Combining GroupBy with Transform in Pandas

Last update on December 21 2024 09:22:52 (UTC/GMT +8 hours)

Pandas Advanced Grouping and Aggregation: Exercise-11 with Solution

Combining GroupBy with Transform:
Write a Pandas program to combine GroupBy with Transform to perform complex data transformations on grouped data.

Sample Solution:

Python Code :

import pandas as pd
# Sample DataFrame
data = {'Category': ['A', 'A', 'B', 'B', 'C', 'C'],
        'Value': [1, 2, 3, 4, 5, 6]}

df = pd.DataFrame(data)
print("Sample DataFrame:")
print(df)
# Group by 'Category' and transform by calculating the mean
print("\nGroup by 'Category' and transform by calculating the mean:")
transformed = df.groupby('Category').transform('mean')
print(transformed)

Output:

Sample DataFrame:
  Category  Value
0        A      1
1        A      2
2        B      3
3        B      4
4        C      5
5        C      6

Group by 'Category' and transform by calculating the mean:
   Value
0    1.5
1    1.5
2    3.5
3    3.5
4    5.5
5    5.5

Explanation:

• Import pandas.
• Create a sample DataFrame.
• Group by 'Category'.
• Transform by calculating the mean for each group.
• Print the transformed DataFrame.

Python Code Editor:

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