Скачать или смотреть How to Fix Overlaying Plots on the Y-Axis in Matplotlib: A Step-by-Step Guide

Learn how to resolve the issue of plots not overlaying on the Y-axis in Matplotlib with this easy-to-follow guide. Start using plots effectively today!
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This video is based on the question https://stackoverflow.com/q/63892606/ asked by the user 'Leon Held' ( https://stackoverflow.com/u/7334797/ ) and on the answer https://stackoverflow.com/a/63892900/ provided by the user 'Jody Klymak' ( https://stackoverflow.com/u/3394386/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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How to Fix Overlaying Plots on the Y-Axis in Matplotlib: A Step-by-Step Guide

If you’re using Matplotlib to create plots, you may have run into a common issue where your plots don’t overlay correctly on the y-axis. This can result in your data being presented in a confusing manner, and can make it hard to interpret your results effectively. In this post, we’ll explore why this happens and how to fix it, ensuring your plots showcase your data correctly.

Understanding the Problem

When you want to display multiple data series on the same graph in Matplotlib, you expect them to overlay each other for better comparison. However, you may find that even though you are using the same x-axis (like frequency in your case), the plots are appearing one on top of the other rather than sharing the same y-axis.

This issue arises mainly from how you create and reference the plotting axis in your code. Let’s break down a typical scenario where this issue might occur, as outlined in a recent query we found:

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

In this code snippet, while the x-axis is appropriately set to a logarithmic scale, both plots are not actually overlaying each other as intended. So, how do we fix this?

The Solution: Use Subplots Correctly

To resolve this, you will need to effectively create a figure and explicitly reference the axes when plotting your data. This allows Matplotlib to understand that it should overlay the plots rather than create separate ones. Here’s how to do it:

Step-by-Step Guide

Create a new figure and axis: First, you need to create a figure and an axis object. This is done with the statement fig, ax = plt.subplots().

Plot your data: Use the ax object to plot your data instead of the generic plt module. This will ensure that your plots overlay properly.

Here’s how the corrected code looks:

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

Key Points to Remember

Use plt.subplots: This function helps in creating a specific plot area where you can add your data.

Reference your axis: Always plot your data using the ax object created from plt.subplots(). This designates that both plots will share the same axes.

Customizing your plots: Once you establish your plots correctly, you can further customize your axes with titles, labels, and legends to enhance clarity.

Conclusion

By following these simple adjustments, you should be able to get your plots overlaying on the y-axis in Matplotlib without any issues. Utilizing subplots not only fixes your current problem, but also opens up additional customization options for your visualizations.

If you find yourself repeatedly facing issues with plot overlays, remember this guide! Happy plotting!