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Python

Python Plot Legend Outside: A Step-by-Step Guide

By Filip on 10/04/2024

Learn different methods to effortlessly position your plot's legend outside the plotting area in Python for enhanced readability and aesthetic appeal.

Python Plot Legend Outside: A Step-by-Step Guide

Table of Contents

Introduction

In this tutorial, we'll learn how to place the legend outside of a Matplotlib plot in Python. This is particularly useful when the legend overlaps with the plot elements, making it difficult to read. We'll use the matplotlib.pyplot module for this purpose.

Step-by-Step Guide

  1. Import the necessary library:

    import matplotlib.pyplot as plt

  2. Create your plot:

    plt.plot([1, 2, 3, 4], [10, 20, 25, 30], label='Line 1')
plt.plot([1, 2, 3, 4], [15, 25, 30, 35], label='Line 2')

  3. Use the plt.legend() function with the bbox_to_anchor parameter:

    • To place the legend outside the plot:

      plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
      • bbox_to_anchor=(1.05, 1) places the legend slightly to the right (1.05) and at the top (1) of the plot.
      • loc='upper left' specifies the upper left corner of the legend box as the anchor point.

    • To adjust the legend's position further:

      • Increase the first value in bbox_to_anchor to move the legend further to the right.
      • Decrease the second value in bbox_to_anchor to move the legend below the plot.

    • To prevent the legend from overlapping with the plot:

      plt.tight_layout()

  4. Display the plot:

    plt.show()

Code Example

The Python code generates a line plot with two lines, 'Line 1' and 'Line 2', with specified x and y values. The legend is positioned outside the plot on the right side and the layout is adjusted to prevent overlapping of plot elements. Finally, the plot is displayed.

import matplotlib.pyplot as plt

# Create your plot
plt.plot([1, 2, 3, 4], [10, 20, 25, 30], label='Line 1')
plt.plot([1, 2, 3, 4], [15, 25, 30, 35], label='Line 2')

# Place the legend outside the plot
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')

# Prevent the legend from overlapping with the plot
plt.tight_layout()

# Display the plot
plt.show()

Explanation:

  1. Import matplotlib.pyplot: This line imports the necessary library for plotting.
  2. Create the plot:
    • plt.plot([1, 2, 3, 4], [10, 20, 25, 30], label='Line 1'): Plots the first line with x-values [1, 2, 3, 4] and corresponding y-values [10, 20, 25, 30]. The label argument sets the label for this line in the legend.
    • plt.plot([1, 2, 3, 4], [15, 25, 30, 35], label='Line 2'): Plots the second line similarly.
  3. Place the legend:
    • plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left'):
      • bbox_to_anchor=(1.05, 1): Specifies the coordinates (1.05, 1) relative to the plot's coordinate system (where (0, 0) is the bottom left and (1, 1) is the top right) for placing the legend box.
      • loc='upper left': Sets the upper left corner of the legend box as the anchor point for the specified bbox_to_anchor coordinates.
  4. Prevent overlapping:
    • plt.tight_layout(): Adjusts the plot's layout to prevent labels, titles, and the legend from overlapping with the plot area.
  5. Display the plot:
    • plt.show(): Shows the plot with the legend placed outside.

This code will create a plot with two lines and a legend positioned slightly to the right and at the top of the plot area, ensuring no overlapping occurs.

Additional Notes

  • Flexibility of bbox_to_anchor: The bbox_to_anchor parameter is very versatile. You can:
    • Use it with different loc values to control which corner of the legend box is anchored to the specified coordinates.
    • Provide relative coordinates (values between 0 and 1) or absolute coordinates.
  • Fine-tuning position: You might need to experiment with different values for bbox_to_anchor to achieve the desired legend placement, especially for complex plots.
  • Alternatives: While bbox_to_anchor is powerful, consider these alternatives for simpler cases:
    • Using predefined locations: plt.legend() accepts keywords like 'upper right', 'lower left', etc., for common legend placements.
    • Placing within the plot: You can often fit the legend within the plot by adjusting its position using these keywords and potentially shrinking the fontsize using plt.legend(fontsize='small').
  • plt.tight_layout() importance: Always use plt.tight_layout() after placing the legend outside to prevent overlapping and ensure all elements fit within the figure.
  • Saving the figure: After creating your plot, use plt.savefig('my_plot.png') to save it as an image file. Make sure to call plt.tight_layout() before saving to avoid cropping issues.
  • Other customizations: You can further customize the legend's appearance, such as:
    • Changing the font size, style, and color.
    • Adding a title to the legend.
    • Modifying the frame and background of the legend box.

Refer to the Matplotlib documentation for more details on these customizations and other legend options.

Summary

This guide explains how to move the legend outside of a Matplotlib plot in Python.

Key Steps:

  1. Import matplotlib.pyplot: import matplotlib.pyplot as plt
  2. Create your plot: Use plt.plot() to define your lines and labels.
  3. Place the legend outside:
    • Use plt.legend(bbox_to_anchor=(x, y), loc='position')
      • bbox_to_anchor: Controls legend position relative to the plot.
        • x > 1: Moves legend to the right.
        • y < 1: Moves legend below the plot.
      • loc: Specifies the anchor point within the legend box (e.g., 'upper left').
  4. Prevent overlapping: Use plt.tight_layout() to adjust plot elements and avoid overlap.
  5. Display the plot: plt.show()

Example:

import matplotlib.pyplot as plt

plt.plot([1, 2, 3, 4], [10, 20, 25, 30], label='Line 1')
plt.plot([1, 2, 3, 4], [15, 25, 30, 35], label='Line 2')

plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
plt.tight_layout()
plt.show()

This code creates a plot with two lines and places the legend slightly to the right and at the top, preventing any overlap with the plotted data.

Conclusion

This guide provided a comprehensive overview of positioning legends outside a Matplotlib plot. We covered the importance of using bbox_to_anchor and loc for precise placement, and how plt.tight_layout() ensures a polished look by preventing overlaps. Remember that Matplotlib offers extensive customization options, so explore its documentation to tailor your plots further. By mastering these techniques, you'll enhance the clarity and visual appeal of your data visualizations.

References

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