---
pretty_name: Amazon US Orders
license: cc-by-4.0
language:
  - en
task_categories:
  - other
size_categories:
  - 1K<n<10K
tags:
  - tabular
  - csv
  - ecommerce
  - orders
  - amazon
  - transactions
dataset_info:
  features:
    - name: user_id
      dtype: string
    - name: order_id
      dtype: string
    - name: asin
      dtype: string
    - name: product_name
      dtype: string
    - name: product_condition
      dtype: string
    - name: order_date
      dtype: date32
    - name: quantity
      dtype: int64
    - name: unit_price
      dtype: float64
    - name: unit_price_tax
      dtype: float64
    - name: currency
      dtype: string
    - name: total_amount
      dtype: float64
    - name: website
      dtype: string
    - name: shipping_city_country
      dtype: string
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/orders.csv
---

This is a sample dataset. To access the full version or request any custom dataset tailored to your needs, contact DataHive at contact@datahive.ai.

# Amazon US Orders

## Dataset Summary

A structured e-commerce order dataset built from real Amazon purchase histories voluntarily shared by users on the platform. Each record represents a single order line item with full pricing breakdown (unit price, tax, discounts, shipping), fulfilment status, and shipping location.

The sample includes:

- **10 unique users**
- **1k order items**
- Marketplace: Amazon.com


### Dataset Description

- **Access:** Free sample dataset
- **Curated by:** https://datahive.ai
- **Language(s):** English
- **License:** Creative Commons Attribution 4.0 (CC BY 4.0)

## Use Cases

- **E-commerce analytics**: basket analysis, spending patterns, seasonal trends
- **Price research**: cross-marketplace price comparison, tax structure analysis
- **Demand forecasting**: order frequency and product category modelling

## Data Collection

Order data was exported directly from personal Amazon accounts by participating users who consented to share their purchase history.

## Anonymization

- **User & order IDs** — original identifiers replaced with deterministic SHA-256 pseudonyms (truncated to 8 hex characters), preserving cross-record linkability
- **Addresses** — reduced to city and country only; street names, house numbers, and postal codes are removed
- **Dates** — normalized to `YYYY-MM-DD`; time components stripped

## Dataset Structure

### Data Fields

| Column | Type | Description |
|---|---|---|
| `user_id` | string | User identifier |
| `order_id` | string | Order identifier |
| `asin` | string | Amazon Standard Identification Number |
| `product_name` | string | Full product title |
| `product_condition` | string | Item condition (e.g. New) |
| `order_date` | date | Date the order was placed |
| `quantity` | int | Number of units ordered |
| `unit_price` | float | Price per unit excluding tax (USD) |
| `unit_price_tax` | float | Tax per unit (USD) |
| `currency` | string | Currency code (USD) |
| `total_amount` | float | Total charged including tax (USD) |
| `website` | string | Amazon marketplace (Amazon.com) |
| `shipping_city_country` | string | Shipping destination city and country |

### Data Splits

Single split containing all records. No train/test separation — this is a raw data export, not a benchmark.

## Licensing Information

This dataset is released under the [Creative Commons Attribution 4.0 International (CC-BY-4.0)](https://creativecommons.org/licenses/by/4.0/) license.

## Dataset Card Contact

contact@datahive.ai