csv10.9 KB
E-commerce Products (CSV, 200 rows)
A realistic e-commerce product catalogue (200 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
Preview — first 50 linescsv
product_id,sku,name,category,price,stock,rating
1,SKU-00001,Wireless Coffee Beans,Home & Kitchen,222.23,216,4.4
2,SKU-00002,Deluxe Notebook,Books,487.92,47,4.5
3,SKU-00003,Classic Coffee Beans,Clothing,68.41,419,3.7
4,SKU-00004,Ergonomic Blender,Sports,323.7,463,4.6
5,SKU-00005,Stainless Yoga Mat,Toys,117.47,46,3.1
6,SKU-00006,Stainless Desk Lamp,Beauty,317.66,413,4.5
7,SKU-00007,Classic T-Shirt,Grocery,485.49,222,4.6
8,SKU-00008,Deluxe Coffee Beans,Electronics,236.02,97,3.1
9,SKU-00009,Stainless Blender,Home & Kitchen,343.1,461,4.9
10,SKU-00010,Classic Yoga Mat,Books,188.37,162,3.9
11,SKU-00011,Classic Blender,Clothing,69.3,343,3.5
12,SKU-00012,Ergonomic Building Blocks,Sports,221.38,334,4.7
13,SKU-00013,Portable Coffee Beans,Toys,159.61,383,4.6
14,SKU-00014,Deluxe Desk Lamp,Beauty,147.71,193,4.4
15,SKU-00015,Portable Blender,Grocery,103.94,402,4.6
16,SKU-00016,Wireless Coffee Beans,Electronics,354.05,332,4.6
17,SKU-00017,Stainless Yoga Mat,Home & Kitchen,286.52,18,3.2
18,SKU-00018,Organic Yoga Mat,Books,238.18,334,4.1
19,SKU-00019,Wireless Coffee Beans,Clothing,319.18,282,4.1
20,SKU-00020,Stainless Coffee Beans,Sports,20.24,151,3.9
21,SKU-00021,Eco Notebook,Toys,207.21,496,3.5
22,SKU-00022,Deluxe Desk Lamp,Beauty,144.28,29,3.6
23,SKU-00023,Ergonomic Face Cream,Grocery,280.72,252,4.3
24,SKU-00024,Classic Yoga Mat,Electronics,407.93,203,3.3
25,SKU-00025,Compact Headphones,Home & Kitchen,49.56,385,3.9
26,SKU-00026,Classic Coffee Beans,Books,253.01,80,3.3
27,SKU-00027,Ergonomic Face Cream,Clothing,225.84,83,3.6
28,SKU-00028,Compact Face Cream,Sports,184.09,315,3.2
29,SKU-00029,Compact Blender,Toys,481.13,183,4.4
30,SKU-00030,Eco Yoga Mat,Beauty,484.73,132,4.6
31,SKU-00031,Premium Coffee Beans,Grocery,227.42,368,3.2
32,SKU-00032,Premium Yoga Mat,Electronics,230.6,451,3.4
33,SKU-00033,Classic T-Shirt,Home & Kitchen,291.7,273,4.7
34,SKU-00034,Organic Headphones,Books,361.12,379,3.9
35,SKU-00035,Compact Face Cream,Clothing,294.12,47,3.2
36,SKU-00036,Portable Coffee Beans,Sports,25.59,207,4.0
37,SKU-00037,Organic T-Shirt,Toys,76.53,338,4.2
38,SKU-00038,Organic Coffee Beans,Beauty,462.92,85,4.2
39,SKU-00039,Ergonomic T-Shirt,Grocery,297.49,147,4.9
40,SKU-00040,Wireless Yoga Mat,Electronics,392.44,241,3.2
41,SKU-00041,Premium Yoga Mat,Home & Kitchen,247.89,220,4.1
42,SKU-00042,Eco Building Blocks,Books,137.14,236,3.7
43,SKU-00043,Stainless Building Blocks,Clothing,222.25,142,4.7
44,SKU-00044,Wireless Headphones,Sports,74.41,448,4.1
45,SKU-00045,Compact Blender,Toys,337.75,59,4.3
46,SKU-00046,Premium Coffee Beans,Beauty,385.47,363,3.2
47,SKU-00047,Portable Water Bottle,Grocery,118.95,118,4.1
48,SKU-00048,Wireless Building Blocks,Electronics,415.74,185,4.6
49,SKU-00049,Eco T-Shirt,Home & Kitchen,476.68,317,4.0… 202 lines total — download for the full file.
Specifications
- Rows
- 200
- Columns
- 7
- Schema
- product_id, sku, name, category, price, stock, rating
- Domain
- e-commerce
What is a .csv file?
CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.
How to use this file
Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.
Related files
- csvE-commerce Customers (CSV, 500 rows)A realistic e-commerce customer directory (500 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- csvE-commerce Orders (CSV, 2000 rows)A realistic e-commerce order lines (customer_id → customers, product_id → products) (2000 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- jsonE-commerce Customers (JSON, 500 records)The e-commerce customers table as a JSON array — the format twin of the CSV, for import and conversion testing.
- sqlE-commerce Database Schema (SQL)A relational SQL schema (products, customers, orders with primary and foreign keys) plus sample INSERTs — the DDL twin of the e-commerce dataset, for testing schema import and migrations.
- jsonE-commerce Orders (JSON, 2000 records)The e-commerce orders table as a JSON array — the format twin of the CSV, for import and conversion testing.
- parquetE-commerce Orders (Parquet, 2000 rows)The e-commerce orders table as Apache Parquet — the columnar twin, for testing analytics engines (pandas, DuckDB, Spark).
Generated by generation/data_realworld.py. Free for any use, no attribution required — license.