Table of Contents
To group a Pandas DataFrame by its index and perform a calculation on the grouped data, first use the “groupby” function to group the data by the desired index. Then, specify the desired calculation to be performed on the grouped data using built-in Pandas functions such as “sum”, “mean”, or “count”. This will return a new DataFrame with the calculated values for each group based on the specified index. This method is useful for analyzing and summarizing data based on specific categories within the index.
Pandas: Group By Index and Perform Calculation
You can use the following methods to group by one or more index columns in pandas and perform some calculation:
Method 1: Group By One Index Column
df.groupby('index1')['numeric_column'].max()
Method 2: Group By Multiple Index Columns
df.groupby(['index1', 'index2'])['numeric_column'].sum()
Method 3: Group By Index Column and Regular Column
df.groupby(['index1', 'numeric_column1'])['numeric_column2'].nunique()
The following examples show how to use each method with the following pandas DataFrame that has a MultiIndex:
import pandas as pd
#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'B'],
'position': ['G', 'G', 'G', 'F', 'F', 'G', 'G', 'F', 'F', 'F'],
'points': [7, 7, 7, 19, 16, 9, 10, 10, 8, 8],
'rebounds': [8, 8, 8, 10, 11, 12, 13, 13, 15, 11]})
#set 'team' column to be index column
df.set_index(['team', 'position'], inplace=True)
#view DataFrame
df
points rebounds
team position
A G 7 8
G 7 8
G 7 8
F 19 10
F 16 11
B G 9 12
G 10 13
F 10 13
F 8 15
F 8 11
Method 1: Group By One Index Column
The following code shows how to find the max value of the ‘points’ column, grouped by the ‘position’ index column:
#find max value of 'points' grouped by 'position index column
df.groupby('position')['points'].max()
position
F 19
G 10
Name: points, dtype: int64Method 2: Group By Multiple Index Columns
The following code shows how to find the sum of the ‘points’ column, grouped by the ‘team’ and ‘position’ index columns:
#find max value of 'points' grouped by 'position index column
df.groupby(['team', 'position'])['points'].sum()
team position
A F 35
G 21
B F 26
G 19
Name: points, dtype: int64Method 3: Group By Index Column & Regular Column
The following code shows how to find the number of unique values in the ‘rebounds’ column, grouped by the index column ‘team’ and the ordinary column ‘points’:
#find max value of 'points' grouped by 'position index column
df.groupby(['team', 'points'])['rebounds'].nunique()
team points
A 7 1
16 1
19 1
B 8 2
9 1
10 1
Name: rebounds, dtype: int64Additional Resources
The following tutorials explain how to perform other common operations in pandas:
Cite this article
stats writer (2024). How can I group a Pandas DataFrame by its index and perform a calculation on the grouped data?. PSYCHOLOGICAL SCALES. Retrieved from https://scales.arabpsychology.com/stats/how-can-i-group-a-pandas-dataframe-by-its-index-and-perform-a-calculation-on-the-grouped-data/
stats writer. "How can I group a Pandas DataFrame by its index and perform a calculation on the grouped data?." PSYCHOLOGICAL SCALES, 2 Jul. 2024, https://scales.arabpsychology.com/stats/how-can-i-group-a-pandas-dataframe-by-its-index-and-perform-a-calculation-on-the-grouped-data/.
stats writer. "How can I group a Pandas DataFrame by its index and perform a calculation on the grouped data?." PSYCHOLOGICAL SCALES, 2024. https://scales.arabpsychology.com/stats/how-can-i-group-a-pandas-dataframe-by-its-index-and-perform-a-calculation-on-the-grouped-data/.
stats writer (2024) 'How can I group a Pandas DataFrame by its index and perform a calculation on the grouped data?', PSYCHOLOGICAL SCALES. Available at: https://scales.arabpsychology.com/stats/how-can-i-group-a-pandas-dataframe-by-its-index-and-perform-a-calculation-on-the-grouped-data/.
[1] stats writer, "How can I group a Pandas DataFrame by its index and perform a calculation on the grouped data?," PSYCHOLOGICAL SCALES, vol. X, no. Y, ص Z-Z, July, 2024.
stats writer. How can I group a Pandas DataFrame by its index and perform a calculation on the grouped data?. PSYCHOLOGICAL SCALES. 2024;vol(issue):pages.
