Purpose

Total Orders & Revenue: 41 orders generating $12,511.53 (average order value: $305.16) across a single country and 12 cities
Geographic Concentration: New York, NY dominates with 8 orders ($3,020.76), while top 3 cities account for 47.5% of total revenue
State Performance: Texas leads with 11 orders, followed by New York (8) and California (10), indicating multi-state distribution
Data Quality: 51.2% retention after deduplication and geographic validation; 48.8% of raw records lacked complete location data

This section documents the data cleaning process applied to raw Shopify order exports before geographic analysis. The 51.2% retention rate reflects intentional deduplication and geographic filtering necessary to transform line-item-level transaction data into order-level geographic insights, which directly supports the objective of identifying top-performing regions and revenue patterns.

Key Findings

Retention Rate (51.2%): Nearly half of initial rows were removed, primarily due to multi-row line items being deduplicated to order level and exclusion of records missing billing geography data
Rows Removed (39 of 80): The substantial removal reflects the structured nature of e-commerce exports where single orders generate multiple rows when containing multiple line items
Final Dataset (41 orders): Represents the clean, order-level foundation for all subsequent geographic aggregations and revenue analysis

Interpretation

The 51.2% retention rate is appropriate for this analysis type and does not indicate data quality problems. The documented removal reasons—line-item deduplication and geographic filtering—are standard preprocessing steps for order-level geographic analysis. This ensures each order is counted once with accurate billing location attribution, which is essential for reliable city, province, and country-level revenue calculations presented in downstream datasets.

Context

The analysis assumes billing address accuracy and uses the first line-item row's total for order revenue. No train/