Density plot of several variables


It is sometimes particularly useful to plot the distribution of several variables on the same plot in order to compare them more easily. This can be performed by using the kdeplot function of seaborn several times as presented below.

As stated before, seaborn being built on top of matplotlib enables you to use matplotlib.fig and matplotlib.axes objects to add graphs to your figures.
In the following example, we successively add kdeplots to a matplotlib figure and plot it. From this example, you can play with colors, or any other kdeplot argument to better distinguish the two distributions.

# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background (use sns.set_theme() if seaborn version 0.11.0 or above) 
sns.set(style="darkgrid")
df = sns.load_dataset('iris')
 
# plotting both distibutions on the same figure
fig = sns.kdeplot(df['sepal_width'], shade=True, color="r")
fig = sns.kdeplot(df['sepal_length'], shade=True, color="b")
plt.show()

Violin

Density

Histogram

Boxplot

Ridgeline

Contact & Edit

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Violin

Density

Histogram

Boxplot

Ridgeline

Scatterplot

Heatmap

Correlogram

Bubble

Connected Scatter

2D Density

Barplot

Spider / Radar

Wordcloud

Parallel

Lollipop

Circular Barplot

Treemap

Venn Diagram

Donut

Pie Chart

Dendrogram

Circular Packing

Line chart

Area chart

Stacked Area

Streamgraph

Map

Choropleth

Hexbin

Cartogram

Connection

Bubble

Chord Diagram

Network

Sankey

Arc Diagram

Edge Bundling

Colors

Interactivity

Animation with python

Animation

Cheat sheets

Caveats

3D