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Predictive Data Analysis with Python

Histogram Plots

Explore techniques to visualize numerical data distribution using histogram plots with Matplotlib and Seaborn. Learn to customize bins, colors, and transparency for single and multiple datasets. Understand how jointplot enhances multi-dataset histogram visualization for clearer data insights.

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Histogram

This visualization is used to display the distribution of numerical data as accurately as possible. This plot divides the data into a specified number of bins, thus separating the data into a range of values. Then, it sketches bars to show the number of data points that each bin contains.

Using matplotlib

Matplotlib provides the hist() function to plot a histogram. The following example implements a histogram of two-hundred random values.

Python 3.5
import numpy as np
import matplotlib.pyplot as plt
set1 = np.random.randn(200) # Generating random data
plt.hist(set1, edgecolor='black', color='red', bins=20) # plotting histogram

Two additional parameters are passed to the hist() function. The color parameter defines the color of the ...