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Process Overseas Voting Data

Source: R/process_overseas.R
process_overseas.Rd

Standardises column names and calculates total votes for overseas voting data from the 2013, 2019, and 2022 Australian federal elections. This function aligns disparate column names across election years to a consistent format and computes the total votes as the sum of postal and pre-poll votes. If an unrecognised election year is provided, the data is returned unprocessed with a message.

Usage

process_overseas(data, event)

Arguments

data

A data frame containing overseas voting data. Must include an event column indicating the election event (e.g., "2013 Federal Election", "2019 Federal Election", "2022 Federal Election", "2023 Referendum") and, for recognised years, year-specific columns for state, division, overseas post, and vote counts.

event

A character string specifying the election event to process. Recognised values are "2013 Federal Election", "2019 Federal Election", "2022 Federal Election", or "2023 Referendum". Other values will result in the data being returned unprocessed.

Value

A data frame. For recognised election years ("2013", "2019", "2022", "2023"), it contains standardised columns:

  • date (if present in input)

  • event (the election event)

  • StateAb (state abbreviation, standardised using amend_names() for 2013 and 2019)

  • DivisionNm (division name)

  • OverseasPost (name of the overseas voting post)

  • PrePollVotes (pre-poll vote count)

  • PostalVotes (postal vote count)

  • TotalVotes (sum of PrePollVotes and PostalVotes, with NA handling)

Rows with missing StateAb values (e.g., totals) are removed for 2013 data. For unrecognised election years, the original data frame is returned unchanged.

Details

This function processes overseas voting data by:

  1. Standardising column names to a consistent set across recognised election years using rename_cols().

  2. For 2013 data: Removing unnecessary columns (pp_sort_nm, Total) and rows with NA in StateAb.

  3. Converting full state names to abbreviations using amend_names() for 2013 and 2019 data.

  4. Calculating TotalVotes as the sum of PostalVotes and PrePollVotes, treating NA as 0.

  5. For unrecognised years: Returning the data unprocessed with an informative message.

The function assumes the input data frame contains the required columns for the specified event year when it is "2013", "2019", or "2022", though column names may vary as per the original datasets.

See also

amend_names) for state name standardisation.

Examples

# Sample 2013 data
data_2013 <- data.frame(
  event = "2013 Federal Election",
  StateAb = c("NSW", "VIC", NA),
  DivisionNm = c("Sydney", "Melbourne", "Total"),
  pp_nm = c("London", "Paris", "All"),
  `Pre-poll Votes` = c(100, 150, 250),
  `Postal Votes` = c(50, 75, 125),
  pp_sort_nm = c("LON", "PAR", "ALL"),
  Total = c(150, 225, 375),
  check.names = FALSE
)
process_overseas(data_2013, "2013 Federal Election")
#> Processing `2013 Federal Election` data to ensure all columns align across all elections.
#>                   event StateAb DivisionNm OverseasPost PrePollVotes
#> 1 2013 Federal Election     NSW     Sydney       London          100
#> 2 2013 Federal Election     VIC  Melbourne        Paris          150
#>   PostalVotes TotalVotes
#> 1          50        150
#> 2          75        225

# Sample invalid year
data_2025 <- data.frame(event = "2025 Federal Election", StateAb = "QLD", Votes = 100)
process_overseas(data_2025, "2025 Federal Election")
#> No processing required for `2025 Federal Election`. Data returned unprocessed.
#>                   event StateAb Votes
#> 1 2025 Federal Election     QLD   100