How to Add a Horizontal Line Across Subplots in Python

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What will you learn?

In this tutorial, you will master the art of incorporating horizontal lines across multiple subplots using Matplotlib in Python. This skill is crucial for improving the interpretability and analytical depth of your visualizations.

Introduction to the Problem and Solution

When working with data visualization, it’s common to highlight specific values or thresholds across plots for comparison or reference. If you are creating multiple subplots within a single figure using Matplotlib, you may want to emphasize a particular y-value consistently across all these subplots. Adding horizontal lines uniformly across different subplots might initially seem challenging.

However, fear not! We will address this challenge by leveraging Matplotlib’s axhline function. This function empowers us to draw horizontal lines precisely at specified positions on our charts. By iterating over each subplot (axes object) within our figure, we can seamlessly add these lines uniformly across all subplots. Let’s delve into practical examples to understand how this is achieved.

Code

import matplotlib.pyplot as plt

# Create a figure and 2x1 grid of subplots
fig, axs = plt.subplots(2)

# Sample data
x = range(10)
y1 = [2*i for i in x]
y2 = [i**0.5 for i in x]

# Plotting on each subplot
axs[0].plot(x, y1)
axs[1].plot(x, y2)

# Adding a horizontal line at y=5 on both subplots
for ax in axs:
    ax.axhline(y=5, color='r', linestyle='--')

plt.show()

# Copyright PHD

Explanation

In the provided solution:

  • We started by importing matplotlib.pyplot for plotting.
  • Created a figure with two vertical subplots (axs) using plt.subplots().
  • Plotted sample datasets (y1 and y2) against the same x-values on these separate axes.
  • Iterated over each subplot (each ax in axs) and utilized .axhline() method to draw a red dashed horizontal line at y=5. The parameters like color=’r’ and linestyle=’–‘ define the appearance of this line.

This approach ensures that regardless of the data represented by individual subplots, they all share a common reference point horizontally drawn across them.

  1. What does .subplot() do?

  2. The .subplot() function creates one or more sub-plots within a single window.

  3. Can I use .axhline() with vertical plots?

  4. Yes, but for vertical lines, use .axvline() instead.

  5. How do I change the color of my horizontal line?

  6. You can specify your desired color using the color= parameter inside .axhline() method.

  7. Is it possible to add multiple horizontal lines on one plot?

  8. Certainly! Call .axhline() multiple times with different ‘y’ values.

  9. Does .axhline() work with non-linear scales?

  10. Yes, it works with any scale set on your axes (linear, log, etc.).

  11. Can I change the thickness of my horizontal line?

  12. To change thickness, use the ‘linewidth=’ parameter inside .axhline().

  13. How do I customize my dashed-line pattern?

  14. You can set custom dash sequences using ‘linestyle=’ parameter; standard patterns include ‘–‘, ‘-.’, ‘:’, etc., but you can define custom patterns too!

  15. Can I label my horizontal line?

  16. Yes, use the ‘label =’ parameter and then invoke .legend() method to display it.

  17. Is there a way to add a horizontal line across all subfigures regardless of subplot arrangement?

  18. You need to iterate through each axis object (‘Ax’) irrespective of figures and layouts.

  19. What happens if my plot is updated after adding an axhline?

  20. The horizontal line remains at its specified position unless redrawn or new lines are added.

Conclusion

By now, you should have gained proficiency in effectively utilizing axhline() to incorporate horizontal lines across your subplots in Matplotlib. This technique not only enhances chart readability but also facilitates easy data comparison across various visualizations. Experiment with it in your next project for an additional layer of analysis!

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