Pandas - Applying a Custom Function to Rows using apply()

Last update on May 05 2025 13:05:11 (UTC/GMT +8 hours)

2. Apply Custom Function to Each Row Using apply()

Write a Pandas program that apply a custom function to each row using apply() function.

In this exercise, we have applied a custom function that calculates the sum of each row in a DataFrame using apply() function.

Sample Solution:

Code :

import pandas as pd

# Create a sample DataFrame
df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
})

# Define a custom function to calculate the sum of a row
def row_sum(row):
    return row.sum()

# Apply the custom function row-wise
df['Row_Sum'] = df.apply(row_sum, axis=1)

# Output the result
print(df)

Output:

   A  B  C  Row_Sum
0  1  4  7       12
1  2  5  8       15
2  3  6  9       18

Explanation:

Created a DataFrame with columns 'A', 'B', 'C'.
Defined a function row_sum() to calculate the sum of a row.
Applied row_sum() row-wise using apply() with axis=1.
Added the row sums as a new column to the DataFrame.

For more Practice: Solve these Related Problems:

Write a Pandas program to calculate the sum of each row using a custom function applied with apply(axis=1).
Write a Pandas program to create a new column that concatenates values from multiple columns by applying a custom function to each row.
Write a Pandas program to apply a custom function row-wise that returns the maximum value among selected columns.
Write a Pandas program to compute a new metric for each row by applying a custom function using apply(axis=1) with conditional logic.

Go to:

Previous: Apply Custom Function to Multiple Columns Using apply().
Next: Apply Custom Function to Each Column Using apply().

Python-Pandas Code Editor:

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