Pandas - Applying a Custom Function Element-wise with applymap()

Last update on April 09 2025 12:53:15 (UTC/GMT +8 hours)

1. Apply Custom Function Element-wise with applymap()

Write a Pandas program that apply a custom function element-wise using applymap() function.

In this exercise, we have applied a custom function that squares each element of a Pandas DataFrame element-wise using applymap().

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 square each element
def square(x):
    return x ** 2

# Apply the custom function element-wise using applymap()
df_squared = df.applymap(square)

# Output the result
print(df_squared)

Output:

   A   B   C
0  1  16  49
1  4  25  64
2  9  36  81                                      

Explanation:

• Created a DataFrame with columns 'A', 'B', 'C'.
• Defined a function square() that squares its input.
• Applied the square() function to each element of the DataFrame using applymap().
• Displayed the resulting DataFrame where each element has been squared.

For more Practice: Solve these Related Problems:

• Write a Pandas program to apply a custom function element-wise using applymap() that multiplies each numeric value by 2.
• Write a Pandas program to use applymap() to convert all string entries in a DataFrame to uppercase.
• Write a Pandas program to apply a custom lambda function using applymap() that replaces negative numbers with zero.
• Write a Pandas program to use applymap() on a DataFrame to format float numbers to 2 decimal places.

Python-Pandas Code Editor:

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