills",year=2019)
# Preference flow for Warringah 2022,
# excluding two finalists from round 1,
# independent candidate in teal.
house_preference_flow_plot(division = "Warringah",year=2022,

## End(Not run)

Plot historical changes in primary vote

Description

Line chart with historial changes for a division, group of candidates in a party, selected parties, etc.

Usage

house_primary_comparison_plot(
  division = NULL,
  year = NULL,
  state = NULL,
  label = "Candidate",
  plotted_variable = "Percentage",
  sort_by_value = TRUE,
  extra_colours = NULL,
  plot_format = "lollipop",
  include_labels = FALSE,
  hor_nudge = 5,
  parties = NULL,
  parties_year = NULL,
  merge_parties = NULL,
  include_others = FALSE,
  include_informal = FALSE,
  individualise_IND = TRUE,
  include_data = TRUE,
  data = NULL
)

Arguments

division

Name of ONE electoral division
year

numeric vector with election years (from 2004), defaults to all.
state

Code for one state
label

How to label the results, either by Candidate Name ("Name",default), Party Name ("PartyNm") or Party abbreviation ("PartyAb")
plotted_variable

Variable to plot, out of "OrdinaryVotes", "Percentage" (default) and Percentage_with_Informal
sort_by_value

Whether to sort results by descending order (TRUE by default)
extra_colours

manual mapping of colours for each party, as a named vector.
plot_format

Whether to plot lollipop chart ("lollipop", default) or a bar chart.
include_labels

If set to TRUE, the plot will include each value.
hor_nudge

if labels are included, separation from chart/dot
parties

which parties to include in the summary. All (default), a vector of strings with the party acronyms (see list_parties()), or a number indicating the top n parties from a certain year.
parties_year

If parties has is NULL or a number, this indicates if the selection needs to be from a certain year (.e.g only select the historical data for the three top parties in 2012)
merge_parties

list of parties to merge in one line following, the format list(NEWCODE=c(code1,code2,etc.))
include_others

Boolean used along parties to included the remaining votes in one "Other" category.
include_informal

Boolean to add informal votes in addition to the party selection. Informal votes will be included if no parties are selected, or the top n parties are selected, and it happens to be in the top n - even if this flag is set to false.
individualise_IND

If set to TRUE, party abbreviations for each independent candidate will be changed from "IND" to "IND-<<candidate's surname>>", effectively separating them in party aggregations.
include_data

If set to TRUE, output of house_primary_vote_summary(), will be included under <<output_var>>$source_data (defaults to FALSE)
data

Alternative, instead of providing a parameters, it is possible to provide the data frame with the data to plot, following the format from the output of house_primary_vote_summary().

Value

ggplot2 object

Examples

## Not run: 
# Compare primary voting in Kooyong in 2022,  lollipop chart (default)
house_primary_comparison_plot(division = "Kooyong",
                              year=2022,
                              individualise_IND = TRUE)
# Liberal Primary vote in Tasmania in 2022, bar chart
house_primary_comparison_plot(state="TAS",
                              year=2022,
                              parties=c("LP"),
                              plot_format = "bar")


## End(Not run)

Plot primary vote history

Description

Plot historical primary vote results for a division or group of divisions, being able to select and aggregate political parties. Can plot either percentages or absolute number of ordinary votes.

Usage

house_primary_historic_plot(
  division = NULL,
  plotted_variable = "Percentage",
  parties = NULL,
  parties_year = NULL,
  merge_parties = NULL,
  include_others = FALSE,
  include_informal = FALSE,
  individualise_IND = FALSE,
  extra_colours = NULL,
  include_labels = FALSE,
  year = NULL,
  include_data = FALSE,
  include_text_tooltip = FALSE,
  data = NULL
)

Arguments

division

named vector with division names
plotted_variable

Variable to plot, out of "OrdinaryVotes", "Percentage" (default) and Percentage_with_Informal
parties

which parties to include in the summary. All (default), a vector of strings with the party acronyms (see list_parties()), or a number indicating the top n parties from a certain year.
parties_year

