Box plots

seaborn.boxplot() is used to visualise the distribution of a numerical variable and compare it across categories.

A box plot (a.k.a. box-and-whisker plot) shows:

• The median (middle value)
• The quartiles (Q1, Q3) — 25th and 75th percentiles
• The interquartile range (IQR) — Q3 − Q1
• Whiskers — roughly 1.5×IQR beyond the box
• Outliers — data points outside whiskers

It’s great for spotting spread, symmetry, and outliers in your data.

Syntax:

Parameters:

• data = DataFrame containing the data
• x, y = Variables for categories and values
• hue = Adds subcategories (side-by-side boxes)
• order / hue_order = Specify category order
• palette = Colour scheme
• orient = "v" (vertical) or "h" (horizontal)
• width = Width of boxes
• dodge = Separate hue boxes side by side
• notch = Draw notches to show confidence around median
• flierprops = Customise outlier points
• medianprops = Customise median line style

Basic example

Shows the distribution of total bills for each day.

Add hue (subgroups)

• Each day has two boxes, one per sex.
• Allows you to compare distributions between men and women for each day.

Horizontal boxes

Flips the boxes horizontally — good for long category labels.

Customise colors and style

• palette="pastel" → soft colour theme
• medianprops → style the median line
• boxprops → outline colour

Show or hide outliers

Removes outlier points (dots beyond whiskers).

Add notches for median confidence

Adds notches to indicate an approximate 95% confidence interval around the median.

Control category order

Controls the order of categories on the x-axis.

Using hue for subgroups

Compares distributions of total bill across smokers/non-smokers for each sex.