Dataset

italian-food-supermarkets
Open Data Contract Standard v3.1.0
web-scraped groceries-and-food

Fundamentals

Basic information about the data contract

Name
Variations of Food Prices in Italian Supermarkets
Version
1.0
Tenant
Sasso et al (2025) https://doi.org/10.5281/zenodo.14927602
Purpose
This web scraped dataset includes retail prices for meat, fruit, and vegetable products collected over a period spanning from December 2020 to March 2023 (2 years and 4.5 months or 862 days). Dataset facilitates comprehensive analyses, enabling exploration of regional price variations, comparisons across product categories, and time-series investigations into price dynamics within the Italian retail food market.
Usage
Open dataset, shared under "Creative Commons Attribution 4.0 International" licence on Zenodo.

Links:
How to cite
APA style:
Sasso, D., Bacco, L., Palumbo, L., Marcucci, J., Salvini, N., Laureti, T., & Vollero, L. (2025). Variations of Food Prices in Italian Supermarkets (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14927602

Chicago style
Sasso, Daniele, Luca Bacco, Luigi Palumbo, Juri Marcucci, Niccolo Salvini, Tiziana Laureti, and Luca Vollero. "Variations of Food Prices in Italian Supermarkets". Zenodo, February 25, 2025. https://doi.org/10.5281/zenodo.14927602.

Bibtex citation
Click here for raw form

Entity Relationship Diagram

Visual representation of data model relationships

                    erDiagram
	"**Dataset**" {
	date object
	price number
	product_id integer
	store_id integer
	region object
	product object
	COICOP5 object
	COICOP4 object
}

Schema

The data schema and structure

Dataset None
File Information:
- Format: CSV (.csv), UTF-8 encoded, comma-separated.
- Each row corresponds to one product observation at a specific store on a specific date.
- No missing values are present in the cleaned version.
Property Business Name Type Required Description
date
 Scrape date
object
 No Date of price collection. Dataset total coverage is 2 years, 4.5 months (2020-12-03 to 2023-04-14) Dataset based on 841 distinct web scrapes, with an average 236 unique products captured each time per scraped store. The amount of web offers started to decline by mid-2022.
Example: '2020-12-03'
price
 Product price
number
 No Retail price in euros (EUR), using a decimal point (.).
Example: '1.99'
product_id
 Product ID
integer
 No A unique identifier assigned to each product. There are 2,361 unique products in the sample spread relatively equally across the COICOP categories.
Example: '2'
store_id
 Store ID
integer
 No Anonymized unique identifier of the store where the price was recorded. There are 20 distinct stores covered by the dataset.
Example: '2'
region
 Region
object
 No Italian region where the store is located. There are 7 distinct regions of Italy covered by the dataset.
Example: 'Calabria'
product
 Product name
object
 No Full commercial name of the product, including quantity or weight.
Example: 'arance navelina italia calibro 1.5 kg'
COICOP5
 COICOP5 category
object
 No Product classification at the 5-digit level based on the COICOP nomenclature. There are 24 COICOP5 categories covered by the dataset. Classification was assigned via manual annotation and rule-based categorization using domain-specific keywords.
Example: 'Oranges'
COICOP4
 COICOP4 category
object
 No Higher-level COICOP category. Classification assigned via manual annotation and rule-based categorization using domain-specific keywords (tied to COICOP5).
Example: 'Fruit'

Team

Team members and their roles

Sasso, Daniele, Luca Bacco, Luigi Palumbo, Juri Marcucci, Niccolo Salvini, Tiziana Laureti, and Luca Vollero
https://doi.org/10.5281/zenodo.14927602
Username Role Date In Date Out Comment
Created at 24 Feb 2026 05:02:51 UTC with Data Contract CLI v0.11.5

Data Contract YAML

version: '1.0'
kind: DataContract
apiVersion: v3.1.0
id: italian-food-supermarkets
name: Variations of Food Prices in Italian Supermarkets
tenant: Sasso et al (2025) https://doi.org/10.5281/zenodo.14927602
tags:
- web-scraped
- groceries-and-food
status: 'Documentation
  level: 3'
description:
  usage: "Open dataset, shared under \"Creative Commons Attribution 4.0 International\"\
    \ licence on Zenodo.\n\n

\nLinks:
\n\n"
  purpose: 'This web scraped dataset includes retail prices for meat, fruit, and vegetable
    products collected over a period spanning from December 2020 to March 2023 (2
    years and 4.5 months or 862 days).


