Matplotlib
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Adding a title to a plotAdding arrows to an annotationAdding axis labels to a plotAdding markers to a plotAnnotating data pointsApplying an offset to annotationsChanging the default font sizeChanging the marker size in scatterplotsChanging the number of ticksChanging the tick sizeRemoving certain ticksRemoving column name label from pie chartsRemoving default axis labelsRotating axis labelsRotating custom tick labelsSpecifying custom tick labelsWriting mathematical expressions
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Annotating data points in Matplotlib
schedule Aug 12, 2023
Last updated local_offer
Tags Python●Matplotlib
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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 pltx = [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:
Published by Isshin Inada
Edited by 0 others
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