import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns
# Create the data : copied from examples/kde_ridgeplot.py
rs = np.random.RandomState(1979)
x = rs.randn(500)
g = np.tile(list("ABCDEFGHIJ"), 50)
df = pd.DataFrame(dict(x=x, g=g))
m = df.g.map(ord)
df["x"] += m
fig, ax = plt.subplots(1, 1, num=1, clear=True)
sns.kdeplot(
df,
x="x",
hue="g",
ax=ax,
fill=True,
linewidth=2,
clip_on=False,
ec="w",
alpha=1,
)
from mpl_visual_context.spreader import spready
polys = ax.collections
dy = 0.5 * max([p.get_datalim(p.axes.transData).height for p in polys])
yindices = np.arange(len(polys))
gg = df["g"].unique()
yoffsets = spready(polys, yindices, dy=dy)
ax.set_ylim(min(yoffsets), max(yoffsets) + dy)
ax.set_yticks(yoffsets, labels=gg[::-1])
ax.legend_.remove()
plt.show()
Total running time of the script: (0 minutes 0.076 seconds)
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