Annotations - ( Advanced Plotting Techniques )

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Syntax

axis.text(x, y, s, fontdict=None, **kwargs)

Example

import matplotlib.pyplot as plt

fig, ax = plt.subplots()

ax.plot([0, 1, 2, 3, 4], [0, 1, 4, 9, 16])

ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_title('Annotating Example')

ax.annotate('Important Point', xy=(2, 4), xytext=(3, 7),
            arrowprops=dict(facecolor='red', shrink=0.01))

plt.show()

Output

A plot is displayed with an annotation of the text 'Important Point' at the point (2, 4) and an arrow pointing towards the location (3, 7).

Explanation

Annotations are used in plots to highlight important points or add text descriptions to the plot. matplotlib provides the text() and annotate() methods to add annotations to a plot.

In the above example, we plot a graph and then use the annotate() method to add the annotation 'Important Point' at the point (2, 4). We also specify the location of the text using xytext=(3, 7) and add an arrow pointing towards the location using arrowprops=dict(facecolor='red', shrink=0.01).

Use

Annotations are a powerful tool for highlighting important features in a plot. They can be used to add textual descriptions or explanations to a plot, or to point out specific data points of interest.

Important Points

• Annotations can be used to highlight important features in a plot
• matplotlib provides the text() and annotate() methods to add annotations to a plot
• The annotate() method can be used to add a text annotation with an arrow pointing towards a specific location
• Annotations can be customized with various properties such as font size, font style, color, etc.

Summary

In conclusion, annotations are a great way to highlight important features in a plot. matplotlib provides several methods to add annotations to a plot, including the text() and annotate() methods. Annotations can be customized with various properties to suit the specific needs of the plot.