Count a categorical question as percentages

The headline helper: replaces the ubiquitous count(x) %>% mutate(pct = round(n / sum(n) * 100)) %>% select(-n) dance with a single call. Returns both the raw counts and the percentages, optionally grouped by one or more variables and optionally pivoted to a wide cross-tabulation.

Usage

calc_percentage(
  data = NULL,
  column,
  by = NULL,
  sort = c("none", "desc", "asc"),
  levels = NULL,
  digits = 0,
  wide = FALSE,
  na_rm = TRUE,
  drop = NULL,
  weights = NULL
)

Arguments

data

A data frame. If omitted, the session default set with use_dataset() is used.

column

The categorical column to tabulate (unquoted).

by

Optional grouping column(s). Percentages are computed within each group so they sum to ~100 per group. Pass one bare name (by = year) or several with c() (by = c(year, game)).

sort

Level ordering of column: "none" (default, data order), "desc" (largest percentage first) or "asc".

levels

Optional character vector giving an explicit level order for column (the "custom" ordering mode). Overrides sort. If omitted and sort = "none", a registered order for this variable is applied automatically (see register_order()), and failing that a factor keeps its own level order.

digits

Decimal places for the percentage. Defaults to 0.

wide

If TRUE, pivot to one row per by group and one column per answer (dropping n), the shape a wide summary table needs. Defaults to FALSE (tidy long form).

na_rm

If TRUE (default), blanks and "Prefer not to answer" responses (see na_blank()) are dropped before counting.

drop

Optional character vector of answer values to remove before counting (e.g. c("Other", "Don't know")), so the kept answers re-base to ~100%. Matching is case-insensitive (see drop_items()). Defaults to the drop_answers option (NULL = drop nothing; see ezrsurvey_options()).

weights

Survey weighting for this call: NULL (default) uses the session scheme from set_weights() if one is set; FALSE forces unweighted; or pass an ad-hoc scheme (any form set_weights() accepts) to weight just this call. When weighting is active a wpct column (weighted percentage) is added beside n and pct.

Value

A tibble with column, n and pct (and wpct when weighting is active) in long form, or one row per group with an answer column each (wide form).

Details

Percentages are computed within each group, so they sum to about 100 per group (subject to rounding). The level order of column is decided in this order of precedence: an explicit levels argument; then a non-"none" sort; then a registered order for the variable (see register_order()); then the column's own levels, when it is a factor; otherwise data order. When by is omitted, the default_by option is used if set (see ezrsurvey_options()), so you can apply a standard breakdown without repeating it. wide = TRUE pivots to one row per group with a column per answer – the shape you want for a slide table or an Excel tab.

See also

calc_percentage_multi() for check-all-that-apply questions, calc_percentage_batch() for many questions at once, calc_summary() for numeric variables, register_order() for reusable level orders.

Other summaries: calc_percentage_batch(), calc_percentage_multi(), calc_summary(), clear_checkpoints(), crosstab(), crosstab_banner()

Examples

calc_percentage(podracing_survey, demo_gender)
#> # A tibble: 3 × 3
#>   demo_gender     n   pct
#>   <chr>       <int> <dbl>
#> 1 Female        399    42
#> 2 Male          525    55
#> 3 Non-binary     27     3

# largest first
calc_percentage(podracing_survey, demo_gender, sort = "desc")
#> # A tibble: 3 × 3
#>   demo_gender     n   pct
#>   <fct>       <int> <dbl>
#> 1 Male          525    55
#> 2 Female        399    42
#> 3 Non-binary     27     3

# grouped and pivoted to a wide cross-tab
calc_percentage(podracing_survey, satis_return, by = region, wide = TRUE)
#> # A tibble: 5 × 6
#>   region        Likely `Not sure` Unlikely `Very likely` `Very unlikely`
#>   <chr>          <dbl>      <dbl>    <dbl>         <dbl>           <dbl>
#> 1 Asia              24         25       12            34               5
#> 2 Europe            28         25       16            25               6
#> 3 Latin America     30         21       11            28              10
#> 4 North America     26         24       17            24               8
#> 5 Oceania           31         12       24            24              10