Sample E-Commerce Products Catalog Dataset CSV

Q: "Can I use this CSV to test product imports in Shopify or WooCommerce?"

"Yes. The column headers correspond to standard e-commerce fields (SKU, Title, Category, Price, Inventory) and can be mapped during the store import wizard."

Q: "How can I calculate profit margins from this dataset in Excel or Pandas?"

"Use the formula: `(Price_USD - Cost_USD) / Price_USD` to derive the gross margin percentage for each product SKU."

Q: "Is this dataset licensed for commercial applications?"

"Yes. All product records in this dataset are released under the public domain / MIT license, free for personal and commercial usage without attribution."

Download a 50-item e-commerce product catalog dataset in CSV format. Includes SKUs, categories, retail pricing, inventory stock counts, and ratings.

Download CSV (4 KB)

File Format CSV

File Size 4 KB

Compatibility Shopify, WooCommerce, Magento, BigCommerce, SQL, Python, Excel

License Free (Personal & Commercial)

Template Highlights & Included Features

Realistic Multi-Category Catalog

Includes 20 diverse consumer products spanning Electronics, Home & Kitchen, Office Furniture, and Sports & Fitness categories.

10 Core E-Commerce Attributes

Pre-structured with Product_SKU, Product_Name, Category, Subcategory, Price_USD, Cost_USD, Stock_Quantity, Average_Rating, Weight_KG, and Status.

Clean Numerical Values

Retail prices and Wholesale Costs formatted as raw decimals without currency symbols, ready for immediate SQL math and profit margin formulas.

Ready for Store Importers

Formatted to align with standard product import columns for WooCommerce, Shopify CSV templates, and headless store test suites.

Building modern e-commerce storefronts, inventory tracking systems, or marketplace search engines requires realistic product data. Hardcoding placeholder titles like “Product 1” or “Test Item” fails to reveal real-world issues such as title wrapping, multi-level category navigation, and pricing calculations. This Sample E-Commerce Products Catalog Dataset (.csv) delivers an authentic retail inventory dataset.

Dataset Structure & Field Specifications

The dataset provides clean, normalized tabular records structured with the following attributes:

Column Name	Data Type	Sample Data	Definition
`Product_SKU`	String	`TECH-001`	Unique Stock Keeping Unit code
`Product_Name`	String	`Wireless Noise-Canceling Headphones`	Full consumer-facing product title
`Category`	String	`Electronics`	Top-level merchandising category
`Subcategory`	String	`Audio`	Granular product department
`Price_USD`	Decimal	`199.99`	Retail selling price
`Cost_USD`	Decimal	`85.00`	Wholesale Cost of Goods Sold (COGS)
`Stock_Quantity`	Integer	`142`	Available warehouse inventory count
`Average_Rating`	Decimal	`4.8`	Aggregated customer star review (1.0 - 5.0)
`Weight_KG`	Decimal	`0.35`	Unit shipping weight for logistics testing
`Status`	String	`In Stock` / `Low Stock`	Operational fulfillment state

Recommended Development Applications

E-Commerce Search & Filtering: Test instant search autosuggest, category facets, price range sliders, and in-stock toggles in Algolia, Meilisearch, or Elasticsearch.

Profit & Loss Financial Analysis: Practice modeling gross profit contribution per department using SQL window functions or Python Pandas:

import pandas as pd
df = pd.read_csv('sample-ecommerce-products-catalog.csv')
df['Gross_Profit'] = df['Price_USD'] - df['Cost_USD']
print(df.groupby('Category')['Gross_Profit'].mean())

Inventory Management & Reorder Points: Test automated alert triggers when Stock_Quantity falls below safety thresholds.

Frequently Asked Questions

Can I use this CSV to test product imports in Shopify or WooCommerce?

Yes. The column headers correspond to standard e-commerce fields (SKU, Title, Category, Price, Inventory) and can be mapped during the store import wizard.

How can I calculate profit margins from this dataset in Excel or Pandas?

Use the formula: `(Price_USD - Cost_USD) / Price_USD` to derive the gross margin percentage for each product SKU.

Is this dataset licensed for commercial applications?

Yes. All product records in this dataset are released under the public domain / MIT license, free for personal and commercial usage without attribution.