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How to plot the difference of two distributions in Matplotlib?
To plot the difference of two distributions in Matplotlib, we can take the following steps −
Set the figure size and adjust the padding between and around the subplots.
Create a and b datasets using Numpy.
Get kdea and kdeb, i.e., representation of a kernel-density estimate using Gaussian kernels.
Create a grid using Numpy.
Plot the gird with kdea(grid), kdeb(grid) and kdea(grid)-kdeb(grid), using plot() method.
Place the legend at the upper-left corner.
To display the figure, use show() method.
Example
import numpy as np import matplotlib.pyplot as plt import scipy.stats plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True a = np.random.gumbel(50, 28, 100) b = np.random.gumbel(60, 37, 100) kdea = scipy.stats.gaussian_kde(a) kdeb = scipy.stats.gaussian_kde(b) grid = np.linspace(0, 50, 100) plt.plot(grid, kdea(grid), label="Kde A") plt.plot(grid, kdeb(grid), label="Kde B") plt.plot(grid, kdea(grid)-kdeb(grid), label="Difference") plt.legend(loc='upper left') plt.show()
Output
Updated on: 10-Aug-2021
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