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A large collection of color maps for Python

Project description

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 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
import seaborn as sns
from pypalettes import load_cmap
import numpy as np

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

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

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

heatmap example



Getting started


  • Load a color map:
from pypalettes import load_cmap
cmap = load_cmap('Chaetodon_sedentarius')
cmap

Darjeeling2


  • Transform a qualitative color map into a continuous one:
from pypalettes import load_cmap
cmap = load_cmap('Chaetodon_sedentarius', type='continuous')
cmap

Darjeeling2


  • Invert a color map:
from pypalettes import load_cmap
cmap = load_cmap('Chaetodon_sedentarius', reverse=True)
cmap

Darjeeling2


  • 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!

choropleth map of europe stacked area chart of natural disasters
gapminder bubble chart



Acknowledgements

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

A big thanks to Yan Holtz for:



How data has been collected

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

Learn more in the dedicated directory.



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