How to remove the white shade/color from the heatmap using sns.kdeplot()? I just want the red color

Question

from mplsoccer.pitch import Pitch
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import kde
from scipy.ndimage import gaussian_filter
from copy import copy
np.random.seed(19680801)

plt.style.use('dark_background')

fields = ['id', 'minute', 'result', 'X1', 'Y','xG','h_a','situation','season',
          'shotType','X']
df=pd.read_csv('shots.csv', skipinitialspace=True, usecols=fields)
fig, ax = pitch.draw()
sns.kdeplot(df.Y, df.X,shade=True, ax=ax, cmap='Reds',
              shade_lowest=False,levels=20,kernel='gau',gridsize=50,
              bw='scott',cut=0,cbar=True,)
ax.set_xlim(ax.get_xlim()[::-1])        # invert the axis
ax.yaxis.tick_right()  
plt.axis('off')
plt.show()

The values df.X & df.Y lie between (0,1). I want the red part only. In matplotlib I used vmin argument eliminate the white part. What can be done here?

Edit: On second thoughts, the White region would be eliminated if the colormap starts from 12 in the fig attached. So the colormap starts from red and ends on dark red. That's what I would like.

Answer 1

I would use this approach to pick colours out of your colormap:

from matplotlib import cm
from matplotlib.colors import ListedColormap

# select 42 colours from the "Reds" cmap
red_selection = cm.get_cmap("Reds", 42)

# select half of the colours, closest to Red and assign to a new colormap
red_cmap = ListedColormap(red_selection(range(42))[21:, :])

from mplsoccer.pitch import Pitch
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import kde
from scipy.ndimage import gaussian_filter
from copy import copy
np.random.seed(19680801)

plt.style.use('dark_background')

fields = ['id', 'minute', 'result', 'X1', 'Y','xG','h_a','situation','season',
          'shotType','X']
df=pd.read_csv('shots.csv', skipinitialspace=True, usecols=fields)
fig, ax = pitch.draw()
sns.kdeplot(df.Y, df.X,shade=True, ax=ax, cmap=red_cmap,
              shade_lowest=False,levels=20,kernel='gau',gridsize=50,
              bw='scott',cut=0,cbar=True,)
ax.set_xlim(ax.get_xlim()[::-1])        # invert the axis
ax.yaxis.tick_right()  
plt.axis('off')
plt.show()