Add turnout to referendum data

Augments data with an additional column turnout containing the voter turnout calculated as:

$$\frac{votes\_yes+votes\_no+votes\_empty+votes\_invalid}{electorate\_total}$$

Usage

add_turnout(data, rough = TRUE, excl_dubious = TRUE)

Arguments

data

RDB referendum data as returned by rfrnds(). A data frame that at minimum contains the columns electorate_total, votes_yes, votes_no, votes_empty and votes_invalid.

rough

Whether to fall back on a "rough" calculation of the turnout in case any of the variables votes_empty or votes_invalid is unknown (NA), or to be strict and return NA in such a case.

excl_dubious

Whether or not to exclude obviously dubious turnout numbers (those > 1.0) by setting them to NA. Such numbers stem either from data errors or (officially) tampered numbers.

Value

A tibble.

See also

Other referendum data augmentation functions: add_country_code_continual(), add_country_code_long(), add_country_name_long(), add_country_name(), add_former_country_flag(), add_period(), add_urls(), add_world_regions()

Examples

# rough turnout numbers
rdb::rfrnds(quiet = TRUE) |>
  rdb::add_turnout() |>
  dplyr::select(id,
                electorate_total,
                starts_with("votes_"),
                turnout)
#> # A tibble: 17,766 × 8
#>    id                       electorate_total votes_yes votes_no votes_empty votes_invalid votes_per_subterritory turnout
#>    <chr>                               <int>     <int>    <int>       <int>         <int> <list>                   <dbl>
#>  1 65096e84481d20233932cc70         29532595    608254 10675211           0        173734 <NULL>                   0.388
#>  2 65096dc1481d20233932cc6e         29532595    608254 10675211           0        799123 <NULL>                   0.409
#>  3 65096535481d20233932cc66         29532595    445270 10808410           0        828908 <NULL>                   0.409
#>  4 6509625d481d20233932cc63         29532595    360803 10878863           0        842922 <NULL>                   0.409
#>  5 650034e4481d20233932cc39         17671784   6286894  9452792           0        155545 <NULL>                   0.899
#>  6 64e46f7a481d20233932cc0b         13045553   5541585  3859507      841696        574474 <NULL>                   0.829
#>  7 64e46c8f481d20233932cc09               NA        NA       NA          NA            NA <NULL>                  NA    
#>  8 64c8b3ca0b8bae0c78c7ec8a               NA        NA       NA          NA            NA <NULL>                  NA    
#>  9 64c8b19c0b8bae0c78c7ec86               NA        NA       NA          NA            NA <NULL>                  NA    
#> 10 64c8a28d0b8bae0c78c7ec82               NA        NA       NA          NA            NA <NULL>                  NA    
#> # ℹ 17,756 more rows

# strict turnout numbers
rdb::rfrnds(quiet = TRUE) |>
  rdb::add_turnout(rough = FALSE) |>
  dplyr::select(id,
                electorate_total,
                starts_with("votes_"),
                turnout)
#> # A tibble: 17,766 × 8
#>    id                       electorate_total votes_yes votes_no votes_empty votes_invalid votes_per_subterritory turnout
#>    <chr>                               <int>     <int>    <int>       <int>         <int> <list>                   <dbl>
#>  1 65096e84481d20233932cc70         29532595    608254 10675211           0        173734 <NULL>                   0.388
#>  2 65096dc1481d20233932cc6e         29532595    608254 10675211           0        799123 <NULL>                   0.409
#>  3 65096535481d20233932cc66         29532595    445270 10808410           0        828908 <NULL>                   0.409
#>  4 6509625d481d20233932cc63         29532595    360803 10878863           0        842922 <NULL>                   0.409
#>  5 650034e4481d20233932cc39         17671784   6286894  9452792           0        155545 <NULL>                   0.899
#>  6 64e46f7a481d20233932cc0b         13045553   5541585  3859507      841696        574474 <NULL>                   0.829
#>  7 64e46c8f481d20233932cc09               NA        NA       NA          NA            NA <NULL>                  NA    
#>  8 64c8b3ca0b8bae0c78c7ec8a               NA        NA       NA          NA            NA <NULL>                  NA    
#>  9 64c8b19c0b8bae0c78c7ec86               NA        NA       NA          NA            NA <NULL>                  NA    
#> 10 64c8a28d0b8bae0c78c7ec82               NA        NA       NA          NA            NA <NULL>                  NA    
#> # ℹ 17,756 more rows