How to Make a Bell Curve in Python?

How to Make a Bell Curve in Python?

Creating a bell curve essentially means plotting the probability density function (PDF) of a normal (Gaussian) distribution. The bell curve is symmetric, and its peak represents the mean (and also the median and mode) of the distribution.

Here's how you can make a bell curve in Python using the numpy and matplotlib libraries:

  • First, you need to set up the libraries. If you haven't installed them yet:
pip install numpy matplotlib
  • Here's a Python script to plot a bell curve:
import numpy as np import matplotlib.pyplot as plt # Define the parameters for the normal distribution, # where mu is the mean and sigma is the standard deviation. mu, sigma = 0, 0.1 # Create a series of numbers that will be used as the x-axis values x = np.linspace(mu - 3*sigma, mu + 3*sigma, 100) # Calculate the corresponding PDF values for each x y = (1 / (sigma * np.sqrt(2 * np.pi))) * np.exp(- 0.5 * ((x - mu) / sigma)**2) # Plot the bell curve plt.plot(x, y, '-o', color='blue', markersize=2) plt.title('Bell Curve (Normal Distribution)') plt.xlabel('Value') plt.ylabel('Density') plt.show()

This script will display a bell curve centered at mu (mean = 0) with a standard deviation of sigma (0.1). Adjust the mu and sigma values as needed. The x values cover a range of ��3 standard deviations from the mean, which usually covers about 99.7% of the data in a normal distribution.

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