Pandas - Applying Conditional Logic to DataFrame Rows with apply()

Last update on December 21 2024 07:41:05 (UTC/GMT +8 hours)

Pandas: Custom Function Exercise-12 with Solution

Write a Pandas program that uses apply() to work with conditional logic in DataFrame.

In this exercise we have applied a custom function that uses conditional logic to set values based on a threshold.

Sample Solution :

Code :

import pandas as pd

# Create a sample DataFrame
df = pd.DataFrame({
    'A': [10, 20, 30],
    'B': [5, 15, 25]
})

# Define a function with conditional logic
def threshold(row):
    return 'High' if row['A'] > 15 else 'Low'

# Apply the function to the rows
df['A_threshold'] = df.apply(threshold, axis=1)

# Output the result
print(df)

Output:

    A   B A_threshold
0  10   5         Low
1  20  15        High
2  30  25        High                                     

Explanation:

• Created a DataFrame with columns 'A' and 'B'.
• Defined a function threshold() that labels 'A' as 'High' if it’s greater than 15, otherwise 'Low'.
• Applied this function row-wise using apply() with axis=1.
• Added the labels as a new column 'A_threshold' in the DataFrame.

Python-Pandas Code Editor:

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