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Learn how to add a `grid` to multiple matplotlib figures in Python with a simple technique to ensure clarity in your visual data representations.
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This video is based on the question https://stackoverflow.com/q/70633593/ asked by the user 'Lucas Schwartz' ( https://stackoverflow.com/u/9385136/ ) and on the answer https://stackoverflow.com/a/70633632/ provided by the user 'Kingshuk Basak' ( https://stackoverflow.com/u/8966443/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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How to Display the Grid in Multiple Matplotlib Charts at the Same Time

When working with data visualization in Python, especially using libraries like Matplotlib, the clarity of your charts is crucial. A common feature that enhances readability is the grid, which helps to interpret data points relative to one another.

However, if you've ever tried to include grids in multiple Matplotlib figures, you might have run into a problem: the grid only appears on one of the charts despite your efforts. This post will guide you through fixing this issue so that you can enhance your visualizations in multiple charts simultaneously.

Problem Overview

If you attempt to use the built-in command plt.grid() in your code, you may find that it applies only to the last figure created. This limitation can be frustrating, especially when dealing with multiple data representations that require clarity.

The challenge is to ensure that each chart separately incorporates its own gridlines. Let’s dive into how to achieve this.

Solution Breakdown

To display grids in multiple figures, you need to call the grid method for each axis object that you create.

Step-by-step Code Modification

Here’s a breakdown of the required changes in your code:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of Changes

Creating Separate Figure and Axes: By creating different figure objects (fig and fig1) and their respective axes, each figure can be independently manipulated.

Adding Grids Individually: The crucial addition here is the calls to axis.grid() and ax.grid(). This explicitly enables grids for both axes corresponding to their individual figures.

No Use of plt.grid(): By omitting the generic plt.grid() command, you ensure that the grid remains properly associated with the defined axes.

Conclusion

By following these steps, you can confidently add grids to multiple Matplotlib charts, enhancing their utility and readability. This is particularly valuable when you are analyzing significant amounts of data spread across various visual formats.

Now you can enjoy the clarity that grids provide in your data visualizations across separate charts without hassle. Happy plotting!