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Create a Pivot Table with multiple columns – Python Pandas
We can create a Pivot Table with multiple columns. To create a Pivot Table, use the pandas.pivot_table to create a spreadsheet-style pivot table as a DataFrame.
At first, import the required library −
import pandas as pd
Create a DataFrame with Team records −
dataFrame = pd.DataFrame({'Team ID': {0: 5, 1: 9, 2: 6, 3: 11, 4: 2, 5: 7 },'Team Name': {0: 'India', 1: 'Australia', 2: 'Bangladesh', 3: 'South Africa', 4: 'Sri Lanka', 5: 'England'},'Team Points': {0: 95, 1: 93, 2: 42, 3: 60, 4: 80, 5: 55},'Team Rank': {0: 'One', 1: 'Two', 2: 'Six', 3: 'Four', 4: 'Three', 5: 'Five'}})Create a Pivot Table with multiple columns. We have set more than more than two columns −
pd.pivot_table(dataFrame, index = ["Team ID", "Team Name", "Team Rank"])
Example
Following is the code −
import pandas as pd
# create DataFrame with Team records
dataFrame = pd.DataFrame({'Team ID': {0: 5, 1: 9, 2: 6, 3: 11, 4: 2, 5: 7 },'Team Name': {0: 'India', 1: 'Australia', 2: 'Bangladesh', 3: 'South Africa', 4: 'Sri Lanka', 5: 'England'},'Team Points': {0: 95, 1: 93, 2: 42, 3: 60, 4: 80, 5: 55},'Team Rank': {0: 'One', 1: 'Two', 2: 'Six', 3: 'Four', 4: 'Three', 5: 'Five'}})
print("\n... Pivot ...")
# multiple columns
print(pd.pivot_table(dataFrame, index = ["Team ID", "Team Name", "Team Rank"]))Output
This will produce the following output −
... Pivot ... Team Points Team ID Team Name Team Rank 2 Sri Lanka Three 80 5 India One 95 6 Bangladesh Six 42 7 England Five 55 9 Australia Two 93 11 South Africa Four 60
Updated on: 22-Sep-2021
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