Make a list with all categorical values and
Value
List. Length same as number of categorical columns, each with a
frequency data.frame using freqs().
See also
Other Tools:
autoline(),
bind_files(),
bring_api(),
chr2num(),
db_download(),
db_upload(),
dont_sleep(),
export_plot(),
export_results(),
files_functions(),
font_exists(),
formatColoured(),
formatHTML(),
glued(),
grepm(),
h2o_selectmodel(),
haveInternet(),
image_metadata(),
importxlsx(),
ip_data(),
json2vector(),
listfiles(),
mail_send(),
markdown2df(),
move_files(),
msplit(),
myip(),
quiet(),
read.file(),
statusbar(),
tic(),
try_require(),
updateLares(),
warnifnot(),
what_size()
Examples
data(dft) # Titanic dataset
df <- dft[, 1:5]
head(df)
#> PassengerId Survived Pclass Sex Age
#> 1 1 FALSE 3 male 22
#> 2 2 TRUE 1 female 38
#> 3 3 TRUE 3 female 26
#> 4 4 TRUE 1 female 35
#> 5 5 FALSE 3 male 35
#> 6 6 FALSE 3 male NA
list_cats(df)
#> $Pclass
#> # A tibble: 3 × 3
#> Pclass n p
#> <chr> <int> <dbl>
#> 1 1 216 24.2
#> 2 2 184 20.6
#> 3 3 491 55.1
#>
#> $Sex
#> # A tibble: 2 × 3
#> Sex n p
#> <chr> <int> <dbl>
#> 1 female 314 35.2
#> 2 male 577 64.8
#>