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Скачать или смотреть Create a Stunning Scatter Plot with Empty Circles in Python

  • vlogize
  • 2025-09-14
  • 0
Create a Stunning Scatter Plot with Empty Circles in Python
scatter plot with empty circle within looppythonmatplotlibplotscatter plot
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Описание к видео Create a Stunning Scatter Plot with Empty Circles in Python

Learn how to create a scatter plot in Python using Matplotlib, featuring empty circles as markers and applying automatic color assignment for maximum visual appeal.
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This video is based on the question https://stackoverflow.com/q/62410226/ asked by the user 'Vinod Kumar' ( https://stackoverflow.com/u/7298014/ ) and on the answer https://stackoverflow.com/a/62410286/ provided by the user 'BlackBear' ( https://stackoverflow.com/u/521776/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: scatter plot with empty circle within loop

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
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How to Create a Stunning Scatter Plot with Empty Circles in Python

Visualizing data through graphs is an essential part of data analysis. Among various forms of data visualization, scatter plots are particularly useful for displaying relationships between two variables. In this guide, we're going to tackle a common problem faced by many who wish to create a scatter plot with empty circles as markers using Python’s Matplotlib library.

The Problem

You may have come across a situation where you want to plot multiple arrays on a scatter plot using empty circles (bordered markers) while ensuring that the colors are assigned automatically. In traditional plots, filled circles can be easily rendered, but introducing empty circles often makes them disappear or appear too bland if not styled correctly.

Simple Example: Filled Circles

To demonstrate the issue, here's a snippet of code that successfully creates a scatter plot with filled circles:

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

The Challenge

When you attempt to use the facecolor='none' option for empty circles, the markers might not appear as intended. The obvious question is: How can we address this issue while still making the markers visually appealing?

The Solution

To create a scatter plot with empty circles and have the markers properly displayed, we can manually assign edge colors that correspond to the default color palette of Matplotlib. Let’s break down the steps involved in the solution.

1. Initialize Your Data

Just as in the earlier example, you will start by creating a dictionary of arrays:

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

2. Set Up the Plot

You will need to create a figure and axis object using Matplotlib:

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

3. Loop Through Your Data

The key to making this work is using an enumeration loop to create scatter plots for each array (y) while assigning colors for the edge of the markers:

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

4. Show the Plot

Finally, don’t forget to display your plot:

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

Complete Code Example

Here is the complete code for your scatter plot with empty circles:

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

Conclusion

Creating a scatter plot with empty circles in Python is straightforward once you understand how to manage color assignments manually. By following the outlined steps, you'll ensure your data is presented in an engaging and visually appealing manner.

Now, get out there and experiment with your own data to create stunning scatter plots!

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