KDE_RidgePlot.py
c6b661d2d480Development-of-Analysis…

KDE_RidgePlot.py
View Options

			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)

			g.fig.savefig()
			plt.show()