Plot two histograms on single chart with matplotlib Plot two histograms on single chart with matplotlib python python

Plot two histograms on single chart with matplotlib


Here you have a working example:

import randomimport numpyfrom matplotlib import pyplotx = [random.gauss(3,1) for _ in range(400)]y = [random.gauss(4,2) for _ in range(400)]bins = numpy.linspace(-10, 10, 100)pyplot.hist(x, bins, alpha=0.5, label='x')pyplot.hist(y, bins, alpha=0.5, label='y')pyplot.legend(loc='upper right')pyplot.show()

enter image description here


The accepted answers gives the code for a histogram with overlapping bars, but in case you want each bar to be side-by-side (as I did), try the variation below:

import numpy as npimport matplotlib.pyplot as pltplt.style.use('seaborn-deep')x = np.random.normal(1, 2, 5000)y = np.random.normal(-1, 3, 2000)bins = np.linspace(-10, 10, 30)plt.hist([x, y], bins, label=['x', 'y'])plt.legend(loc='upper right')plt.show()

enter image description here

Reference: http://matplotlib.org/examples/statistics/histogram_demo_multihist.html

EDIT [2018/03/16]: Updated to allow plotting of arrays of different sizes, as suggested by @stochastic_zeitgeist


In the case you have different sample sizes, it may be difficult to compare the distributions with a single y-axis. For example:

import numpy as npimport matplotlib.pyplot as plt#makes the datay1 = np.random.normal(-2, 2, 1000)y2 = np.random.normal(2, 2, 5000)colors = ['b','g']#plots the histogramfig, ax1 = plt.subplots()ax1.hist([y1,y2],color=colors)ax1.set_xlim(-10,10)ax1.set_ylabel("Count")plt.tight_layout()plt.show()

hist_single_ax

In this case, you can plot your two data sets on different axes. To do so, you can get your histogram data using matplotlib, clear the axis, and then re-plot it on two separate axes (shifting the bin edges so that they don't overlap):

#sets up the axis and gets histogram datafig, ax1 = plt.subplots()ax2 = ax1.twinx()ax1.hist([y1, y2], color=colors)n, bins, patches = ax1.hist([y1,y2])ax1.cla() #clear the axis#plots the histogram datawidth = (bins[1] - bins[0]) * 0.4bins_shifted = bins + widthax1.bar(bins[:-1], n[0], width, align='edge', color=colors[0])ax2.bar(bins_shifted[:-1], n[1], width, align='edge', color=colors[1])#finishes the plotax1.set_ylabel("Count", color=colors[0])ax2.set_ylabel("Count", color=colors[1])ax1.tick_params('y', colors=colors[0])ax2.tick_params('y', colors=colors[1])plt.tight_layout()plt.show()

hist_twin_ax


matomo