Extracts query parameters from URLs within CSV files and transforms them into organized data columns.
This skill automates the tedious task of decomposing complex URLs stored in CSV files into actionable data. By identifying URL columns and parsing their query strings, it creates new columns for every unique parameter found, such as UTM tags, referral IDs, or session tokens. It is particularly useful for digital marketers and data analysts who need to organize web traffic data or prepare datasets for deeper analysis without manual string manipulation or complex spreadsheet formulas.
Key Features
01Automatic detection of 'url' or 'URL' headers in CSV files
02Comprehensive extraction of all query parameters into new columns
03Non-destructive updates that preserve all original data while adding columns
04Intelligent handling of multiple parameter values using pipe delimiters
05Batch processing capabilities for multiple CSV files in a directory
062 GitHub stars
Use Cases
01Extracting product IDs or user tokens from web tracking URLs in log exports
02Cleaning and preparing link-heavy datasets for data visualization or BI tools
03Analyzing UTM parameters for marketing campaign performance tracking
