RETAIL PERFORMANCE — DATA DICTIONARY
All records are original synthetic practice data generated for Data Analyst Career. No real people or businesses are represented. You may use these files in personal learning and public portfolios with source credit to DataAnalystCareer.com. Label all results as synthetic. These simplified datasets are not real business benchmarks.

Grain: one order line. There are 200 orders with 3 lines each (600 rows).
Coverage: January–June 2026. Currency: fictional USD values.

order_line_id: unique, non-null line identifier.
order_id: order identifier; repeats across its three lines.
order_date: transaction date, ISO YYYY-MM-DD.
region: East, West, or Central; consistent within an order.
category: Accessories, Electronics, or Home.
quantity: positive integer units on the line.
unit_price: pre-discount selling price per unit.
unit_cost: cost per unit; excludes overhead, tax, shipping, and marketing.
discount_rate: decimal fraction, e.g. 0.20 means 20% off.
returned: 1 means fully returned; 0 means not returned.

METRIC RULES
Net revenue = quantity * unit_price * (1 - discount_rate), for returned=0 only.
Recognized cost = quantity * unit_cost, for returned=0 only.
Gross profit = net revenue - recognized cost.
Gross margin rate = total gross profit / total net revenue, guarding zero denominators.
Return rate = returned lines / all lines, NOT returned orders / all orders.
Returned lines have zero revenue and zero recognized cost in this simplified practice model. No return date is modeled. Do not infer actual accounting policy from this exercise.

IMPORT CONTROL TOTALS (whole file, before any date or region filtering)
Rows: 600
Distinct order_line_id: 600
Distinct order_id: 200
Returned lines: 50
Quantity, including returned lines: 2072
Net revenue per the above rule: 152858.50
Recognized cost: 99995.70
Gross profit: 52862.80

CHECKS
Verify unique line IDs, three rows per order, rates between 0 and 1, positive quantities, and consistency of date and region within orders. Reconcile total revenue to the sum of monthly revenue. Calculate margin from sums, not an average of line margins.