Histograms are powerful visualizations that show the number of occurrences for each value of a variable, creating a distribution of results. Sometimes it's useful to plot multiple distributions in a single plot where bars from different distributions are adjacent to each other. This is often called a grouped histogram, and it's easily accomplished using Matplotlib.
To create plot with multiple histograms for different groups, organize your data into separate arrays according to their group and pass them to
import matplotlib.pyplot as plt group1 = [1, 1, 1, 2, 2, 3, 4] group2 = [2, 2, 2, 1, 1, 3, 1, 4] # Create a stacked histogram here plt.hist([group1, group2], bins=[1, 2, 3, 4, 5], rwidth=0.9, align="left") plt.legend(["Group 1", "Group 2"]) plt.xticks([1, 2, 3, 4]) plt.ylabel("Quantity") plt.xlabel("Value") plt.show()
To plot additional histograms, simply add more arrays to the list passed to
plt.hist(). These arrays do not need to be the same length, as
plt.hist() simply counts the occurrences different values in each array.