In this Matplotlib tutorial we want to learn How to Create Histogram in Python Matplotlib, histograms are a powerful tool in data visualization, and it allows us to analyze the distribution and frequency of values within a dataset. Python Matplotlib library provides a simple and effective way to create histograms.
For creating histogram in matplotlib, we need to import the required modules.
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import matplotlib.pyplot as plt import numpy as np |
For creating of histogram, we need to generate some random data using numpy random.randn() function. This will give us an array of random numbers with a normal distribution.
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data = np.random.randn(1000) |
Using Matplotlib hist() function, we can create a histogram based on the generated data.
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plt.hist(data, bins=30, color='skyblue', edgecolor='black') |
Matplotlib provides different customization options to enhance the appearance of the histogram. You can add labels, change colors, adjust the bin size and many more.
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plt.xlabel('Values') plt.ylabel('Frequency') plt.title('Histogram') |
For displaying the histogram, we can use the plt.show() function.
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plt.show() |
If you wish to save the histogram as an image, you can use the plt.savefig() function instead.
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plt.savefig('histogram.png') |
This is the complete code for this article
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import matplotlib.pyplot as plt import numpy as np # Generate Sample Data data = np.random.randn(1000) # Create the Histogram plt.hist(data, bins=30, color='skyblue', edgecolor='black') # Customize the Histogram plt.xlabel('Values') plt.ylabel('Frequency') plt.title('Histogram') # Display the Histogram plt.show() # Save the Histogram as an Image # plt.savefig('histogram.png') |
Run your code and this will be the output
