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

Most seaborn methods to generate color palettes have an optional argument as_cmap which by default is False. You can use to directly get a Matplotlib colormap:

import seaborn as sns import matplotlib.pylab as plt import numpy as np  # construct cmap my_cmap = sns.light_palette("Navy", as_cmap=True)  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() 

Answer 2

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()