This function differs from cat_vcount in that it operates on columns
in dataframes rather than directly on vectors, which means it is more useful
in pipelines but handles a narrower range of inputs. The results are sorted
in descending order of frequency.
cat_count(
data,
cat,
na.rm = FALSE,
only = "",
clean_names = getOption("tabbycat.clean_names")
)A tibble showing the frequency of each value in cat.
A dataframe containing a categorical vector for which frequencies will be calculated.
The column name of the categorical variable for which frequencies will be calculated.
A boolean indicating whether to exclude NAs from the results. The default is FALSE.
A string indicating that only one of the frequency columns
should be returned in the results. If only is either "n" or
"number", only the number column is returned. If only is either
"p" or "percent", only the percent column is returned. If only is
any other value, both columns are shown. The default value is an empty
string, which means both columns are shown.
A boolean indicating whether the column names of the
results tibble should be cleaned, so that any column names produced from
data are converted to snake_case. The default is TRUE, but this can be
changed with options(tabbycat.clean_names = FALSE).