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 in a Pandas DataFrame. This is where the sum() function can be used to perform column-wise calculations.

The column whose sum needs to be computed can be accessed by column name or index. Let's explore different approaches to calculate the sum of a specific column.

Creating a Sample DataFrame

First, let's create a DataFrame with sample data ?

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])
}

my_df = pd.DataFrame(my_data)
print("The dataframe is:")
print(my_df)

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

Method 1: Using Column Name

The most common way to get the sum of a specific column is by passing the column name ?

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])
}

my_df = pd.DataFrame(my_data)

print("The sum of 'Age' column is:")
print(my_df['Age'].sum())

print("The sum of 'Value' column is:")
print(my_df['Value'].sum())

The sum of 'Age' column is:
236
The sum of 'Value' column is:
232.77

Method 2: Using Column Index

You can also access columns by their index position ?

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])
}

my_df = pd.DataFrame(my_data)

# Age column is at index 1
print("Sum using column index 1 (Age):")
print(my_df.iloc[:, 1].sum())

# Value column is at index 2
print("Sum using column index 2 (Value):")
print(my_df.iloc[:, 2].sum())

Sum using column index 1 (Age):
236
Sum using column index 2 (Value):
232.77

Method 3: Multiple Column Sums

You can calculate sums for multiple columns at once ?

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])
}

my_df = pd.DataFrame(my_data)

print("Sum of numeric columns:")
print(my_df[['Age', 'Value']].sum())

Sum of numeric columns:
Age      236.00
Value    232.77
dtype: float64

Conclusion

Use df['column_name'].sum() to get the sum of a specific column by name. For multiple columns, pass a list of column names to calculate sums efficiently. Column indexing with iloc provides an alternative when working with positional access.