Distribution plot

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:

Parameters:

• data = DataFrame containing the data
• x, y = Variables to plot
• hue = Adds colour-coded subgroups
• row, 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 binning
• multiple = How hue groups are displayed ("layer", "stack", "dodge", "fill")
• common_norm = Normalise groups together or separately
• palette = Colour scheme
• aspect = Width-to-height ratio of each facet
• height = Height of each facet (in inches)

Basic example

Creates a histogram of total_bill. Equivalent to sns.histplot(x="total_bill"), but as a figure-level plot.

Facet by column

One subplot for each day.

Facet by row and column

Creates a grid of subplots by both day (columns) and sex (rows).

Customise facet appearance

Adjusts subplot size (height) and shape (aspect) Adds colour-coded KDEs within each facet