Producing multiple histograms side by side#
This example plots horizontal histograms of different samples along a categorical x-axis. Additionally, the histograms are plotted to be symmetrical about their x-position, thus making them very similar to violin plots.
To make this highly specialized plot, we can't use the standard
method. Instead, we use
barh to draw the horizontal bars directly. The
vertical positions and lengths of the bars are computed via the
np.histogram function. The histograms for all the samples are
computed using the same range (min and max values) and number of bins,
so that the bins for each sample are in the same vertical positions.
Selecting different bin counts and sizes can significantly affect the shape of a histogram. The Astropy docs have a great section on how to select these parameters: http://docs.astropy.org/en/stable/visualization/histogram.html
import numpy as np import matplotlib.pyplot as plt np.random.seed(19680801) number_of_bins = 20 # An example of three data sets to compare number_of_data_points = 387 labels = ["A", "B", "C"] data_sets = [np.random.normal(0, 1, number_of_data_points), np.random.normal(6, 1, number_of_data_points), np.random.normal(-3, 1, number_of_data_points)] # Computed quantities to aid plotting hist_range = (np.min(data_sets), np.max(data_sets)) binned_data_sets = [ np.histogram(d, range=hist_range, bins=number_of_bins) for d in data_sets ] binned_maximums = np.max(binned_data_sets, axis=1) x_locations = np.arange(0, sum(binned_maximums), np.max(binned_maximums)) # The bin_edges are the same for all of the histograms bin_edges = np.linspace(hist_range, hist_range, number_of_bins + 1) heights = np.diff(bin_edges) centers = bin_edges[:-1] + heights / 2 # Cycle through and plot each histogram fig, ax = plt.subplots() for x_loc, binned_data in zip(x_locations, binned_data_sets): lefts = x_loc - 0.5 * binned_data ax.barh(centers, binned_data, height=heights, left=lefts) ax.set_xticks(x_locations, labels) ax.set_ylabel("Data values") ax.set_xlabel("Data sets") plt.show()
The use of the following functions, methods, classes and modules is shown in this example: