Multiple relational plots

Seaborn basics

1 min read

Published Oct 7 2025

ChartsGraphsMatplotlibNumPyPandasPythonSeabornVisualisation

seaborn.relplot() is a figure-level function for creating relational plots — it’s basically a wrapper around sns.scatterplot() and sns.lineplot() that allows faceting (i.e., multiple subplots for different subsets of data).

It helps you visualise relationships between variables and how they change across categories.

Syntax:

sns.relplot(

data=None,

x=None,

y=None,

hue=None,

style=None,

size=None,

col=None,

row=None,

kind='scatter',

palette=None,

markers=True,

sizes=None,

col_wrap=None,

height=5,

aspect=1,

facet_kws=None,

**kwargs

)

Parameters:

data = DataFrame with your data
x, y = Variables to plot on axes
hue = Colour by variable
style = Marker or line style by variable
size = Marker/line size by variable
col, row = Create subplots (facets) across columns or rows
kind = "scatter" (default) or "line"
palette = Colour palette
col_wrap = Wrap facet columns onto multiple rows
height = Height (in inches) of each facet
aspect = Aspect ratio (width/height) of each facet

Basic example (scatter)

import seaborn as sns

import matplotlib.pyplot as plt

data = sns.load_dataset("penguins")

sns.relplot(

data=data,

x="bill_length_mm",

y="bill_depth_mm",

kind="scatter"

)

plt.show()

Creates a simple scatter plot of bill length vs bill depth.

Faceting with `col` and `row`

import seaborn as sns

import matplotlib.pyplot as plt

data = sns.load_dataset("penguins")

sns.relplot(

data=data,

x="bill_length_mm",

y="bill_depth_mm",

hue="species",

col="island",

kind="scatter"

)

plt.show()

Creates a separate plot for each island.

seaborn relational plot faceting col row example

Faceting in grid (row + col)

import seaborn as sns

import matplotlib.pyplot as plt

data = sns.load_dataset("penguins")

sns.relplot(

data=data,

x="bill_length_mm",

y="bill_depth_mm",

hue="species",

col="island",

row="sex",

kind="scatter"

)

plt.show()

Subplots arranged by island (columns) and sex (rows).

seaborn relational plot faceting grid example

Faceting line chart

import seaborn as sns

import matplotlib.pyplot as plt

fmri = sns.load_dataset("fmri")

sns.relplot(

data=fmri,

x="timepoint",

y="signal",

hue="event",

col="region",

kind="line",

height=4,

aspect=1.2

)

plt.show()

Makes a grid of line plots, one for each brain region.

seaborn relational plot faceting line example

Multiple relational plots

Seaborn basics

1 min read