Cumulative percentage of a column in Pandas – Python

Cumulative Percentage is calculated by the mathematical formula of dividing the cumulative sum of the column by the mathematical sum of all the values and then multiplying the result by 100. This is also applicable in Pandas Data frames.
Here, the pre-defined cumsum() and sum() functions are used to compute the cumulative sum and sum of all the values of a column.
Syntax:

df[cum_percent] = 100 * (df[‘column_name’].cumsum()/df[‘column_name’].sum()) 

Example 1:

Python3

import pandas as pd
import numpy as np

# Create a DataFrame
df1 = {
     'Name':['abc','bcd','cde','def','efg','fgh','ghi'],
   'Math_score':[52,87,49,74,28,59,48]}

df1 = pd.DataFrame(df1, columns=['Name','Math_score'])

# Computing Cumulative Percentage
df1['cum_percent'] = 100*(df1.Math_score.cumsum() / df1.Math_score.sum())

df1

Output:

Example 2:

Python3

import pandas as pd
import numpy as np

# Create a DataFrame
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]
}

df1 = pd.DataFrame(df1,columns=['Name','Math_score','Eng_score'])

# Computing cumulative Percentage
df1['Eng_cum_percent'] = (df1.Eng_score.cumsum() / df1.Eng_score.sum()) * 100

df1

Output: