Results for “data-cleaning”

Cleans credit risk data and screens variables for pre-loan modeling through an 11-step pipeline covering missing rate calculation, IV/PSI filtering, null importance denoising, and correlation removal.

Cleans datasets, detects anomalies, generates reports, and creates visualizations using pandas, scikit-learn, and plotting libraries to turn raw data into client-ready deliverables.

Analyzes uploaded data files with full Python access, producing cleaned datasets, statistical reports, charts, and dashboards via the CellCog coding agent.