If parties has is NULL or a number, this indicates if the selection needs to be from a certain year (.e.g only select the historical data for the three top parties in 2012).
merge_parties

list of parties to merge in one line following, the format list(NEWCODE=c(code1,code2,etc.))
include_others

Boolean used along parties to included the remaining votes in one "Other" category.
include_informal

Boolean to add informal votes in addition to the party selection. Informal votes will be included if no parties are selected, or the top n parties are selected, and it happens to be in the top n - even if this flag is set to false.
individualise_IND

If set to TRUE, party abbreviations for each independent candidate will be changed from "IND" to "IND-<<candidate's surname>>", effectively separating them in party aggregations.
extra_colours

manual mapping of colours for each party, as a named vector.
include_labels

If set to TRUE, the plot will include each value.
year

numeric vector with election years (from 2004), defaults to all.
include_data

If set to TRUE, output of house_primary_vote_summary(), will be included under <<output_var>>$source_data (defaults to FALSE)
include_text_tooltip

Flag to include tooltip for plotly mapped as text in ggplot
data

Alternative, instead of providing a parameters, it is possible to provide the data frame with the data to plot, folowing the format from the output of house_primary_vote_summary().

Value

ggplot2 object

Examples

## Not run: 
# Plot historic primary voting in Canberra, top 3 parties
house_primary_historic_plot("Canberra", parties =3,


## End(Not run)

Helper function to download data

Description

Helper function to download data

Usage

house_primary_vote_summary(
  division = NULL,
  state = NULL,
  year = NULL,
  parties = NULL,
  parties_year = NULL,
  include_others = FALSE,
  merge_parties = NULL,
  include_informal = FALSE,
  include_names = TRUE,
  individualise_IND = FALSE,
  wide_format = NULL
)

Arguments

division

vector with names of electoral divisions (e.g. "Banks", "Wills","Indi")
state

if divisions are not provide, provide a vector with state initials e.g. c("NT","TAS")
year

numeric vector with election years (from 2004), defaults to all.
parties

which parties to include in the summary. All (default), a vector of strings with the party acronyms (see list_parties()), or a number indicating the top n parties from a certain year.
parties_year

If parties has is NULL or a number, this indicates if the selection needs to be from a certain year (.e.g only select the historical data for the three top parties in 2012)
include_others

Boolean used along parties to included the remaining votes in one "Other" category.
merge_parties

list of parties to merge in one line following, the format list(NEWCODE=c(code1,code2,etc.))
include_informal

Boolean to add informal votes in addition to the party selection. Informal votes will be included if no parties are selected, or the top n parties are selected, and it happens to be in the top n - even if this flag is set to false.
include_names

whether to include the candidates name and surname in the extract (TRUE by default).
individualise_IND

If set to TRUE, party abbreviations for each independent candidate will be changed from "IND" to "IND-<<candidate's surname>>", effectively separating them in party aggregations.
wide_format

Whether to present the result in long format, like the AEC's source, or a year-by-year summary. Options include NULL (no summarisation, default), "OrdinaryVotes" (absolute numbers), "Percentage_with_Informal" and "Percentage" (which is the percentage counted on elections).

Value

dataframe

Examples

## Not run: 
# Get primary for Kooyong in 2022
house_primary_vote(division="Kooyong",year=2022)
# Get historic primary for Liberals and Labor in Kooyong
house_primary_vote(division="Kooyong",parties=c("LP","ALP")
#Get primary vote for all National candidates in WA, 2022
house_primary_vote(state="WA",year=2022,parties=c(NP))

## End(Not run)

Historic Resuls

Description

Plot seats by party across time. Parties can be filtered and grouped by coalitions.

