How to Sum Values within Groups Using Pandas GroupBy?

How to Calculate Summation Using Pandas GroupBy

In data science, it is often necessary to aggregate data to gain insights. One common aggregation technique is summing values within groups. The Python library Pandas provides the versatile GroupBy function to group data and perform various operations, including summation.

Consider the following DataFrame:

Fruit	Date	Name	Number
Apples	10/6/2016	Bob	7
Apples	10/6/2016	Bob	8
Apples	10/6/2016	Mike	9
Apples	10/7/2016	Steve	10
Apples	10/7/2016	Bob	1
Oranges	10/7/2016	Bob	2
Oranges	10/6/2016	Tom	15
Oranges	10/6/2016	Mike	57
Oranges	10/6/2016	Bob	65
Oranges	10/7/2016	Tony	1
Grapes	10/7/2016	Bob	1
Grapes	10/7/2016	Tom	87
Grapes	10/7/2016	Bob	22
Grapes	10/7/2016	Bob	12
Grapes	10/7/2016	Tony	15

To obtain the total number of Fruits purchased by each Name, use the GroupBy.sum() method:

df.groupby(['Name', 'Fruit']).sum()

This will produce the following output:

Fruit	Name	Number
Apples	Bob	16
Apples	Mike	9
Apples	Steve	10
Grapes	Bob	35
Grapes	Tom	87
Grapes	Tony	15
Oranges	Bob	67
Oranges	Mike	57
Oranges	Tom	15
Oranges	Tony	1

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