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Global E-Commerce Sales & Margin 2026
120 rows
Data Quality Profile
98% Health
TOTAL ROWS
120
COLUMNS
9
NULL VALUES
0 (0.0%)
DUPLICATES
0
Schema Columns (9)
DuckDB Types
order_id
string
order_date
date
region
string
category
string
customer_tier
string
revenue
number
cost
number
profit
number
churn_risk
number
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# DataQuery AI - Python Analysis Workspace # The active dataset is loaded as pandas DataFrame 'df' import pandas as pd import numpy as np # Group revenue and profit by region summary = df.groupby('region').agg({ 'revenue': 'sum', 'profit': 'sum' }).reset_index() summary['margin_pct'] = (summary['profit'] / summary['revenue']) * 100 summary = summary.sort_values(by='revenue', ascending=False) print("Aggregated regional margin performance:") print(summary)
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RECORDS
4
PRIMARY METRIC
revenue
EXEC SPEED
18.4ms
Timeline:
1
Load sales_q3_global.csv
2
Regional Margin Aggregation
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