Matplotlib Text Object Concatenation

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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.

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Skills Graph

%%%%{init: {'theme':'neutral'}}%%%% flowchart RL python(("`Python`")) -.-> python/BasicConceptsGroup(["`Basic Concepts`"]) python(("`Python`")) -.-> python/FileHandlingGroup(["`File Handling`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/BasicConceptsGroup(["`Basic Concepts`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/PlotCustomizationGroup(["`Plot Customization`"]) matplotlib(("`Matplotlib`")) -.-> matplotlib/AdvancedTopicsGroup(["`Advanced Topics`"]) python(("`Python`")) -.-> python/DataStructuresGroup(["`Data Structures`"]) python(("`Python`")) -.-> python/ModulesandPackagesGroup(["`Modules and Packages`"]) python(("`Python`")) -.-> python/DataScienceandMachineLearningGroup(["`Data Science and Machine Learning`"]) python/BasicConceptsGroup -.-> python/comments("`Comments`") python/FileHandlingGroup -.-> python/with_statement("`Using with Statement`") matplotlib/BasicConceptsGroup -.-> matplotlib/importing_matplotlib("`Importing Matplotlib`") matplotlib/BasicConceptsGroup -.-> matplotlib/figures_axes("`Understanding Figures and Axes`") matplotlib/PlotCustomizationGroup -.-> matplotlib/text_annotations("`Text Annotations`") matplotlib/AdvancedTopicsGroup -.-> matplotlib/matplotlib_config("`Customizing Matplotlib Configurations`") python/DataStructuresGroup -.-> python/lists("`Lists`") python/DataStructuresGroup -.-> python/tuples("`Tuples`") python/ModulesandPackagesGroup -.-> python/importing_modules("`Importing Modules`") python/DataScienceandMachineLearningGroup -.-> python/data_visualization("`Data Visualization`") subgraph Lab Skills python/comments -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} python/with_statement -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} matplotlib/importing_matplotlib -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} matplotlib/figures_axes -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} matplotlib/text_annotations -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} matplotlib/matplotlib_config -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} python/lists -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} python/tuples -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} python/importing_modules -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} python/data_visualization -.-> lab-48900{{"`Matplotlib Text Object Concatenation`"}} end

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.

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