    Dataset facilitates comprehensive analyses, enabling exploration of regional price
    variations, comparisons across product categories, and time-series investigations
    into price dynamics within the Italian retail food market.

    '
  limitations: 'APA style: 
Sasso, D., Bacco, L., Palumbo, L., Marcucci,
    J., Salvini, N., Laureti, T., & Vollero, L. (2025). Variations of Food Prices
    in Italian Supermarkets (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14927602


    


    Chicago style
Sasso, Daniele, Luca Bacco, Luigi Palumbo, Juri Marcucci,
    Niccolo Salvini, Tiziana Laureti, and Luca Vollero. "Variations of Food Prices
    in Italian Supermarkets". Zenodo, February 25, 2025. https://doi.org/10.5281/zenodo.14927602.


    


    Bibtex citation
Click
    here for raw form

    '
domain: Consumer Price Statistics
schema:
- name: Dataset
  description: "File Information:
\n    - Format: CSV (.csv), UTF-8 encoded, comma-separated.
\n\
    \    - Each row corresponds to one product observation at a specific store on\
    \ a specific date.
\n    - No missing values are present in the cleaned version.\n"
  businessName: ''
  properties:
  - name: date
    description: 'Date of price collection.

      Dataset total coverage is 2 years, 4.5 months (2020-12-03 to 2023-04-14)

      Dataset based on 841 distinct web scrapes, with an average 236 unique products
      captured each time per scraped store. The amount of web offers started to decline
      by mid-2022. 
Example: ''2020-12-03''

      '
    businessName: Scrape date
    logicalType: object
    examples:
    - '2020-12-03'
  - name: price
    description: 'Retail price in euros (EUR), using a decimal point (.). 
Example:
      ''1.99''

      '
    businessName: Product price
    logicalType: number
    examples:
    - '1.99'
  - name: product_id
    description: 'A unique identifier assigned to each product.

      There are 2,361 unique products in the sample spread relatively equally across
      the COICOP categories. 
Example: ''2''

      '
    businessName: Product ID
    logicalType: integer
    examples:
    - '2'
  - name: store_id
    description: 'Anonymized unique identifier of the store where the price was recorded.

      There are 20 distinct stores covered by the dataset. 
Example: ''2''

      '
    businessName: Store ID
    logicalType: integer
    examples:
    - '2'
  - name: region
    description: 'Italian region where the store is located.

      There are 7 distinct regions of Italy covered by the dataset. 
Example: ''Calabria''

      '
    businessName: Region
    logicalType: object
    examples:
    - Calabria
  - name: product
    description: 'Full commercial name of the product, including quantity or weight.
      
Example: ''arance navelina italia calibro 1.5 kg'''
    businessName: Product name
    logicalType: object
    examples:
    - arance navelina italia calibro 1.5 kg
  - name: COICOP5
    description: 'Product classification at the 5-digit level based on the COICOP
      nomenclature.

      There are 24 COICOP5 categories covered by the dataset. Classification was assigned
      via manual annotation and rule-based categorization using domain-specific keywords.
      
Example: ''Oranges''

      '
    businessName: COICOP5 category
    logicalType: object
    examples:
    - Oranges
  - name: COICOP4
    description: 'Higher-level COICOP category. Classification assigned via manual
      annotation and rule-based categorization using domain-specific keywords (tied
      to COICOP5). 
Example: ''Fruit''

      '
    businessName: COICOP4 category
    logicalType: object
    examples:
    - Fruit
team:
  name: Sasso, Daniele, Luca Bacco, Luigi Palumbo, Juri Marcucci, Niccolo Salvini,
    Tiziana Laureti, and Luca Vollero
  description: https://doi.org/10.5281/zenodo.14927602