Matplotlib Python Subplots

In this Matplotlib tutorial we want to learn about Matplotlib Python Subplots, when you are doing data visualization, then you will need to display multiple plots side by side to compare and contrast different aspects of the data. Python Matplotlib library provides a powerful feature called subplots, and it allows us to create multiple plots inside a single figure.



First of all you need to install Matplotlib and you can use pip for that.



After that we need to import our required modules from Python Matplotlib.



For creating subplots, we use the plt.subplots() function. This function returns a figure object and an array of axes objects, which represent each subplot. We can specify the number of rows and columns of subplots we want using the nrows and ncols parameters.



After that we have the subplots, we can plot our data on each subplot individually using the axes objects. We can access the axes using indexing notation.




Matplotlib provides different customization options for subplots. You can set titles, labels, legends, adjust axis limits and more on each individual subplot.



If the subplots overlap or have insufficient space, we can adjust the layout using the plt.tight_layout() function. This ensures that all subplots are properly spaced and visible.




To displaying the subplots, we can use the function.





This is the complete code for this article




Run the code and this will be the output

Matplotlib Python Subplots
Matplotlib Python Subplots



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