Automated Data Cleaning and Standardization for Grocery Products (Scraping Optional)
Budget: $250 – $750 CAD
Automated Data Cleaning and Standardization for Grocery Products (Scraping Optional)
Job Description:
We are looking for a freelancer to build an automated solution to clean and standardize grocery product data collected from multiple store websites.
We already have about 29,000 products from one store and expect similar data volumes from 2–3 additional stores. The goal is to normalize the data across all sources so we can compare prices and product info store-to-store.
We are open to assigning the scraping part as well if you have the required skills and tools.
Tasks Include:
Clean and normalize product names (remove brand duplication, simplify formats)
Standardize units (e.g., 500g → 0.5kg, 1L → 1000ml, etc.)
Normalize brand names, categories, and size formats
Remove or merge duplicate entries
Format prices consistently (remove currency symbols, convert to numbers)
Deliver a script or pipeline that can process this data automatically on a regular basis
(Optional) Scrape 2–3 more stores in a structured format if you can
Required Skills:
Strong experience in data cleaning and transformation
Python (Pandas) or other scripting tools for automation
Familiarity with units, weights, volumes used in grocery data
Experience with large datasets (25,000+ rows)
(Bonus) Experience in fuzzy matching, deduplication logic
(Optional) Web scraping using Playwright, Scrapy, Apify, or similar
Deliverables:
Cleaned and standardized product dataset (first store as a test)
A working script or workflow to automate future cleanups
(Optional) Structured and scraped datasets from other stores in same format
Clear documentation or explanation of how the automation works
Budget and Timeline:
We are ready to start immediately
Please include quotes for:
Data cleanup + automation only
Data cleanup + automation + scraping (per store or full project)
First working version expected in 5–7 days
To Apply:
Share past experience with similar projects
List tools you plan to use
Provide any sample output or screenshots from similar data jobs
Confirm availability and delivery timeline
Job Description:
We are looking for a freelancer to build an automated solution to clean and standardize grocery product data collected from multiple store websites.
We already have about 29,000 products from one store and expect similar data volumes from 2–3 additional stores. The goal is to normalize the data across all sources so we can compare prices and product info store-to-store.
We are open to assigning the scraping part as well if you have the required skills and tools.
Tasks Include:
Clean and normalize product names (remove brand duplication, simplify formats)
Standardize units (e.g., 500g → 0.5kg, 1L → 1000ml, etc.)
Normalize brand names, categories, and size formats
Remove or merge duplicate entries
Format prices consistently (remove currency symbols, convert to numbers)
Deliver a script or pipeline that can process this data automatically on a regular basis
(Optional) Scrape 2–3 more stores in a structured format if you can
Required Skills:
Strong experience in data cleaning and transformation
Python (Pandas) or other scripting tools for automation
Familiarity with units, weights, volumes used in grocery data
Experience with large datasets (25,000+ rows)
(Bonus) Experience in fuzzy matching, deduplication logic
(Optional) Web scraping using Playwright, Scrapy, Apify, or similar
Deliverables:
Cleaned and standardized product dataset (first store as a test)
A working script or workflow to automate future cleanups
(Optional) Structured and scraped datasets from other stores in same format
Clear documentation or explanation of how the automation works
Budget and Timeline:
We are ready to start immediately
Please include quotes for:
Data cleanup + automation only
Data cleanup + automation + scraping (per store or full project)
First working version expected in 5–7 days
To Apply:
Share past experience with similar projects
List tools you plan to use
Provide any sample output or screenshots from similar data jobs
Confirm availability and delivery timeline
Related categories:
Python
Data Entry
Excel
Web Scraping
Data Mining
Data Analysis
Automation
Pandas