sdks/python: enable named aggregation to deferred DataFrame groupby

[mohamedawnallah]

Description

In this commit, we enable named aggregation to deferred DataFrame groupby.

Fixes #27278

Current Behavior

Before	After

Verifying Named Aggregation in Beam DataFrame GroupBy

import pandas as pd
import apache_beam as beam
from apache_beam.dataframe import convert

employee_data = {
    'Department': ['HR', 'HR', 'Engineering', 'Engineering', 'Sales', 'Sales'],
    'Salary': [50000, 55000, 70000, 75000, 60000, 65000],
    'Performance_Score': [8, 9, 7, 6, 8, 8],
    'Years_of_Experience': [2, 5, 8, 10, 3, 4]
}

employee_df = pd.DataFrame(employee_data)

CSV_HEADER = "Department,Mean_Salary,Median_Performance_Score,Total_Years_of_Experience"

def process_aggregated_data(row):
    """Convert aggregated data into a format suitable for CSV output."""
    department = row.Department
    salary = row.Mean_Salary
    performance_score = row.Median_Performance_Score
    experience = row.Total_Years_of_Experience
    return f"{department},{salary},{performance_score},{experience}"

with beam.Pipeline() as pipeline:
    # Convert pandas DataFrame to PCollection.
    employee_pcollection = convert.to_pcollection(employee_df, pipeline=pipeline)
    employee_beam_df = convert.to_dataframe(employee_pcollection)

    # Group by Department and aggregate functions:
    # mean salary, median performance score, and sum of years of experience
    with beam.dataframe.allow_non_parallel_operations():
        employee_aggregated_df = employee_beam_df.groupby('Department').agg(
            Mean_Salary=('Salary', 'mean'),
            Median_Performance_Score=('Performance_Score', 'median'),
            Total_Years_of_Experience=('Years_of_Experience', 'sum')
        ).reset_index()

    # Write the CSV, including header and data.
    csv_pcollection = (
        convert.to_pcollection(employee_aggregated_df)
        | beam.Map(lambda row: process_aggregated_data(row))
        | beam.io.WriteToText(
            "employee_data_grouped_by_department",
            file_name_suffix=".csv",
            header=CSV_HEADER
        )
    )

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[github-actions]

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[mohamedawnallah]

Run Prism_Python PreCommit 3.9

[github-actions]

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[liferoad]

Thanks!

[github-actions]

Reminder, please take a look at this pr: @tvalentyn

[tvalentyn]

Thanks for the change and follow-up, @mohamedawnallah . For future changes, please don't squash reviewed and unreviewed commits before the review process has concluded; instead, add follow-up commits on the branch, leaving prior commits as is.

Otherwise, reviewing is significantly harder.

[mohamedawnallah]

For future changes, please don't squash reviewed and unreviewed commits before the review process has concluded; instead, add follow-up commits on the branch, leaving prior commits as is.

I will keep this in mind next time, Thanks 🙏

Otherwise, reviewing is significantly harder.

Thanks for your patience @tvalentyn 🙏