davidev07/synthetic-ecommerce-dataset
Synthetic E-commerce Dataset - Free Sample This repository contains a free sample of the Synthetic E-commerce Dataset: 100 users, 50 products, 1,000 transactions, with full relational integrity (foreign keys, temporal consistency, validated business rules) and a fixed random seed (42) for reproducibility. License below (CC0) applies only to this free sample, not to the full-size commercial packs. Formats CSV Apache Parquet Schema users: user_id… See the full description on the dataset page: https://huggingface.co/datasets/davidev07/synthetic-ecommerce-dataset.
Synthetic E-commerce Dataset - Free Sample
This repository contains a free sample of the Synthetic E-commerce Dataset: 100 users, 50 products, 1,000 transactions, with full relational integrity (foreign keys, temporal consistency, validated business rules) and a fixed random seed (42) for reproducibility.
License below (CC0) applies only to this free sample, not to the full-size commercial packs.
Formats
- CSV
- Apache Parquet
Schema
users: userid, fullname, email, country, city, currency, signup_date
products: productid, productname, category, price
transactions: transactionid, userid, productid, purchasedate, quantity, unitprice, subtotal, discountpercentage, discountamount, totalamount, currency, country, paymentmethod, paymentstatus, orderstatus, devicetype, discountcode, shippingaddress
Quick start
import pandas as pd
users = pd.read_parquet("users.parquet")
products = pd.read_parquet("products.parquet")
transactions = pd.read_parquet("transactions.parquet")
result = transactions.merge(users, on="user_id").merge(products, on="product_id")
print(result.head())Complete Dataset
The commercial package contains:
- 1,000 transactions
- 50,000 transactions
- 500,000 transactions
Each size also includes its own users and products tables. Full-size packs are available for purchase on Gumroad: https://bergese4.gumroad.com/l/synthetice-commercedataset
All data is completely synthetic. No real customer information is included.
