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

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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.

Updated on 10-Dec-2020 13:08:54