seaborn color_palette as matplotlib colormap

Question

Seaborn offers a function called color_palette, which allows you to easily create new color_palettes for plots.

colors = ["#67E568","#257F27","#08420D","#FFF000","#FFB62B","#E56124","#E53E30","#7F2353","#F911FF","#9F8CA6"]

color_palette = sns.color_palette(colors)

I want to transform color_palette to a cmap, which I can use in matplotlib, but I don't see how I can do this.

Sadly just functions like "cubehelix_palette","light_palette",… have an "as_cmap" paramater. "color_palette" doesn't, unfortunately.

Answer 1

You have to convert a list of colors from seaborn palette to color map of matplolib (thx to @RafaelLopes for proposed changes):

import seaborn as sns
import matplotlib.pylab as plt
import numpy as np
from matplotlib.colors import ListedColormap

# construct cmap
flatui = ["#9b59b6", "#3498db", "#95a5a6", "#e74c3c", "#34495e", "#2ecc71"]
my_cmap = ListedColormap(sns.color_palette(flatui).as_hex())

N = 500
data1 = np.random.randn(N)
data2 = np.random.randn(N)
colors = np.linspace(0,1,N)
plt.scatter(data1, data2, c=colors, cmap=my_cmap)
plt.colorbar()
plt.show()