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pythonplotseaborngradientkernel-density

Distribution Plot with Gradient Fill in Python

I'm trying to create a density plot with a gradient fill in python like this:

enter image description here

I've attempted to do so using this code:

plt.figure(figsize=(6, 1))
sns.kdeplot(data=df, x='Overall Rating', fill=True, palette='viridis')
...and
sns.kdeplot(data=df, x='Overall Rating', fill=True, cmap='viridis')

Neither work, both outputting this plot:

enter image description here

I've searched all over for a method to do this in python, but no luck. I've tried implementing the methods from this answer by @Diziet Asahi but can't wrap my head around it. Any help would really be appreciated!

Solution

  • You just need to grab the ax: ax = sns.kdeplot(...) and then execute the inner part of the for loop in @Diziet Asahi's solution with that ax.

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

sns.set_theme(style='white')
iris = sns.load_dataset('iris')
ax = sns.kdeplot(data=iris, x='petal_length', fill=True)

sns.despine()
cmap = 'turbo'
im = ax.imshow(np.linspace(0, 1, 256).reshape(1, -1), cmap=cmap, aspect='auto',
               extent=[*ax.get_xlim(), *ax.get_ylim()], zorder=10)
path = ax.collections[0].get_paths()[0]
patch = matplotlib.patches.PathPatch(path, transform=ax.transData)
im.set_clip_path(patch)

plt.show()

    kdeplot with gradient fill