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Annotating data points in Matplotlib

schedule Aug 12, 2023
Last updated
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PythonMatplotlib
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To annotate data points in Matplotlib, use the annotate(~) method:

import matplotlib.pyplot as plt

x = [1,2,3]
y = [4,5,6]
plt.scatter([1,2,3], [4,5,6])
for i in range(len(x)):
# The 1st argument is the annotation label, 2nd is the coordinate of the annotation
plt.annotate(i, (x[i], y[i]))

This produces the following:

Applying an offset

With the default settings, the annotations do not look great; the annotations overlap with our data points. To fix this, we can apply an offset like so:

x = [1,2,3]
y = [4,5,6]
plt.scatter([1,2,3], [4,5,6])
for i in range(len(x)):
plt.annotate(i, (x[i], y[i]), xytext=(5, 5), textcoords="offset pixels")

Here, we are setting two additional parameters xytext and textcoords. The textcoords indicates that we want to apply the offset in units of pixels, and the xytext indicates how much we want to offset the annotations by. The xytext takes in a tuple, with the first item being the horizontal offset, and second being the vertical offset.

The output is as follows:

Changing the font-size

To change the font-size of the annotation, specify the fontsize argument:

import matplotlib.pyplot as plt
x = [1,2,3]
y = [4,5,6]
plt.scatter([1,2,3], [4,5,6])
for i in range(len(x)):
plt.annotate(i, (x[i], y[i]), fontsize=20)

This produces the following plot:

robocat
Published by Isshin Inada
Edited by 0 others
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