A cross-tabulation function with output similar to STATA, tidy friendly, with weighting possibility.
Usage
crosstab(
df,
...,
wt = NULL,
prow = FALSE,
pcol = FALSE,
pall = FALSE,
decimals = 2,
rm.na = FALSE,
total = TRUE,
order = TRUE
)Arguments
- df
Data.frame.
- ...
Variables. Dependent and independent variables.
- wt
Variable, numeric. Weights.
- prow, pcol, pall
Boolean. Calculate percent values for rows, columns, or the whole table, respectively.
- decimals
Integer. How many decimals should be returned?
- rm.na
Boolean. Remove NA values?
- total
Boolean. Return total values column?
- order
Boolean. Sort columns and rows by frequencies? Else, will be sorted alphabetically
Value
data.frame. Result of crossing the variables provided in ... and
counting how many observations (rows) fall into each criteria.
See also
Other Exploratory:
corr_cross(),
corr_var(),
df_str(),
distr(),
freqs_df(),
freqs_list(),
freqs_plot(),
freqs(),
lasso_vars(),
missingness(),
plot_cats(),
plot_df(),
plot_nums(),
tree_var()
Examples
data(dft) # Titanic dataset
crosstab(dft, Survived, Pclass, total = FALSE)
#> # A tibble: 2 × 4
#> `Survived x Pclass` `3` `1` `2`
#> <fct> <int> <int> <int>
#> 1 FALSE 372 80 97
#> 2 TRUE 119 136 87
# Show values in percentages
crosstab(dft, Pclass, Survived, prow = TRUE)
#> # A tibble: 3 × 4
#> `Pclass x Survived` `FALSE` `TRUE` total
#> <fct> <dbl> <dbl> <dbl>
#> 1 3 67.8 34.8 55.1
#> 2 1 14.6 39.8 24.2
#> 3 2 17.7 25.4 20.6
crosstab(dft, Pclass, Survived, pall = TRUE)
#> # A tibble: 3 × 4
#> `Pclass x Survived` `FALSE` `TRUE` total
#> <fct> <dbl> <dbl> <dbl>
#> 1 3 41.8 13.4 55.1
#> 2 1 8.98 15.3 24.2
#> 3 2 10.9 9.76 20.6
# Weighted by another variable
crosstab(dft, Survived, Pclass, wt = Fare, prow = TRUE)
#> # A tibble: 2 × 5
#> `Survived x Pclass` `1` `3` `2` total
#> <fct> <dbl> <dbl> <dbl> <dbl>
#> 1 TRUE 71.5 24.3 50.5 57.7
#> 2 FALSE 28.5 75.7 49.5 42.3