Multi-Histogram Distributions

Comparing histograms across classes can provide useful information about the nature of the data you are working with. The implementation belows demostrates how to achieve this using ggplot. I begin by generating random data for the distribution.

library(ggthemr)
library(ggplot2)

ggthemr("dust")


x = rnorm(n = 10000, mean = 21, sd = 1.5)
y = rnorm(n = 10000, mean = 25, sd = 1.5)
z = rnorm(n = 10000, mean = 19, sd = 1.8)

data = data.frame( values = c(x, y, z),
    class = rep(c("A", "B", "C"), each = length(x)))

head(data)

A data.frame: 6 × 2

	values	class
1	23.74437	A
2	16.92297	A
3	19.04337	A
4	19.34535	A
5	21.86623	A
6	20.00213	A

options(repr.plot.width = 10, repr.plot.height = 8)

histograms = ggplot( data, aes( x = values, 
                                fill = class )) +
                        geom_histogram( color = "black", bins=30) +
                        ggtitle("Multi-Class Histogram Distribution Plot ")

histograms