Creating Pivot Table with Pandas

Hey Guys, today I’m going to create an article on PIVOT TABLE in Python with the help of Pandas.  So, Pivot Table is basically tabled summarize data, they can be used to find unique values in a field. This is a good way to quickly see all the values that appear in a field and also find typos and other inconsistencies.

We perform reading CSV File and convert into a Pivot table.

Sample Data which help us to create the Pivot Table.

Import Pandas module for reading CSV file

import pandas as pd

Read the CSV file using Pandas

data  = pd.read_csv(r"C:\Users\Jamaley\Videos\sample_csv.csv")

Data is a data frame variable which holds the CSV file.

Class	 Div	Score
Ramesh	 1st	4
Ramesh	 1st	24
Abhishek 2nd	31
Jamaley	 2nd	2
Jamaley	 1st	3
Rahul	 1st	4
Raja	 2nd	24
Rahul	 2nd	31
Raja	 1st	2
Nilesh	 1st	3
Jamaley	 2nd	2
Abhishek 2nd	3

Create a pivot table

pd.pivot_table(data, index=['Class','Div'])

Create a spreadsheet-style pivot table as a DataFrame. The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) on the index and columns of the result DataFrame.

Create a pivot table (Mean)

pd.pivot_table(data, index=['Class','Div'], aggfunc='mean')

taking the mean across columns

Create a pivot table (count)

pd.pivot_table(data, index=['Class','Div'], aggfunc='count')

Note Table Headers for CSV are as follow – Class, Div, Score.

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