Datasets:

crawlfeeds
/

tesco-grocery-uk

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
name: string
sku: int64
tpnc: int64
tpnb: int64
gtin: int64
gtin13: int64
price: string
unit_price: string
unit_of_measure: string
currency: string
availability: string
is_for_sale: bool
base_product_id: string
shelfLife: string
foodIcons: string
restrictions: string
manufacturer: string
manufacturer_address: string
images: string
description: string
product_url: string
brand: string
avg_rating: string
reviews_count: string
uniq_id: string
pack_size: string
alcohol_units: string
abv: string
category_1: string
category_2: string
category_3: string
breadcrumbs: string
ingredients: string
nutrition: string
specifications: string
features: string
warnings: string
storage: string
other_information: string
allergens: string
preparation_and_usage: string
brand_marketing: string
product_marketing: string
origin_information: string
legal_labelling: string
nutritional_claims: string
directions: string
preparation_guidelines: string
cooking_instructions: string
clothing_info: string
product_dimensions: string
recycling_info: string
manufacturer_marketing: string
other_nutrition_information: string
pack_size_info: string
is_new: bool
product_type: string
super_department: string
department: string
aisle: string
distributor_address: string
importer_address: string
multi_pack_details: string
additives: string
box_contents: string
components: string
dosage: string
drained_weight: string
energy_efficiency: string
freezing_instructions: string
guideline_daily_amount: string
hazard_info: string
health_claims: string
healthmark: string
lower_age_limit: string
nappies: string
net_contents: string
number_of_uses: string
safety_warning: string
upper_age_limit: string
_version: int64
_imported_at: string
product_id: null
product_name: null
category: null
subcategory: null
original_price: null
unit: null
price_per_unit: null
rating: null
num_reviews: null
image_url: null
scraped_at: null
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 10418
to
{'product_id': Value('string'), 'product_name': Value('string'), 'category': Value('string'), 'subcategory': Value('string'), 'brand': Value('string'), 'price': Value('float64'), 'original_price': Value('float64'), 'currency': Value('string'), 'unit': Value('string'), 'price_per_unit': Value('string'), 'availability': Value('string'), 'rating': Value('float64'), 'num_reviews': Value('int64'), 'product_url': Value('string'), 'image_url': Value('string'), 'scraped_at': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                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 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2388, in _iter_arrow
                  pa_table = cast_table_to_features(pa_table, self.features)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2271, in cast_table_to_features
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              name: string
              sku: int64
              tpnc: int64
              tpnb: int64
              gtin: int64
              gtin13: int64
              price: string
              unit_price: string
              unit_of_measure: string
              currency: string
              availability: string
              is_for_sale: bool
              base_product_id: string
              shelfLife: string
              foodIcons: string
              restrictions: string
              manufacturer: string
              manufacturer_address: string
              images: string
              description: string
              product_url: string
              brand: string
              avg_rating: string
              reviews_count: string
              uniq_id: string
              pack_size: string
              alcohol_units: string
              abv: string
              category_1: string
              category_2: string
              category_3: string
              breadcrumbs: string
              ingredients: string
              nutrition: string
              specifications: string
              features: string
              warnings: string
              storage: string
              other_information: string
              allergens: string
              preparation_and_usage: string
              brand_marketing: string
              product_marketing: string
              origin_information: string
              legal_labelling: string
              nutritional_claims: string
              directions: string
              preparation_guidelines: string
              cooking_instructions: string
              clothing_info: string
              product_dimensions: string
              recycling_info: string
              manufacturer_marketing: string
              other_nutrition_information: string
              pack_size_info: string
              is_new: bool
              product_type: string
              super_department: string
              department: string
              aisle: string
              distributor_address: string
              importer_address: string
              multi_pack_details: string
              additives: string
              box_contents: string
              components: string
              dosage: string
              drained_weight: string
              energy_efficiency: string
              freezing_instructions: string
              guideline_daily_amount: string
              hazard_info: string
              health_claims: string
              healthmark: string
              lower_age_limit: string
              nappies: string
              net_contents: string
              number_of_uses: string
              safety_warning: string
              upper_age_limit: string
              _version: int64
              _imported_at: string
              product_id: null
              product_name: null
              category: null
              subcategory: null
              original_price: null
              unit: null
              price_per_unit: null
              rating: null
              num_reviews: null
              image_url: null
              scraped_at: null
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 10418
              to
              {'product_id': Value('string'), 'product_name': Value('string'), 'category': Value('string'), 'subcategory': Value('string'), 'brand': Value('string'), 'price': Value('float64'), 'original_price': Value('float64'), 'currency': Value('string'), 'unit': Value('string'), 'price_per_unit': Value('string'), 'availability': Value('string'), 'rating': Value('float64'), 'num_reviews': Value('int64'), 'product_url': Value('string'), 'image_url': Value('string'), 'scraped_at': Value('string')}
              because column names don't match

