Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Python Pandas - Draw vertical bar plots with nested grouping by two categorical variables in Seaborn
Bar Plot in Seaborn is used to show point estimates and confidence intervals as rectangular bars. The seaborn.barplot() is used for this. Plotting vertical bar plots grouped by a categorical variable, by passing categorical variables using x, y or hue parameter.
Let’s say the following is our dataset in the form of a CSV file − Cricketers2.csv
At first, import the required libraries −
import seaborn as sb import pandas as pd import matplotlib.pyplot as plt
Load data from a CSV file into a Pandas DataFrame −
dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv")
Plotting vertical bar plots grouped by two categorical variables. The hue parameter also set
sb.barplot(x = dataFrame["Role"], y = dataFrame["Matches"], hue = "Academy", data= dataFrame)
Example
Following is the code −
import seaborn as sb
import pandas as pd
import matplotlib.pyplot as plt
# Load data from a CSV file into a Pandas DataFrame
dataFrame = pd.read_csv("C:\Users\amit_\Desktop\Cricketers2.csv")
# plotting vertical bar plots grouped by two categorical variables
# hue parameter also set
sb.barplot(x = dataFrame["Role"], y = dataFrame["Matches"], hue = "Academy", data= dataFrame)
# display
plt.show()Output
This will produce the following output −
Updated on: 29-Sep-2021
718 Views
Advertisements