medium Data Analysis

Category Sales Aggregation

The Brief

The finance team needs a category-level breakdown showing total units, total revenue, and average revenue per transaction for each product category. Use pandas groupby with multiple aggregations to produce the report and print it as a clean table.

Acceptance Criteria

Tap a criterion to mark it off as you work. Tap a category header to expand or collapse.

2 Group the data by the Category column

4 Round the mean revenue to 2 decimal places

5 Print the resulting summary table sorted by total revenue descending

1 Load the dataset into a pandas DataFrame

3 Aggregate three measures at once: sum of Units, sum of Revenue, mean of Revenue

💡 Hints 0 / 3

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solution.py

Python 3

import pandas as pd
import io

data = """Date,Category,Product,Units,Revenue
2024-03-01,Hardware,Drill,4,160.00
2024-03-02,Software,License,12,720.00
2024-03-03,Hardware,Saw,3,90.00
2024-03-04,Software,License,8,480.00
2024-03-05,Services,Install,2,250.00
2024-03-06,Hardware,Drill,5,200.00
2024-03-07,Services,Install,1,125.00
2024-03-08,Software,Plugin,20,400.00"""

df = pd.read_csv(io.StringIO(data))

# Group by Category and aggregate
# Sort by total revenue descending
# Print the result

Console