Overlapping Annotations in Matplotlib

Matplotlib visualizations often encounter the issue of overlapping annotations, leading to cluttered and difficult-to-interpret graphs. This article provides a comprehensive solution to address this challenge.

The Herausforderung

Overlapping annotations arise when multiple annotations share the same screen space, creating visual clutter. In the provided code, the annotation text for data points tends to overlap, especially in denser regions of the graph.

The Lösung

To avoid overlapping annotations, the adjustText library, written by Phlya, offers a simple and effective solution. This library automatically adjusts the position of annotations to minimize overlaps while maintaining readability.

Using adjustText

The following code snippet demonstrates how to use adjustText to optimize annotation placement in the provided example:

import matplotlib.pyplot as plt
from adjustText import adjust_text

# ... (code to generate the data and plot remain the same as before) ...

plt.xlabel("Proportional Euclidean Distance")
plt.ylabel("Percentage Timewindows Attended")
plt.title("Test plot")

texts = [x for (x,y,z) in together]
eucs = [y for (x,y,z) in together]
covers = [z for (x,y,z) in together]

p1 = plt.plot(eucs,covers,color="black", alpha=0.5)
texts = []
for x, y, s in zip(eucs, covers, text):
    texts.append(plt.text(x, y, s))

adjust_text(texts, only_move={'points':'y', 'texts':'y'}, arrowprops=dict(arrowstyle="->", color='r', lw=0.5))
plt.show()

Customizing Text Placement

adjustText offers various customization options to fine-tune the placement of annotations. For instance, it allows you to control which elements are movable (only_move parameter), the alignment of annotations, and the strength of repulsion between text objects.

By experimenting with these parameters, you can achieve optimal text placement that maximizes clarity and visual appeal in your Matplotlib graphs without the worry of overlapping annotations.