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- import numpy as np
- import pandas as pd
- import seaborn as sns
- import matplotlib.pyplot as plt
- sns.set(style="white", rc={"axes.facecolor": (0, 0, 0, 0)})
- # Create the data
- 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
- # Initialize the FacetGrid object
- pal = sns.cubehelix_palette(10, rot=-.25, light=.7)
- g = sns.FacetGrid(df, row="g", hue="g", aspect=15, height=.5, palette=pal)
- # Draw the densities in a few steps
- g.map(sns.kdeplot, "x", clip_on=False, shade=True, alpha=1, lw=1.5, bw=.2)
- g.map(sns.kdeplot, "x", clip_on=False, color="w", lw=2, bw=.2)
- g.map(plt.axhline, y=0, lw=2, clip_on=False)
- # Define and use a simple function to label the plot in axes coordinates
- def label(x, color, label):
- ax = plt.gca()
- ax.text(0, .2, label, fontweight="bold", color=color,
- ha="left", va="center", transform=ax.transAxes)
- g.map(label, "x")
- # Set the subplots to overlap
- g.fig.subplots_adjust(hspace=-.25)
- # Remove axes details that don't play well with overlap
- g.set_titles("")
- g.set(yticks=[])
- g.despine(bottom=True, left=True)
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