Combined Frequencies Plot for Categorical Features

Plot frequencies of multiple categories within a data.frame in a new fancy way. Tidyverse friendly, based on lares::freqs(), no limits on amount of features to evaluate.

Usage

freqs_plot(
  df,
  ...,
  top = 10,
  rm.na = FALSE,
  abc = FALSE,
  title = NA,
  subtitle = NA
)

Arguments

df

Data.frame

...

Variables. Variables you wish to process. Order matters. If no variables are passed, the whole data.frame will be considered

top

Integer. Filter and plot the most n frequent for categorical values. Set to NA to return all values

rm.na

Boolean. Remove NA values in the plot? (not filtered for numerical output; use na.omit() or filter() if needed)

abc

Boolean. Do you wish to sort by alphabetical order?

title

Character. Overwrite plot's title with.

subtitle

Character. Overwrite plot's subtitle with.

Value

Plot. Result of the frequency of combined variables.

See also

Other Frequency: freqs(), freqs_df(), freqs_list()

Other Exploratory: corr_cross(), corr_var(), crosstab(), df_str(), distr(), freqs(), freqs_df(), freqs_list(), lasso_vars(), missingness(), plot_cats(), plot_df(), plot_nums(), tree_var()

Other Visualization: distr(), freqs(), freqs_df(), freqs_list(), noPlot(), plot_chord(), plot_survey(), plot_timeline(), tree_var()

Examples

Sys.unsetenv("LARES_FONT") # Temporal
data(dft) # Titanic dataset

df <- freqs_plot(dft, Pclass, Survived)
head(df$data)
#> # A tibble: 6 × 7
#>   order     n     p  pcum name     value label          
#>   <chr> <int> <dbl> <dbl> <chr>    <chr> <chr>          
#> 1 6        80  8.98 100   Pclass   1     Pclass: 1      
#> 2 6        80  8.98 100   Survived FALSE Survived: FALSE
#> 3 5        87  9.76  91.0 Pclass   2     Pclass: 2      
#> 4 5        87  9.76  91.0 Survived TRUE  Survived: TRUE 
#> 5 4        97 10.9   81.3 Pclass   2     Pclass: 2      
#> 6 4        97 10.9   81.3 Survived FALSE Survived: FALSE
plot(df)


freqs_plot(dft, Pclass, Survived, Sex, Embarked)
#> Showing 10 most frequent values. Tail of 22 other values grouped into one


freqs_plot(dft, Pclass, Survived, Sex, Embarked, top = 15)
#> Showing 15 most frequent values. Tail of 17 other values grouped into one