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🛒 Tesco Grocery UK — Product Dataset

Structured grocery product data scraped from Tesco.com (UK) Provided by CrawlFeeds — Data-as-a-Service platform for web-scraped datasets.

📌 Dataset Overview

This dataset contains 1,000 sample product records scraped from Tesco.com — the UK's largest supermarket chain. It covers product listings across major grocery categories including food, beverages, household, health & beauty, and more.

The full dataset available at crawlfeeds.com contains 400,000+ products refreshed On Demand.

📊 Dataset Details

Attribute	Value
Source	tesco.com
Region	United Kingdom (UK)
Currency	GBP (£)
Sample Size	1,000 products
Full Dataset	400,000+ products
Refresh Frequency	On Demand
Format	CSV
License	CC BY-NC 4.0

📁 Fields / Schema

Column	Type	Description
`product_id`	string	Unique Tesco product identifier
`product_name`	string	Full product name as listed on Tesco.com
`category`	string	Top-level product category (e.g. Food, Drinks)
`subcategory`	string	Sub-level category (e.g. Dairy, Snacks)
`brand`	string	Product brand name
`price`	float	Current selling price in GBP
`original_price`	float	Original price before discount if on sale
`currency`	string	Currency code — GBP
`unit`	string	Unit of measure — per kg, per litre, each
`price_per_unit`	string	Comparable price per unit
`availability`	string	In stock / Out of stock / Limited
`rating`	float	Average customer rating out of 5.0
`num_reviews`	int	Total number of customer reviews
`product_url`	string	Direct URL to product page on Tesco.com
`image_url`	string	Product image URL
`scraped_at`	string	Timestamp when record was scraped

🚀 Use Cases

Price Intelligence — Track Tesco pricing trends over time
Grocery Market Research — Analyse product distribution across categories
Competitor Analysis — Compare pricing against Sainsbury's, ASDA, Waitrose
ML & NLP Training — Train product classification and NER models
RAG Pipelines — Power grocery AI assistants with structured product data
Category Analysis — Understand product range and availability patterns
Retail Analytics — Build dashboards for UK grocery market insights

💻 Usage

from datasets import load_dataset

# Load the dataset
ds = load_dataset("crawlfeeds/tesco-grocery-uk")

# Preview first 5 rows
print(ds['train'][:5])

import pandas as pd

# Load as pandas DataFrame
df = pd.read_csv("tesco_grocery_sample.csv")

# Filter by category
dairy = df[df['category'] == 'Dairy']

# Find discounted products
deals = df[df['price'] < df['original_price']]
print(f"Products on sale: {len(deals)}")

📦 Full Dataset

This is a sample dataset (1,000 rows). The full dataset includes:

Feature	Sample	Full Dataset
Products	1,000	100,000+
Categories	All major	All categories
Refresh	Static	On Demand
Formats	CSV	CSV
Price history	❌	✅
Images	URLs only	URLs + bulk download

👉 Get full access at crawlfeeds.com/datasets/tesco

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Amazon Top Sellers	BSR rankings across all categories	Coming soon
Amazon Products	30M+ product listings	Coming soon
Booking.com Hotels	Hotel listings, pricing, reviews	Coming soon
Blinkit Grocery IN	Indian quick commerce data	Coming soon

⚖️ License & Terms

License: Creative Commons CC BY-NC 4.0
This dataset is for non-commercial research and evaluation only
For commercial use, contact us at contact@crawlfeeds.com
Data is scraped from publicly available pages on Tesco.com
Buyers are responsible for ensuring compliance with applicable laws

📬 Contact & Full Data Access


🌐 Website	crawlfeeds.com
📧 Email	contact@crawlfeeds.com
🤗 HuggingFace	huggingface.co/crawlfeeds
💼 LinkedIn	CrawlFeeds

Dataset maintained by CrawlFeeds — structured web data for research, analytics, and AI.

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