Histogram with several groups - ggplot2

# library library(ggplot2) library(dplyr) library(hrbrthemes) # Build dataset with different distributions data <- data.frame( type = c( rep("variable 1", 1000), rep("variable 2", 1000) ), value = c( rnorm(1000), rnorm(1000, mean=4) ) ) # Represent it p <- data %>% ggplot( aes(x=value, fill=type)) + geom_histogram( color="#e9ecef", alpha=0.6, position = 'identity') + scale_fill_manual(values=c("#69b3a2", "#404080")) + theme_ipsum() + labs(fill="")

If the number of group you need to represent is high, drawing them on the same axis often results in a cluttered and unreadable figure.

A good workaroung is to use small multiple where each group is represented in a fraction of the plot window, making the figure easy to read. This is pretty easy to build thanks to the facet_wrap() function of ggplot2.

Note: read more about the dataset used in this example here.

# Libraries
library(tidyverse)
library(hrbrthemes)
library(viridis)
library(forcats)

# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/zonination/perceptions/master/probly.csv", header=TRUE, sep=",")
data <- data %>%
  gather(key="text", value="value") %>%
  mutate(text = gsub("\\.", " ",text)) %>%
  mutate(value = round(as.numeric(value),0))

# plot
p <- data %>%
  mutate(text = fct_reorder(text, value)) %>%
  ggplot( aes(x=value, color=text, fill=text)) +
    geom_histogram(alpha=0.6, binwidth = 5) +
    scale_fill_viridis(discrete=TRUE) +
    scale_color_viridis(discrete=TRUE) +
    theme_ipsum() +
    theme(
      legend.position="none",
      panel.spacing = unit(0.1, "lines"),
      strip.text.x = element_text(size = 8)
    ) +
    xlab("") +
    ylab("Assigned Probability (%)") +
    facet_wrap(~text)

Histogram with several groups - ggplot2

Several histograms on the same axis

Using small multiple

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