Usage

house_results_historic(
  individualise_IND = FALSE,
  merge_parties = NULL,
  parties = NULL,
  include_others = FALSE,
  include_labels = TRUE,
  extra_colours = NULL,
  include_data = FALSE
)

Arguments

individualise_IND

If set to TRUE, party abbreviations for each independent candidate will be changed from "IND" to "IND-<<candidate's surname>>", effectively separating them in party aggregations.
merge_parties

list of parties to merge in one line following, the format list(NEWCODE=c(code1,code2,etc.))
parties

List of political party abbreviations to filter on. If merge_parties is used, those names can be included too.
include_others

Boolean used along parties to included the remaining votes in one "Other" category.
include_labels

If set to TRUE, the plot will include each value.
extra_colours

manual mapping of colours for each party, as a named vector.
include_data

If set to TRUE, data will be included under <<output_var>>$source_data (defaults to FALSE)

Value

preference flow, ggplot2 object

Examples

## Not run: 
# Historic results, focusing showing tally for Coalition, ALP, Greens - others merged together
house_results_historic(merge_parties = list(COAL=c("CLP","LP","LNP","NP")),
                       parties =c("COAL","ALP","GRN"),
                       include_other=TRUE))

## End(Not run)

Election Tally

Description

Plot party totals for a given election. Can aggregate parties into groups, amongst other filters.

Usage

house_results_tally(
  year,
  individualise_IND = FALSE,
  merge_parties = NULL,
  add_majority_line = TRUE,
  include_labels = FALSE,
  extra_colours = NULL,
  include_data = FALSE
)

Arguments

year

Election year
individualise_IND

If set to TRUE, party abbreviations for each independent candidate will be changed from "IND" to "IND-<<candidate's surname>>", effectively separating them in party aggregations.
merge_parties

list of parties to merge in one line following, the format list(NEWCODE=c(code1,code2,etc.))
add_majority_line

add line representing 50% +1 of the seats
include_labels

If set to TRUE, the plot will include each value.
extra_colours

manual mapping of colours for each party, as a named vector.
include_data

If set to TRUE, data will be included under <<output_var>>$source_data (defaults to FALSE)

Value

preference flow, ggplot2 object

Examples

## Not run: 
# Basic example
house_results_tally(2013)
# Coalition votes put together
house_results_tally(2013, merge_parties = list(COAL=c("CLP","LP","LNP","NP")))

## End(Not run)

Get list of divisions

Description

get list of all the Australian Federal electoral divisions, being able to filter by any attribute. Covers all divisions from the 2004 Election.

Usage

list_divisions(filters = NULL)

Arguments

filters

(optional) list() with filters in the form list(Column="Value")

Value

data frame with lists of divisions

Examples

## Not run: 
# Get list of all divisions
list_divisions()

#Get list containing only Wills and Melbourne
list_divisions(filters=list(DivisionNm=c("Wills","Melbourne")))
 
## End(Not run)

List all political parties.

Description

Lists all political parties that have participated from the 2004 Election onwards. Parties are presented as recorded by the AEC. List can be filtered by party names matching a regular expression.

Usage

list_parties(filters = NULL, party_regex = NULL)

Arguments

filters

(optional) list() with filters in the form list(Column="Value").
party_regex

additional filter for party names, taking a regular expression.

Value

data frame with lists of divisions

Examples

## Not run: 
# Get list of all registered political parties
list_parties()
#
# Get list of all parties whose name start with "Australia"
list_parties(party_regex="^Australia")
 
## End(Not run)

List all polling stations

Description

Retrieve list of all polling station that been used from 2044 onwards. Names as recorded by the AEC. List can be filtered by state, division names and regular expressions matching their names.

Usage

list_polling_places(filters = NULL)

Arguments

filters

(optional) list() with filters in the form list(Column="Value")

Value

data frame with lists of polling stations

Examples

## Not run: 
# Get list of all registered parties
list_parties()
# Get list of polling places in the division of Hasluck
list_parties(list)

 
## End(Not run)

Get election years.

Description

Very simple function listing the election years included in this package.

Usage

list_years()

Value

vector with years

Examples

## Not run: 
# Get list of all divisions
list_years()
 
## End(Not run)

Helper function generate colour palette

Description

Helper function generate colour palette

Usage

manage_colours(extra_colours = NULL, extra_values = NULL, palette = NULL)

Arguments

extra_colours

named vector additional colour (hex) values
extra_values

vector with all unique combinations (to assign each a colour)
palette

palette to replace brewer.pal

Value

named vector with colours

Named vector with common party colours, with option to add custom/additional values

Description

Named vector with common party colours, with option to add custom/additional values

Usage

party_colours(extra = NULL)

Arguments

extra

named vector additional colour (hex) values

Value

named vector