Distribution plot
Seaborn basics
1 min read
This section is 1 min read, full guide is 42 min read
Published Oct 7 2025
24
Show sections list
0
Log in to enable the "Like" button
0
Guide comments
0
Log in to enable the "Save" button
Respond to this guide
Guide Sections
Guide Comments
ChartsGraphsMatplotlibNumPyPandasPythonSeabornVisualisation
seaborn.displot() is a figure-level function for visualising distributions of one or two numeric variables.
It can create:
- Histograms
- Kernel Density Estimates (KDE)
- ECDF plots
- Faceted grids (multiple subplots by category)
It acts as a wrapper around:
sns.histplot()sns.kdeplot()sns.ecdfplot()
and provides additional faceting (subplot) capabilities.
Syntax:
sns.displot(
data=None,
*,
x=None,
y=None,
hue=None,
row=None,
col=None,
kind="hist",
stat="count",
bins="auto",
binwidth=None,
discrete=False,
kde=False,
fill=True,
palette=None,
multiple="layer",
common_norm=True,
common_bins=True,
aspect=None,
height=5,
facet_kws=None,
**kwargs
)
Copy to Clipboard
Parameters:
data= DataFrame containing the datax,y= Variables to plothue= Adds colour-coded subgroupsrow,col= Create multiple subplots (facets)kind= "hist", "kde", or "ecdf"stat= What the bar/curve height represents: "count", "probability", "percent", "density"bins,binwidth= Control histogram binningmultiple= How hue groups are displayed ("layer", "stack", "dodge", "fill")common_norm= Normalise groups together or separatelypalette= Colour schemeaspect= Width-to-height ratio of each facetheight= Height of each facet (in inches)
Basic example
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
sns.displot(data=tips, x="total_bill")
plt.show()
Copy to Clipboard
Creates a histogram of total_bill. Equivalent to sns.histplot(x="total_bill"), but as a figure-level plot.
Facet by column
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
sns.displot(data=tips, x="total_bill", col="day")
plt.show()
Copy to Clipboard
One subplot for each day.
Facet by row and column
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
sns.displot(data=tips, x="total_bill", col="day", row="sex")
plt.show()
Copy to Clipboard
Creates a grid of subplots by both day (columns) and sex (rows).
Customise facet appearance
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
sns.displot(
data=tips,
x="total_bill",
col="day",
hue="sex",
kind="kde",
fill=True,
height=4,
aspect=1.2,
palette="coolwarm"
)
plt.show()
Copy to Clipboard
Adjusts subplot size (height) and shape (aspect) Adds colour-coded KDEs within each facet
