Datasets:

datahiveai
/

amazon-us-orders

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
#: int64
user_id: string
order_id: string
asin: string
product_name: string
product_condition: string
order_date: string
quantity: int64
unit_price: double
unit_price_tax: double
currency: string
total_amount: double
website: string
shipping_city_country: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1937
to
{'user_id': Value('string'), 'order_id': Value('string'), 'asin': Value('string'), 'product_name': Value('string'), 'product_condition': Value('string'), 'order_date': Value('date32'), 'quantity': Value('int64'), 'unit_price': Value('float64'), 'unit_price_tax': Value('float64'), 'currency': Value('string'), 'total_amount': Value('float64'), 'website': Value('string'), 'shipping_city_country': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2674, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2208, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2241, in _iter_arrow
                  pa_table = cast_table_to_features(pa_table, self.features)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2192, in cast_table_to_features
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              #: int64
              user_id: string
              order_id: string
              asin: string
              product_name: string
              product_condition: string
              order_date: string
              quantity: int64
              unit_price: double
              unit_price_tax: double
              currency: string
              total_amount: double
              website: string
              shipping_city_country: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1937
              to
              {'user_id': Value('string'), 'order_id': Value('string'), 'asin': Value('string'), 'product_name': Value('string'), 'product_condition': Value('string'), 'order_date': Value('date32'), 'quantity': Value('int64'), 'unit_price': Value('float64'), 'unit_price_tax': Value('float64'), 'currency': Value('string'), 'total_amount': Value('float64'), 'website': Value('string'), 'shipping_city_country': Value('string')}
              because column names don't match

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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

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) license.

Dataset Card Contact

contact@datahive.ai

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Creative Commons Attribution 4.0 (CC BY 4.0)