I clean and standardize product catalog CSV files using a structured Python workflow designed to reduce repetitive manual work while keeping every change traceable.
This service is for catalogs of up to 500 rows and 10 columns.
You’ll receive:
A cleaned and standardized CSV
A transformation/change report
A QA and issues report
A separate review queue for ambiguous values that should not be guessed
Typical cleanup can include:
Whitespace and formatting inconsistencies
Duplicate detection
Standardization of agreed text fields
Basic validation of structured values
Identification of missing or ambiguous data
Before starting, we’ll agree on the cleanup rules that apply to your file. Values that cannot be safely corrected are flagged for review instead of being invented.
Not included: manual research to reconstruct missing product information, external system integrations, database work, or large-scale semantic rewriting.
I clean and standardize product catalog CSV files using a structured Python workflow designed to reduce repetitive manual work while keeping every change traceable.
This service is for catalogs of up to 500 rows and 10 columns.
You’ll receive:
A cleaned and standardized CSV
A transformation/change report
A QA and issues report
A separate review queue for ambiguous values that should not be guessed
Typical cleanup can include:
Whitespace and formatting inconsistencies
Duplicate detection
Standardization of agreed text fields
Basic validation of structured values
Identification of missing or ambiguous data
Before starting, we’ll agree on the cleanup rules that apply to your file. Values that cannot be safely corrected are flagged for review instead of being invented.
Not included: manual research to reconstruct missing product information, external system integrations, database work, or large-scale semantic rewriting.