Pandas - Apply multiple functions to a DataFrame column using apply()

Last update on December 21 2024 09:14:37 (UTC/GMT +8 hours)

Pandas: Custom Function Exercise-10 with Solution

Write a Pandas function that applies multiple functions to a single column using apply() function.

This exercise demonstrates how to apply multiple functions to a single column in a Pandas DataFrame using apply().

Sample Solution:

Code :

import pandas as pd

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

# Define two custom functions
def add_one(x):
    return x + 1

def square(x):
    return x ** 2

# Apply both functions to column 'A'
df['A_plus_1'] = df['A'].apply(add_one)
df['A_squared'] = df['A'].apply(square)

# Output the result
print(df)

Output:

   A  B  A_plus_1  A_squared
0  1  4         2          1
1  2  5         3          4
2  3  6         4          9                            

Explanation:

• Created a DataFrame with columns 'A' and 'B'.
• Defined two functions: add_one() to increment by 1 and square() to square the values.
• Applied both functions separately to column 'A' and stored the results in new columns 'A_plus_1' and 'A_squared'.
• Displayed the updated DataFrame with the new columns.

Python-Pandas Code Editor:

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