pypalettes 0.1.2

A large collection of color maps for Python

PyPalettes

A large (+2500) collection of color maps for Python.

All available palettes can be found on the dedicated website

You can find an introduction to PyPalettes in the Python Graph Gallery, with code samples and explanations about how to use this library in many different cases.

Installation

You can install pypalettes directly from PyPI with:

pip install --upgrade pypalettes

Alternatively you can install the development version with:

pip install git+https://github.com/JosephBARBIERDARNAL/pypalettes.git

Quick start

Once the cmap is loaded, you can use it as any other color map in matplotlib or seaborn.

import matplotlib.pyplot as plt
from pypalettes import load_cmap
import seaborn as sns
import numpy as np

data = np.random.rand(10, 12)

cmap = load_cmap('Anemone', cmap_type='continuous')

sns.heatmap(data, cmap=cmap)
plt.show()

Getting started

• Load a color map:

from pypalettes import load_cmap
cmap = load_cmap('Chaetodon_sedentarius')
cmap

• Transform a qualitative color map into a continuous one:

from pypalettes import load_cmap
cmap = load_cmap('Chaetodon_sedentarius', cmap_type='continuous')
cmap

• Invert a color map:

from pypalettes import load_cmap
cmap = load_cmap('Chaetodon_sedentarius', reverse=True)
cmap

• Get hex values of a color map:

from pypalettes import get_hex
get_hex('pupitar')

['#7098C0FF', '#88C0E8FF', '#285880FF', '#B8E0F8FF', '#F8F8F8FF', '#404060FF', '#A8A8A8FF', '#C8C8D0FF', '#B04000FF']

• Get rgb values of a color map:

from pypalettes import get_rgb
get_rgb('AirNomads')

[(255, 153, 51), (194, 72, 65), (255, 255, 51), (139, 91, 69), (135, 175, 209), (238, 176, 90), (219, 197, 160)]

More examples can be found in this introduction to PyPalettes.

Chart made with pypalettes

Click on the image to get the associated code!

Acknowledgements

PyPalettes is highly inspired (and relies on for the first one) from

• the R package paletteer
• the python package palettable.

A big thanks to Yan Holtz for:

• Creating the web app for browsing palettes
• Hosting the documentation and examples on the Python Graph Gallery
• Providing valuable feedback on the code and design of the API

How data has been collected

99% of the palettes come from the Paletteer R package.

Learn more in the dedicated directory.