Grouping Rows in pandas

Last Updated : 14 Jan, 2019

Pandas is the most popular Python library that is used for data analysis. It provides highly optimized performance with back-end source code is purely written in C or Python. Let's see how to group rows in Pandas Dataframe with help of multiple examples. Example 1: For grouping rows in Pandas, we will start with creating a pandas dataframe first.

Python3

# importing Pandas import pandas as pd # example dataframe example = {'Team':['Arsenal', 'Manchester United', 'Arsenal', 'Arsenal', 'Chelsea', 'Manchester United', 'Manchester United', 'Chelsea', 'Chelsea', 'Chelsea'], 'Player':['Ozil', 'Pogba', 'Lucas', 'Aubameyang', 'Hazard', 'Mata', 'Lukaku', 'Morata', 'Giroud', 'Kante'], 'Goals':[5, 3, 6, 4, 9, 2, 0, 5, 2, 3] } df = pd.DataFrame(example) print(df)

Now, create a grouping object, means an object that represents that particular grouping.

Python3

total_goals = df['Goals'].groupby(df['Team']) # printing the means value print(total_goals.mean())

Output:

Example 2:

Python3 1==

import pandas as pd # example dataframe example = {'Team':['Australia', 'England', 'South Africa',  'Australia', 'England', 'India', 'India',  'South Africa', 'England', 'India'],    'Player':['Ricky Ponting', 'Joe Root', 'Hashim Amla',  'David Warner', 'Jos Buttler', 'Virat Kohli',  'Rohit Sharma', 'David Miller', 'Eoin Morgan',  'Dinesh Karthik'],    'Runs':[345, 336, 689, 490, 989, 672, 560, 455, 342, 376],    'Salary':[34500, 33600, 68900, 49000, 98899,  67562, 56760, 45675, 34542, 31176] } df = pd.DataFrame(example) total_salary = df['Salary'].groupby(df['Team']) # printing the means value print(total_salary.mean())