Count plots

Seaborn basics

1 min read

Published Oct 7 2025

ChartsGraphsMatplotlibNumPyPandasPythonSeabornVisualisation

seaborn.countplot() is used to count the number of occurrences of each category in a variable and display those counts as bars.

It’s basically like a barplot of counts, except you don’t need to compute the counts yourself — Seaborn does it automatically.

Syntax:

sns.countplot(

data=None,

x=None,

y=None,

hue=None,

order=None,

hue_order=None,

palette=None,

orient=None,

dodge=True,

width=0.8,

**kwargs

)

Parameters:

data = DataFrame containing the data
x, y = Variable(s) for categories (only one is usually needed)
hue = Adds subcategories (grouped bars)
order / hue_order = Order of categories/subcategories
palette = Colour palette
orient = "v" (vertical) or "h" (horizontal)
dodge = Separate hue bars side by side (default: True)
width = Bar width

Basic example

import seaborn as sns

import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.countplot(data=tips, x="day")

plt.show()

This shows how many records (meals) occurred on each day of the week.

Add hue (subgroups)

import seaborn as sns

import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.countplot(data=tips, x="day", hue="sex")

plt.show()

Bars are split by sex.
Each day shows two bars — one for each group in sex.

Horizontal bars

import seaborn as sns

import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.countplot(data=tips, y="day", hue="sex", orient="h")

plt.show()

Flips the bars horizontally — helpful for long category names.

Specify category order

import seaborn as sns

import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.countplot(

data=tips,

x="day",

order=["Sun", "Sat", "Fri", "Thur"]

)

plt.show()

Controls the order of bars along the x-axis.

Customise colours and style

import seaborn as sns

import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.countplot(

data=tips,

x="day",

hue="sex",

palette="coolwarm",

edgecolor="black",

width=0.7

)

plt.show()

palette="coolwarm" → colourful scheme
edgecolor="black" → outlines bars
width=0.7 → slightly thinner bars

Count of multiple variables (via `hue`)

import seaborn as sns

import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.countplot(data=tips, x="smoker", hue="sex")

plt.show()

Shows how many male vs. female smokers and non-smokers there are.

seaborn count plot multiple variables example

Count plots

Seaborn basics

1 min read