Apply a style sheet to Matplotlib

logo of a chart:Density

Matplotlib comes with 26 pre-built style sheets. You can apply them to any kind of Matplotlib chart thanks to the use_style() function. It allows to create beautiful viz out of the box.

List of themes

The list of available matplotlib themes is stored in a list called There are 26 of them.

import matplotlib.pyplot as plt


The scatterplot section of the gallery explains in depth how to build a basic scatterplot with matplotlib. It is pretty straightforward thanks to the plot() function.

# Create a dataset:
import numpy as np
import pandas as pd
df=pd.DataFrame({'x': range(1,101), 'y': np.random.randn(100)*15+range(1,101) })
# plot
plt.plot( 'x', 'y', data=df, linestyle='none', marker='o')

Apply a theme

Now, let's make this chart a bit prettier thanks to the style called fivethirtyeight. In case you don't know it already, FiveThirtyeight is an online newspaper that often displays some very nice dataviz articles.'fivethirtyeight')
plt.plot( 'x', 'y', data=df, linestyle='none', marker='o')
plt.title('Scatterplot with the five38 theme', fontsize=12)

Apply the style on a barchart

You can apply the same exact tip for any kind of chart to make it look better. Here is a barchart example coming from the barchart section of the gallery. It uses the dark_background theme to demo another type of customization.

# create dataset
height = [3, 12, 5, 18, 45]
bars = ('A', 'B', 'C', 'D', 'E')
y_pos = np.arange(len(bars))
# Create horizontal bars
plt.barh(y_pos, height)
# Create names on the x-axis
plt.yticks(y_pos, bars)
# Show graphic'dark_background')
Animation with python


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