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To plot a Chi-Square distribution in Python, you can use the following syntax:

#x-axis ranges from 0 to 20 with .001 steps x = np.arange(0, 20, 0.001) #plot Chi-square distribution with 4 degrees of freedom plt.plot(x, chi2.pdf(x, df=4))

The **x** array defines the range for the x-axis and the **plt.plot()** produces the curve for the Chi-square distribution with the specified degrees of freedom.

The following examples show how to use these functions in practice.

**Example 1: Plot a Single Chi-Square Distribution**

The following code shows how to plot a single Chi-square distribution curve with 4 degrees of freedom

import numpy as np import matplotlib.pyplot as plt from scipy.stats import chi2 #x-axis ranges from 0 to 20 with .001 steps x = np.arange(0, 20, 0.001) #plot Chi-square distribution with 4 degrees of freedom plt.plot(x, chi2.pdf(x, df=4))

You can also modify the color and the width of the line in the graph:

plt.plot(x, chi2.pdf(x, df=4), color='red', linewidth=3)

**Example 2: Plot Multiple Chi-Square Distributions**

The following code shows how to plot multiple Chi-square distribution curves with different degrees of freedom:

import numpy as np import matplotlib.pyplot as plt from scipy.stats import chi2 #x-axis ranges from 0 to 20 with .001 steps x = np.arange(0, 20, 0.001) #define multiple Chi-square distributions plt.plot(x, chi2.pdf(x, df=4), label='df: 4') plt.plot(x, chi2.pdf(x, df=8), label='df: 8') plt.plot(x, chi2.pdf(x, df=12), label='df: 12') #add legend to plot plt.legend()

Feel free to modify the colors of the lines and add a title and axes labels to make the chart complete:

import numpy as np import matplotlib.pyplot as plt from scipy.stats import chi2 #x-axis ranges from 0 to 20 with .001 steps x = np.arange(0, 20, 0.001) #define multiple Chi-square distributions plt.plot(x, chi2.pdf(x, df=4), label='df: 4', color='gold') plt.plot(x, chi2.pdf(x, df=8), label='df: 8', color='red') plt.plot(x, chi2.pdf(x, df=12), label='df: 12', color='pink') #add legend to plot plt.legend(title='Parameters') #add axes labels and a title plt.ylabel('Density') plt.xlabel('x') plt.title('Chi-Square Distributions', fontsize=14)

Refer to the matplotlib documentation for an in-depth explanation of the **plt.plot()** function.