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# Annotating data points in Matplotlib

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

``` 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)): # 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:

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