How to set center color in heatmap

Question

I want to plot a heatmap in seaborn. My code is following:

plt.rcParams['font.size'] = 13
plt.rcParams['font.weight'] = 'bold'
my_dpi=96
fig, ax = plt.subplots(figsize=(800/my_dpi, 600/my_dpi), dpi=my_dpi, facecolor='black')
rdgn = sns.diverging_palette(h_neg=130, h_pos=10, s=99, l=55, sep=3)
sns.heatmap(df, cmap=rdgn, center=0.00, annot=True, fmt ='.2%', linewidths=1.3, linecolor='black', cbar=False, ax=ax)
plt.savefig('./image/image.png', dpi=96, facecolor='black')

And the result is following: enter image description here

I want the set 0 to be white, and the value >0 to be red, the values which <0 to be green. But the center in heatmap is invalid.

By the way, how to set the color unsymmetrical. Because the min value in my data is -0.34 and the maxima is 1.31. I want to set 0 to be white, -0.34 to be greenest and 1.31 to be reddest.

Answer 1

center would require something that can be centered. So instead of a palette, which is a list of colors, you will need a colormap. Seaborn provides the as_cmap parameter for this case,

sns.diverging_palette(..., as_cmap=True)

Alternatively, you can of course use any other matplotlib colormap, or specify your custom colormap.

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

data = np.linspace(-0.34, 1.31, 100).reshape(10,10)

fig, ax = plt.subplots()
rdgn = sns.diverging_palette(h_neg=130, h_pos=10, s=99, l=55, sep=3, as_cmap=True)
sns.heatmap(data, cmap=rdgn, center=0.00, annot=True, fmt ='.0%', 
            linewidths=1.3, linecolor='black', cbar=True, ax=ax)

plt.show()

If instead of centering the colormap you want to shift its middle point you cannot use center. But instead a matplotlib.colors.DivergingNorm.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import DivergingNorm
import seaborn as sns

data = np.linspace(-0.34, 1.31, 100).reshape(10,10)

fig, ax = plt.subplots()
rdgn = sns.diverging_palette(h_neg=130, h_pos=10, s=99, l=55, sep=3, as_cmap=True)
divnorm = DivergingNorm(vmin=data.min(), vcenter=0, vmax=data.max())
sns.heatmap(data, cmap=rdgn, norm=divnorm, annot=True, fmt ='.0%', 
            linewidths=1.3, linecolor='black', cbar=True, ax=ax)

plt.show()

Here, the full colormap will be squeezed in the green part and stretched in the red part.