Adjusting Matplotlib Tick Label Alignment

Introduction

In data visualization, tick labels play an important role in conveying information to viewers. Sometimes, we may need to adjust the alignment of tick labels to make them more readable or to avoid overlapping. In this lab, we will learn how to use Matplotlib to adjust the alignment of tick labels.

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Skills Graph

Import Matplotlib and AxisArtist

First, we need to import Matplotlib and AxisArtist, which provides additional tools for creating custom axes.

import matplotlib.pyplot as plt
import mpl_toolkits.axisartist as axisartist

Define a Function for Setting Up Axes

To simplify the code, we can define a function that takes a figure object and a position as input, and returns an axis object with custom tick labels.

def setup_axes(fig, pos):
    ax = fig.add_subplot(pos, axes_class=axisartist.Axes)
    ax.set_yticks([0.2, 0.8], labels=["short", "loooong"])
    ax.set_xticks([0.2, 0.8], labels=[r"$\frac{1}{2}\pi$", r"$\pi$"])
    return ax

Create a Figure and Add Subplots

Next, we can create a figure object and add three subplots using the setup_axes function.

fig = plt.figure(figsize=(3, 5))
fig.subplots_adjust(left=0.5, hspace=0.7)

ax = setup_axes(fig, 311)
ax.set_ylabel("ha=right")
ax.set_xlabel("va=baseline")

ax = setup_axes(fig, 312)
ax.axis["left"].major_ticklabels.set_ha("center")
ax.axis["bottom"].major_ticklabels.set_va("top")
ax.set_ylabel("ha=center")
ax.set_xlabel("va=top")

ax = setup_axes(fig, 313)
ax.axis["left"].major_ticklabels.set_ha("left")
ax.axis["bottom"].major_ticklabels.set_va("bottom")
ax.set_ylabel("ha=left")
ax.set_xlabel("va=bottom")

Adjust Tick Label Alignment

Finally, we can use the set_ha and set_va methods to adjust the horizontal and vertical alignment of tick labels.

ax.axis["left"].major_ticklabels.set_ha("center")
ax.axis["bottom"].major_ticklabels.set_va("top")

Display the Plot

To display the plot, we can use the show method.

plt.show()

Summary

In this lab, we learned how to use Matplotlib and AxisArtist to adjust the alignment of tick labels. By customizing the horizontal and vertical alignment of tick labels, we can improve the readability and clarity of our data visualizations.