Relabel factor levels with a function, collapsing as necessary

Relabel factor levels with a function, collapsing as necessary

Usage

fct_relabel(.f, .fun, ...)

Arguments

.f

A factor (or character vector).

.fun

A function to be applied to each level. Must accept one character argument and return a character vector of the same length as its input.

You can also use lambda notation, \(x). \(x) paste(x, "y") is equivalent to function(x) paste(x, "y") or function(.) paste(., "y").

...

Additional arguments to fun.

Examples

gss_cat$partyid |> fct_count()
#> # A tibble: 10 × 2
#>    f                      n
#>    <fct>              <int>
#>  1 No answer            154
#>  2 Don't know             1
#>  3 Other party          393
#>  4 Strong republican   2314
#>  5 Not str republican  3032
#>  6 Ind,near rep        1791
#>  7 Independent         4119
#>  8 Ind,near dem        2499
#>  9 Not str democrat    3690
#> 10 Strong democrat     3490
gss_cat$partyid |>
  fct_relabel(\(x) gsub(",", ", ", x)) |>
  fct_count()
#> # A tibble: 10 × 2
#>    f                      n
#>    <fct>              <int>
#>  1 No answer            154
#>  2 Don't know             1
#>  3 Other party          393
#>  4 Strong republican   2314
#>  5 Not str republican  3032
#>  6 Ind, near rep       1791
#>  7 Independent         4119
#>  8 Ind, near dem       2499
#>  9 Not str democrat    3690
#> 10 Strong democrat     3490

convert_income <- function(x) {
  regex <- "^(?:Lt |)[$]([0-9]+).*$"
  is_range <- grepl(regex, x)
  num_income <- as.numeric(gsub(regex, "\\1", x[is_range]))
  num_income <- trunc(num_income / 5000) * 5000
  x[is_range] <- paste0("Gt $", num_income)
  x
}
fct_count(gss_cat$rincome)
#> # A tibble: 16 × 2
#>    f                  n
#>    <fct>          <int>
#>  1 No answer        183
#>  2 Don't know       267
#>  3 Refused          975
#>  4 $25000 or more  7363
#>  5 $20000 - 24999  1283
#>  6 $15000 - 19999  1048
#>  7 $10000 - 14999  1168
#>  8 $8000 to 9999    340
#>  9 $7000 to 7999    188
#> 10 $6000 to 6999    215
#> 11 $5000 to 5999    227
#> 12 $4000 to 4999    226
#> 13 $3000 to 3999    276
#> 14 $1000 to 2999    395
#> 15 Lt $1000         286
#> 16 Not applicable  7043
convert_income(levels(gss_cat$rincome))
#>  [1] "No answer"      "Don't know"     "Refused"       
#>  [4] "Gt $25000"      "Gt $20000"      "Gt $15000"     
#>  [7] "Gt $10000"      "Gt $5000"       "Gt $5000"      
#> [10] "Gt $5000"       "Gt $5000"       "Gt $0"         
#> [13] "Gt $0"          "Gt $0"          "Gt $0"         
#> [16] "Not applicable"
rincome2 <- fct_relabel(gss_cat$rincome, convert_income)
fct_count(rincome2)
#> # A tibble: 10 × 2
#>    f                  n
#>    <fct>          <int>
#>  1 No answer        183
#>  2 Don't know       267
#>  3 Refused          975
#>  4 Gt $25000       7363
#>  5 Gt $20000       1283
#>  6 Gt $15000       1048
#>  7 Gt $10000       1168
#>  8 Gt $5000         970
#>  9 Gt $0           1183
#> 10 Not applicable  7043