How to calculate the Percentage of a column in Pandas ?
A Percentage is calculated by the mathematical formula of dividing the value by the sum of all the values and then multiplying the sum by 100. This is also applicable in Pandas Dataframes.
Here, the pre-defined sum() method of pandas series is used to compute the sum of all the values of a column.
Syntax: Series.sum()
Return: Returns the sum of the values.
Formula:
df[percent] = (df['column_name'] / df['column_name'].sum()) * 100
Example 1: calculate the Percentage of a column in Pandas
Python3
# Import required libraries import pandas as pd import numpy as np # Dictionary df1 = { 'Name' : [ 'abc' , 'bcd' , 'cde' , 'def' , 'efg' , 'fgh' , 'ghi' ], 'Math_score' : [ 52 , 87 , 49 , 74 , 28 , 59 , 48 ]} # Create a DataFrame df1 = pd.DataFrame(df1, columns = [ 'Name' , 'Math_score' ]) # Calculating Percentage df1[ 'percent' ] = (df1[ 'Math_score' ] / df1[ 'Math_score' ]. sum ()) * 100 # Show the dataframe df1 |
Output:
Example 2:
Python3
# Import pandas library import pandas as pd # Dictionary df1 = { 'Name' : [ 'abc' , 'bcd' , 'cde' , 'def' , 'efg' , 'fgh' , 'ghi' ], 'Math_score' : [ 52 , 87 , 49 , 74 , 28 , 59 , 48 ], 'Eng_score' : [ 34 , 67 , 25 , 89 , 92 , 45 , 86 ] } # Create a DataFrame df1 = pd.DataFrame(df1, columns = [ 'Name' , 'Math_score' , 'Eng_score' ]) # Calculate Percentage df1[ 'Eng_percent' ] = (df1[ 'Eng_score' ] / df1[ 'Eng_score' ]. sum ()) * 100 # Show the dataframe df1 |
Output:
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