seaborn.
color_palette
(palette=None, n_colors=None, desat=None)¶Return a list of colors defining a color palette.
deep, muted, bright, pastel, dark, colorblind
name of matplotlib cmap, ‘ch:<cubehelix arguments>’, ‘hls’, ‘husl’, or a list of colors in any format matplotlib accepts
Calling this function with palette=None
will return the current
matplotlib color cycle.
Matplotlib palettes can be specified as reversed palettes by appending “_r” to the name or as “dark” palettes by appending “_d” to the name. (These options are mutually exclusive, but the resulting list of colors can also be reversed).
This function can also be used in a with
statement to temporarily
set the color cycle for a plot or set of plots.
See the tutorial for more information.
Name of palette or None to return current palette. If a sequence, input colors are used but possibly cycled and desaturated.
Number of colors in the palette. If None
, the default will depend
on how palette
is specified. Named palettes default to 6 colors,
but grabbing the current palette or passing in a list of colors will
not change the number of colors unless this is specified. Asking for
more colors than exist in the palette will cause it to cycle.
Proportion to desaturate each color by.
Color palette. Behaves like a list, but can be used as a context
manager and possesses an as_hex
method to convert to hex color
codes.
See also
set_palette
Set the default color cycle for all plots.
set_color_codes
Reassign color codes like "b"
, "g"
, etc. to colors from one of the seaborn palettes.
Examples
Calling with no arguments returns all colors from the current default color cycle:
>>> import seaborn as sns; sns.set()
>>> sns.palplot(sns.color_palette())
Show one of the other “seaborn palettes”, which have the same basic order of hues as the default matplotlib color cycle but more attractive colors. Calling with the name of a palette will return 6 colors by default:
>>> sns.palplot(sns.color_palette("muted"))
Use discrete values from one of the built-in matplotlib colormaps:
>>> sns.palplot(sns.color_palette("RdBu", n_colors=7))
Make a customized cubehelix color palette:
>>> sns.palplot(sns.color_palette("ch:2.5,-.2,dark=.3"))
Use a categorical matplotlib palette and add some desaturation:
>>> sns.palplot(sns.color_palette("Set1", n_colors=8, desat=.5))
Make a “dark” matplotlib sequential palette variant. (This can be good when coloring multiple lines or points that correspond to an ordered variable, where you don’t want the lightest lines to be invisible):
>>> sns.palplot(sns.color_palette("Blues_d"))
Use as a context manager:
>>> import numpy as np, matplotlib.pyplot as plt
>>> with sns.color_palette("husl", 8):
... _ = plt.plot(np.c_[np.zeros(8), np.arange(8)].T)