❮ Previous Next ❯

Bar Plot

  • This module teaches how to create bar plots in Seaborn for categorical data. You will learn about mean aggregation, using hue for grouping, and changing the orientation of bars to enhance data visualization clarity in Python.

  • Categorical Data Visualization

    Theory

    Bar plots are used when:

    • X-axis = Category (like product, day, city)

    • Y-axis = Numerical value (sales, marks, revenue)

    • Comparison between categories

    Seaborn automatically:

    • Calculates mean

    • Shows confidence interval

    Basic Bar Plot Example

Average Total Bill per Day – Bar Plot

This code creates a bar plot using Seaborn to visualize the average total bill amount for each day of the week from the tips dataset. 

import seaborn as sns
import matplotlib.pyplot as plt

# Load dataset
df = sns.load_dataset("tips")

# Basic Bar Plot
sns.barplot(x="day", y="total_bill", data=df)

plt.title("Average Total Bill per Day")
plt.show()
Lesson image

  • Explanation:

    • x="day" → Categorical variable

    • y="total_bill" → Numerical variable

    • Automatically calculates mean


    Mean & Aggregation

    Theory

    By default:

    • Seaborn calculates mean

    • Shows confidence interval

    You can change aggregation using estimator.

    Example – Using Median

Median Total Bill per Day – Bar Plot

This code creates a bar plot using Seaborn where the median total bill is calculated for each day instead of the default mean. 

import numpy as np

sns.barplot(x="day", y="total_bill", data=df, estimator=np.median)

plt.title("Median Total Bill per Day")
plt.show()
Lesson image

  • Using hue

    Theory

    hue adds another categorical variable.

    Used for:

    • Gender comparison

    • Product category comparison

    • Year comparison

    Example

Total Bill per Day – Comparison by Gender

This code creates a grouped bar plot using Seaborn to compare total bill amounts per day for male and female customers. 

sns.barplot(x="day", y="total_bill", hue="sex", data=df)

plt.title("Total Bill per Day (Male vs Female)")
plt.show()
Lesson image

  • Orientation Change

    Theory

    Default orientation = Vertical

    To make horizontal:

    • Swap x and y

    Useful when:

    • Category names are long

    • Better readability needed

    Horizontal Bar Plot

Average Total Bill per Day – Horizontal Bar Plot

This code creates a horizontal bar plot using Seaborn, which is useful when category names are long or for better readability. 

sns.barplot(y="day", x="total_bill", data=df)

plt.title("Horizontal Bar Plot")
plt.show()
Lesson image
❮ Previous Next ❯