dop_irv: Get full distribution of preferences in each instant runoff...

In prefviz: Visualizes Preference Data via Ternary Plots in Two and Higher Dimensions

Get full distribution of preferences in each instant runoff voting round as percentage

Description

Compute the preference in each round of instant runoff voting from input data, transforming the results into a tidy format for visualization. Each row represents one round, with columns for each candidate's preference percentage and the election winner.

Usage

dop_irv(x, value_type = c("percentage", "count"), ...)

Arguments

x	Input data. Accepts the same formats as prefio::pref_irv(): A preference vector where each element represents one ballot A data frame with a column for preference
value_type	Character string specifying the output format. Either: "percentage" (default): Returns vote shares as proportions (0-1) "count": Returns raw vote counts
...	Additional arguments passed to prefio::pref_irv(), including: preferences_col: Column name containing preference orderings frequency_col: Column name containing vote frequencies

Value

A tibble with the following structure:

• round: Integer, the round number (1 to n)

• One column per candidate: Numeric, the percentage of votes (0-1) that candidate received in that round. NA values are replaced with 0 for eliminated candidates.

• winner: Character, the name of the eventual IRV winner (same for all rows)

Examples

# Example 1: From preference vector
votes <- prefio::preferences(c("A > B > C", "B > A > C", "C > B > A", "A > B > C"))
dop_irv(votes, value_type = "count")

# Example 2: From data frame with custom column names
vote_data <- tibble::tibble(
  prefs = prefio::preferences(c("A > B > C", "B > C > A", "C > A > B")),
  counts = c(100, 75, 25)
)
dop_irv(vote_data, value_type = "percentage",
        preferences_col = prefs,
        frequency_col = counts)

prefviz documentation built on April 13, 2026, 5:07 p.m.