Pandas: Annotate data points while plotting from DataFrame

# Table of Contents

# Pandas: Annotate data points while plotting from DataFrame

To annotate data points while plotting from a Pandas DataFrame:

Use a for loop to iterate over the DataFrame's rows.
On each iteration, call the axes.annotate() method.
The method annotates the point with the specified text.

main.py

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import pandas as pd
import matplotlib.pyplot as plt


df = pd.DataFrame({
    'x': [0.79974873, 0.62466539, 0.65046638, 0.22819233, 0.47786481],
    'y': [0.97827185, 0.26413242, 0.88445034, 0.6379751,  0.63235667],
    'name': ['Alice', 'Bobby', 'Carl', 'Dan', 'Ethan']
})

fig, ax = plt.subplots()

df.plot('x', 'y', kind='scatter', ax=ax)

for index, row in df.iterrows():
    ax.annotate(row['name'], (row['x'], row['y']))

ax.set_xlabel('horizontal label')
ax.set_ylabel('vertial label')

plt.show()

annotate data points while plotting from dataframe

The code for this article is available on GitHub

We used the matplotlib.pyplot.subplots() method to create a figure and a set of subplots.

main.py

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fig, ax = plt.subplots()

The next step is to use the DataFrame.plot() method to plot a scatter plot.

main.py

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df.plot('x', 'y', kind='scatter', ax=ax)

The DataFrame.iterrows() method enables us to iterate over the DataFrame's rows as (index, Series) pairs.

main.py

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for index, row in df.iterrows():
    ax.annotate(row['name'], (row['x'], row['y']))

On each iteration, we pass 2 arguments to the Axes.annotate() method:

The text of the annotation.
A tuple containing the x and y values (point) to annotate.

However, by default, the annotated data points don't look very good.

annotate data points while plotting from dataframe

# Prettifying the annotations by passing more arguments to `Axes.annotate()`

You can prettify the way annotations are displayed by passing additional arguments to the Axes.annotate() method.

Here is an example.

main.py

Copied!
import pandas as pd
import matplotlib.pyplot as plt


df = pd.DataFrame({
    'x': [0.79974873, 0.62466539, 0.65046638, 0.22819233, 0.47786481],
    'y': [0.97827185, 0.26413242, 0.88445034, 0.6379751,  0.63235667],
    'name': ['Alice', 'Bobby', 'Carl', 'Dan', 'Ethan']
})

fig, ax = plt.subplots()

df.plot('x', 'y', kind='scatter', ax=ax, s=120)

print(df.iterrows())

for index, row in df.iterrows():
    ax.annotate(
        row['name'],
        (row['x'], row['y']),
        xytext=(10, -5),
        textcoords='offset points',
        fontsize=14,
        color='darkslategrey',
        family='sans-serif'
    )

ax.set_xlabel('horizontal label')
ax.set_ylabel('vertial label')

plt.show()

prettifying the annotations in the call to axes annotate

The code for this article is available on GitHub

The additional arguments we passed to Axes.annotate() are:

xytext - the position (x, y) to place the text at. The coordinate system is determined by the textcoords argument.
textcoords - the coordinate system that xytext is given in. Can be 1 of 2 values:
- "offset points" - offset (in points) from the xy value.
- "offset pixels" - offset (in pixels) from the xy value.
fontsize - the font size of the annotated text.
color - the color of the annotated text.
family - the font family of the annotated text.

You can read more about the arguments the Axes.annotate() method takes in this section of the docs.