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

Pandas: Custom Function Exercise-2 with Solution

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.

Python-Pandas Code Editor:

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