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Test many reported percentages against their counts

Source: R/percentage-of-map.R
percentage_of_map.Rd

[Experimental]

percentage_of_map() applies percentage_of() to every row of a data frame with counts, percentages, and totals.

Call audit() on the output for summary statistics. See percentage_of() for causes of inconsistencies.

Usage

percentage_of_map(
  data,
  digits_percentage,
  absolute = NULL,
  percentage = NULL,
  n = NULL,
  ...,
  rounding = "up_or_down",
  threshold = 5,
  symmetric = FALSE
)

Arguments

data

Data frame with columns absolute, percentage, and n. Any other columns are returned alongside the results.

digits_percentage

Integer. The number of decimal places in percentage, including trailing zeros. There is no default, since a numeric value does not keep them (1.40 is 1.4). Either a single number for the whole column or one number per row of data. If left out, it is taken from a digits_percentage column of data.

absolute, percentage, n

Optionally, the names of the columns in data that contain these values, if they differ from the defaults.

...

These dots must be empty. Every argument after them must be named in full.

rounding, threshold, symmetric

The same as in grim().

Value

A tibble with the columns absolute, percentage, n, digits_percentage, consistency, and any other columns from data. It has the class scrutiny_percentage_of_map, which is recognized by audit().

Summaries with audit()

audit() on percentage_of_map() output returns a tibble with one row and these columns:

  1. all_cases: total number of value sets.

  2. incon_cases: number of inconsistent value sets.

  3. emp_incon: proportion of inconsistent value sets.

Examples

df <- tibble::tibble(
  absolute = c(40, 37, 25),
  percentage = c(33, 31, 20),
  n = 120
)

df |>
  percentage_of_map(digits_percentage = 0)
#> # A tibble: 3 × 5
#> # Percentage: default settings
#>   absolute percentage     n digits_percentage consistency
#>      <int>      <dbl> <int>             <int> <lgl>      
#> 1       40         33   120                 0 TRUE       
#> 2       37         31   120                 0 TRUE       
#> 3       25         20   120                 0 FALSE