How to Add Interactive Hovering Annotations to Matplotlib Scatter Plots?

Adding Hovering Annotations to a Scatter Plot

Introduction

Matplotlib, a popular Python library, provides robust tools for visualizing data. It allows the creation of scatter plots, where each point represents a data value. However, when dealing with a large number of points, it can be difficult to identify individual points without adding annotations to them. This article demonstrates how to add hovering annotations to a scatter plot, making it easier to explore and understand the data.

Implementation

The code provided below demonstrates the creation of a scatter plot with hovering annotations. The key features of the code are:

1. Scatter Plot Creation: The scatter plot is created using the plt.scatter() function, where each point is assigned a color based on a numerical value using the c parameter.
2. Annotation Initialization: An annotation object is created using the ax.annotate() function. This annotation is initially invisible.
3. Hovering Event Handler: The fig.canvas.mpl_connect() function is used to create an event handler that detects cursor hovering over the scatter plot.
4. Annotation Update: When the cursor hovers over a point, the event handler updates the annotation's position, text, and color based on the selected point.
5. Annotation Visibility: The annotation is set to be visible when the cursor hovers over a point and hidden when it moves away.

Result

The output is an interactive scatter plot where hovering over any point reveals its associated text annotation. This allows for quick identification and analysis of individual data points, enhancing the usefulness of the plot.

Alternative Solution for Line Plots

The same approach can be applied to line plots by modifying the event handling statements to work with line segments instead of scatter points. The code provided in the context also includes an example for adding hovering annotations to a line plot.

Conclusion

Hovering annotations are a valuable addition to scatter and line plots, providing a user-friendly way to explore and understand data. The code presented here offers a simple and effective solution that allows for easy integration of this functionality into Python plots.

The above is the detailed content of How to Add Interactive Hovering Annotations to Matplotlib Scatter Plots?. For more information, please follow other related articles on the PHP Chinese website!