Combining GroupBy with Transform in Pandas
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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Previous: Using named Aggregations in Pandas GroupBy.
Next: GroupBy and Apply different functions using a Dictionary in Pandas.
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