cat_group_tbl() summarizes nominal or categorical
variables by a grouping variable, returning frequency counts and
percentages.
cat_group_tbl(
data,
row_var,
col_var,
margins = "all",
na.rm.row_var = FALSE,
na.rm.col_var = FALSE,
pivot = "longer",
only = NULL,
ignore = NULL
)A data frame.
A character string of the name of a variable in data
containing categorical data. This is the primary categorical variable.
A character string of the name of a variable in data
containing categorical data. This is the secondary categorical variable.
A character string that determines how percentage values
are calculated; whether they sum to one across rows, columns, or the
entire table (i.e., all). Defaults to all, but can also be set to
rows or columns.
A logical value indicating whether missing values for
row_var should be removed before calculations. Default is FALSE.
A logical value indicating whether missing values for
col_var should be removed before calculations. Default is FALSE.
A character string that determines the format of the table. By
default, longer returns the data in the long format. To return the data in
the wide format, specify wider.
A character string or vector of character strings of the types
of summary data to return. Default is NULL, which returns both counts and
percentages. To return only counts or percentages, use count or percent,
respectively.
An optional named vector or list that defines values to exclude
from row_var and col_var. If set to NULL (default), all values are retained.
To exclude multiple values from row_var or col_var, provide them as a named
list.
A tibble showing the count and percentage of each category in row_var
by each category in col_var.
cat_group_tbl(data = nlsy,
row_var = "gender",
col_var = "bthwht",
pivot = "wider",
only = "count")
#> # A tibble: 2 × 3
#> gender count_bthwht_0 count_bthwht_1
#> <dbl> <int> <int>
#> 1 0 1340 123
#> 2 1 1409 104
cat_group_tbl(data = nlsy,
row_var = "birthord",
col_var = "breastfed",
pivot = "longer")
#> # A tibble: 16 × 4
#> birthord breastfed count percent
#> <dbl> <dbl> <int> <dbl>
#> 1 1 0 431 0.145
#> 2 1 1 614 0.206
#> 3 2 0 573 0.193
#> 4 2 1 499 0.168
#> 5 3 0 319 0.107
#> 6 3 1 242 0.0813
#> 7 4 0 115 0.0386
#> 8 4 1 77 0.0259
#> 9 5 0 49 0.0165
#> 10 5 1 23 0.00773
#> 11 6 0 13 0.00437
#> 12 6 1 11 0.00370
#> 13 7 0 7 0.00235
#> 14 7 1 1 0.000336
#> 15 8 0 1 0.000336
#> 16 8 1 1 0.000336