In my previous posts, we have seen how we can plot stacked histogram (filled) and a stacked Step histogram (unfilled). In this post, we will see how we can plot multiple histograms with different length using Python’s Matplotlib library on the same axis.

Basically, Histograms are a graphical representation of a frequency distribution of numerical data and it’s a great visualizing tool for quickly assessing a probability distribution of a continuous variable (quantitative variable). Here we have three values in an array and we will plot three different coloured histograms on the same axis.

**First** of all, to create any type of histogram whether it’s a simple histogram or a stacked histogram, we need to import libraries that will help us to implement our task.

Below are the two libraries Numpy and Matplotlib which helps us to perform our task:

import numpy as np from Matplotlib.pyplot as plt

**Let’s plot multiple histograms with different length using Python’s Matplotlib library:**

The below code will create the stacked step histogram (unfilled) using Python’s Matplotlib library. To plot, we have created an array with three values [] and then passed the array into np.random.randn() using for loop so that Matplotlib library can plot multiple histograms with different length on the same axis. Have a look at the below code:

n_bins=30 colors = ['blue', 'orange', 'green'] # Make a multiple-histogram of array of three values with different length. array = [10000, 5000, 2000] x_multi = [np.random.randn(n) for n in array ] plt.hist(x_multi, n_bins, histtype='bar', label=colors) plt.legend(loc="upper right") plt.title('Different Sample Sizes') plt.show()

Hope you like our post. To learn more about Matplotlib package, you can go through the official documentation here.

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