Returns the count-by-count distribution of preferences for every division: each exclusion round, the candidate excluded, and where their preferences flowed. This is the dataset for analysing seats won from second or third place on preference flows, which division-level TPP and TCP figures cannot show.
Arguments
- year
Election year. Use
list_elections()to see available years.- refresh
If
TRUE, re-download from the AEC even if a cached copy exists. Useful on election night when counts are still updating.
Value
A tidy data frame with one row per candidate per count per
division, including countnumber, calculationtype
(preference count, transfer count, and percentages), and
calculationvalue.
Examples
# \donttest{
op <- options(readaec.cache_dir = tempdir())
dop <- get_dop(2025)
#> Downloading from AEC: HouseDopByDivisionDownload-31496.csv
# Final count in a single seat
mel <- subset(dop, division == "Melbourne")
subset(mel, countnumber == max(countnumber))
#> # A tibble: 28 × 15
#> state division_id division countnumber ballotposition candidateid surname
#> <chr> <dbl> <chr> <dbl> <dbl> <dbl> <chr>
#> 1 VIC 228 Melbourne 5 1 41607 CASEY
#> 2 VIC 228 Melbourne 5 1 41607 CASEY
#> 3 VIC 228 Melbourne 5 1 41607 CASEY
#> 4 VIC 228 Melbourne 5 1 41607 CASEY
#> 5 VIC 228 Melbourne 5 2 40817 WITTY
#> 6 VIC 228 Melbourne 5 2 40817 WITTY
#> 7 VIC 228 Melbourne 5 2 40817 WITTY
#> 8 VIC 228 Melbourne 5 2 40817 WITTY
#> 9 VIC 228 Melbourne 5 3 42101 SMITH
#> 10 VIC 228 Melbourne 5 3 42101 SMITH
#> # ℹ 18 more rows
#> # ℹ 8 more variables: given_name <chr>, party <chr>, party_name <chr>,
#> # elected <chr>, historicelected <chr>, calculationtype <chr>,
#> # calculationvalue <dbl>, year <dbl>
options(op)
# }