categorical_eda: Categorical variable plotting

In UBC-MDS/RSimplerEDA: Simpler_eda_r

Description

This function takes in a dataframe object and one categorical feature, to produce a histogram plot that visualizes the distribution of the feature. User can also choose to plot density graph of the feature by specifying in plot_type. The function also offers customization on color, plot title, font size, color-scheme, plot size and other common configurations.

Usage

categorical_eda(
  data,
  xval,
  plot_type = "histogram",
  color = NULL,
  title = NULL,
  font_size = 10,
  color_scheme = "Tableau 20",
  opacity = 0.6,
  facet_factor = NULL,
  facet_col = NULL
)

Arguments

data	A tibble or a dataframe
xval	A variable used to represent the x-axis.
plot_type	An optional character variable used to specify plot type. Options include "histogram" and "density".
color	A character variable used to set the color variable of the plot
title	An optional character variable used to set the title of the plot
font_size	An optional integer variable used to set the font size
color_scheme	An optional character variable used to set the color shceme
opacity	An optional integer variable used to specify density fill opacity for the density plot
facet_factor	An optional character variable used to specify facet factor
facet_col	An optional numeric variable used to specify number of facet columns

Value

A ggplot2 object, either a histogram or a density plot

Examples

library(palmerpenguins)

categorical_plot <- categorical_eda(
  data = penguins,
  xval = body_mass_g,
  color = island,
  title = "Histogram of Body Mass in Different Sex",
  facet_factor = "island",
  facet_col = 1
)

UBC-MDS/RSimplerEDA documentation built on March 28, 2021, 9:34 p.m.