How to get the sum of a specific column of a dataframe in Pandas Python?

Sometimes, it may be required to get the sum of a specific column. This is where the ‘sum’ function can be used.

The column whose sum needs to be computed can be passed as a value to the sum function. The index of the column can also be passed to find the sum.

Let us see a demonstration of the same −

Example

 Live Demo

import pandas as pd my_data = {'Name':pd.Series(['Tom','Jane','Vin','Eve','Will']),'Age':pd.Series([45, 67, 89, 12, 23]),'value':pd.Series([8.79,23.24,31.98,78.56,90.20]) } print("The dataframe is :") my_df = pd.DataFrame(my_data) print(my_df) print("The sum of 'age' column is :") print(my_df.sum(1))

Output

The dataframe is :     Name  Age value 0   Tom   45   8.79 1   Jane  67   23.24 2   Vin   89   31.98 3   Eve   12   78.56 4   Will   23  90.20 The sum of 'age' column is : 0  53.79 1  90.24 2  120.98 3  90.56 4  113.20 dtype: float64

Explanation

• The required libraries are imported, and given alias names for ease of use.

• Dictionary of series consisting of key and value is created, wherein a value is actually a series data structure.

• This dictionary is later passed as a parameter to the ‘Dataframe’ function present in the ‘pandas’ library

• The dataframe is printed on the console.

• We are looking at computing the sum of the ‘Age’ column.

• The name of the column whose sum needs to be computed is passed as a parameter to the ‘sum’ function.

• The sum is printed on the console.