Python | Pivot tables in python

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Summing with pivot tables

You can sum values in a pivot table by specifying the aggfunc parameter in the pivot_table() method as 'sum'. This will create a pivot table that summarizes the data by grouping and summing values based on the specified rows, columns, and values.

Here's an example:

import pandas as pd

# create a pandas DataFrame

df = pd.DataFrame({'Region': ['North', 'North', 'South', 'South', 'West', 'West'],

'Month': ['Jan', 'Feb', 'Jan', 'Feb', 'Jan', 'Feb'],

'Salesperson': ['Alice', 'Bob', 'Charlie', 'Dave', 'Eve', 'Frank'],

'Sales': [100, 200, 150, 50, 75, 125],

'Profit': [20, 50, 30, 10, 15, 25]})

# create a pivot table that summarizes the sales data by region and month

pivot = pd.pivot_table(df, values=['Sales'], index=['Region'], columns=['Month'], aggfunc='sum')

print(pivot)

This will create a pivot table that summarizes the sales data by region and month, with values grouped and summed. The resulting output will be:

Sales

Month Feb Jan

Region

North 200 100

South 50 150

West 200 75

In this example, the aggfunc parameter is set to 'sum', which causes the values in the pivot table to be summed based on the specified rows and columns. You can use other aggregation functions such as 'mean', 'min', 'max', or a custom function by passing the desired function name or function object to the aggfunc parameter.