How to create advanced annotations in Matplotlib

With matplotlib, you can create annotations to highlight specific parts of a chart, but it's a limited tool. In a older post on how to custom titles, we have seen how to use the highlight_text package to create much better annotations with ease.

In this post, we will see how to use this package to create advanced annotations like customizing background color, creating path effects and adding title and subtitle in one annotation.

Annotations

In data visualization, annotations have a major role in available information to the reader.

They can be used to:

highlight specific points
provide additional information
simply explain the data in more depth

However, it can be quite technicaly challenging to customize annotations in matplotlib, especially if you want specific text highlighting such as word in bold, italic or colored differently.

Let's see how we can create nice annotations in a few examples.

Libraries

Default tools from matplotlib are unfortunately not enough to create nice annotations. We will use the highlight-text package that simplifies the process.

Keep in mind that it would have been possible to use the flexitext package that can do approximately the same thing.

And we will also need to load matplotlib and numpy libraries.

import numpy as np
import matplotlib.pyplot as plt
from highlight_text import fig_text, ax_text

Simple annotation

When creating a plot with annotation in matplotlib, we mainly use 2 functions:

annotate()
text()

Concretely, the annotate() function allows to add a text at a specific position, with an arrow pointing to a specific point, while the text() function allows to add a text at a specific position, without any arrow.

Let's see how they behave with a concrete example:

fig, ax = plt.subplots(ncols=2, figsize=(8, 5))
x = [1, 2, 3, 4]
y = [10, 11, 12, 13]

point_to_highlight = (2, 11)

# annotation with .text()
ax[0].plot(x, y)
ax[0].text(
    x=point_to_highlight[0],  # position on x-axis
    y=point_to_highlight[1],  # position on y-axis
    s='Text near the point',
    fontsize=12
)
ax[0].set_title('text()')

# annotation with .annotate()
ax[1].plot(x, y)
ax[1].annotate(
    text='Important Point',
    xy=point_to_highlight,  # position of the point
    xytext=(1, 14),  # position of the text
    arrowprops=dict(facecolor='black', shrink=0.05),
    fontsize=12
)
ax[1].set_title('        annotation()')

plt.show()

Boldness and Italics

Thanks to the highlight_text package, it is possible to bold and italic tp a specific part of the text. This is what will make the annotation stand out from the rest of the text.

The syntax is that we have to put the part of the text that we want to highlight between < and >. Then, we use the highlight_textprops argument to specify the style of the selected part.

fig, ax = plt.subplots(figsize=(8, 5))
x = [1, 2, 3, 4]
y = [10, 11, 12, 13]
point_to_highlight = (2, 11)

ax.plot(x, y)
text = '<Wow>, this annotation is <much better!>'
ax_text(
    x=point_to_highlight[0],  # position on x-axis
    y=point_to_highlight[1],  # position on y-axis
    s=text,
    fontsize=12,
    highlight_textprops=[
        {"fontstyle": 'italic'},
        {"fontweight": 'bold'}
    ],
    ax=ax
)

plt.show()