seaborn.dark_palette¶

seaborn.dark_palette(color, n_colors=6, reverse=False, as_cmap=False, input='rgb')¶

Make a sequential palette that blends from dark to color.

This kind of palette is good for data that range between relatively uninteresting low values and interesting high values.

The color parameter can be specified in a number of ways, including all options for defining a color in matplotlib and several additional color spaces that are handled by seaborn. You can also use the database of named colors from the XKCD color survey.

If you are using the IPython notebook, you can also choose this palette interactively with the choose_dark_palette() function.

Parameters

colorbase color for high values: hex, rgb-tuple, or html color name
n_colorsint, optional: number of colors in the palette
reversebool, optional: if True, reverse the direction of the blend
as_cmapbool, optional: If True, return a matplotlib.colors.Colormap.
input{‘rgb’, ‘hls’, ‘husl’, xkcd’}: Color space to interpret the input color. The first three options apply to tuple inputs and the latter applies to string inputs.

Returns

list of RGB tuples or matplotlib.colors.Colormap

See also

light_palette: Create a sequential palette with bright low values.
diverging_palette: Create a diverging palette with two colors.

Examples

Generate a palette from an HTML color:

>>> import seaborn as sns; sns.set_theme()
>>> sns.palplot(sns.dark_palette("purple"))

Generate a palette that decreases in lightness:

>>> sns.palplot(sns.dark_palette("seagreen", reverse=True))

Generate a palette from an HUSL-space seed:

>>> sns.palplot(sns.dark_palette((260, 75, 60), input="husl"))

Generate a colormap object:

>>> from numpy import arange
>>> x = arange(25).reshape(5, 5)
>>> cmap = sns.dark_palette("#2ecc71", as_cmap=True)
>>> ax = sns.heatmap(x, cmap=cmap)