Histograms can effectively represent the distribution of a variable. Here, we will visualize two normal distributions, both characterized by unit standard deviation, one having a mean of 0 and the other a mean of 3.0:
In: import numpy as np import matplotlib.pyplot as plt x = np.random.normal(loc=0.0, scale=1.0, size=500) z = np.random.normal(loc=3.0, scale=1.0, size=500) plt.hist(np.column_stack((x,z)), bins=20, histtype='bar', color = ['c','b'], stacked=True) plt.grid() plt.show()
The conjoint distributions can offer a different insight on the data if there is a classification problem:
There are a few ways to personalize ...
