Concatenating Matplotlib Text Objects

Introduction

In this lab, you will learn how to concatenate text objects with different properties using Matplotlib. Concatenation is the process of combining multiple text objects into a single string. This can be useful when creating annotations or labels for visualizations.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Create the First Text Object

The first step is to create the first text object using ~.Axes.text. This text object will be the starting point for the concatenation process. The following code creates a red text object with the word "Matplotlib" at position (0.1, 0.5) on the plot.

text = ax.text(.1, .5, "Matplotlib", color="red")

Create the Subsequent Text Objects

The next step is to create the subsequent text objects using ~.Axes.annotate. This function allows you to position the text object relative to the previous text object. The following code creates three text objects that are positioned to the right of the previous text object.

text = ax.annotate(
    " says,", xycoords=text, xy=(1, 0), verticalalignment="bottom",
    color="gold", weight="bold")  ## custom properties
text = ax.annotate(
    " hello", xycoords=text, xy=(1, 0), verticalalignment="bottom",
    color="green", style="italic")  ## custom properties
text = ax.annotate(
    " world!", xycoords=text, xy=(1, 0), verticalalignment="bottom",
    color="blue", family="serif")  ## custom properties

Customize the Text Objects

You can customize the appearance of the text objects using various properties. In the previous code block, we set the color, weight, style, and family properties for each text object. You can experiment with different properties to achieve the desired appearance.

Display the Plot

Once you have created and customized all the text objects, you can display the plot using plt.show(). The following code block shows the complete code for the plot.

import matplotlib.pyplot as plt

plt.rcParams["font.size"] = 20
ax = plt.figure().add_subplot(xticks=[], yticks=[])

## The first word, created with text().
text = ax.text(.1, .5, "Matplotlib", color="red")
## Subsequent words, positioned with annotate(), relative to the preceding one.
text = ax.annotate(
    " says,", xycoords=text, xy=(1, 0), verticalalignment="bottom",
    color="gold", weight="bold")  ## custom properties
text = ax.annotate(
    " hello", xycoords=text, xy=(1, 0), verticalalignment="bottom",
    color="green", style="italic")  ## custom properties
text = ax.annotate(
    " world!", xycoords=text, xy=(1, 0), verticalalignment="bottom",
    color="blue", family="serif")  ## custom properties

plt.show()

Summary

In this lab, you learned how to concatenate text objects with different properties using Matplotlib. You can use this technique to create custom annotations or labels for your visualizations. By customizing the appearance of each text object, you can create visually appealing and informative plots.

Matplotlib Text Object Concatenation