Distribution of preferences by candidate by division in the Australian Federal Election (2022 and 2025)

Provides details on how votes are distributed and transferred among candidates in all count stages of the preferential voting system. All electoral divisions in the Australian Federal Election are included.

Usage

aecdop_2022

aecdop_2025

Format

A tibble of 14 columns:

StateAb

State or territory abbreviation (e.g., "ACT", "NSW", "VIC")

DivisionID

Numeric identifier for the electoral division

DivisionNm

Name of the electoral division (e.g., "Bean", "Canberra")

CountNumber

Round in the counting procedure, starting from 0 (first preference)

BallotPosition

Position of the candidate on the ballot paper

CandidateID

Unique numeric identifier for the candidate

Surname

Candidate's surname

GivenNm

Candidate's given name(s)

PartyAb

Party abbreviation (e.g., "UAPP", "ALP", "LP")

PartyNm

Full party name (e.g., "United Australia Party", "Australian Labor Party")

Elected

Whether the candidate was elected: "Y" (yes) or "N" (no)

HistoricElected

Whether the candidate was elected in the previous election: "Y" (yes) or "N" (no)

CalculationType

Type of calculation:

Preference Count: Number of votes received
Preference Percent: Percentage of votes received
Transfer Count: Number of votes transferred from other candidates
Transfer Percent: Percentage of votes transferred from other candidates

CalculationValue

Numeric value for the calculation type (votes or percentage)

An object of class spec_tbl_df (inherits from tbl_df, tbl, data.frame) with 35096 rows and 14 columns.

An object of class spec_tbl_df (inherits from tbl_df, tbl, data.frame) with 30888 rows and 14 columns.

Source

Australian Electoral Commission (AEC) Distribution of Preferences 2022 Distribution of Preferences 2025

Details

Two datasets are provided:

aecdop_2022: 2022 Federal Election (35,096 rows)
aecdop_2025: 2025 Federal Election (30,888 rows)

Examples

# Load the datasets
data(aecdop_2022)
data(aecdop_2025)

# First preferences for Bean division in 2022
aecdop_2022 |> 
  dplyr::filter(DivisionNm == "Bean",
         CountNumber == 0,
         CalculationType == "Preference Count")
#> # A tibble: 6 × 14
#>   StateAb DivisionID DivisionNm CountNumber BallotPosition CandidateID Surname 
#>   <chr>        <dbl> <chr>            <dbl>          <dbl>       <dbl> <chr>   
#> 1 ACT            318 Bean                 0              1       36239 CONWAY  
#> 2 ACT            318 Bean                 0              2       37455 AMBARD  
#> 3 ACT            318 Bean                 0              3       36231 SMITH   
#> 4 ACT            318 Bean                 0              4       32130 CHRISTIE
#> 5 ACT            318 Bean                 0              5       36243 SAVERY  
#> 6 ACT            318 Bean                 0              6       37198 HIATT   
#> # ℹ 7 more variables: GivenNm <chr>, PartyAb <chr>, PartyNm <chr>,
#> #   Elected <chr>, HistoricElected <chr>, CalculationType <chr>,
#> #   CalculationValue <dbl>