Data Cleaner

What problem does it solve?

This Skill helps users analyze, clean, and prepare datasets by detecting data types, identifying data quality issues, and applying corrections automatically, reducing manual data wrangling and speeding up data work.

Core Features & Use Cases

• Column Analysis: List all columns with basic statistics and sample values to understand dataset structure.
• Type Detection: Automatically detect data types (numeric, categorical, ordinal, text, datetime, boolean) to guide cleaning.
• Data Quality Reports: Generate completeness and quality insights to prioritize fixes.
• Value Mapping & Cleaning: Auto-generate standardization mappings and apply cleaning rules to correct inconsistencies.
• Use Case: You have a messy customer dataset with inconsistent category labels and missing values. This skill analyzes, cleans, and validates data, returning a clean dataset and a quality report.

Quick Start

Use the Data Cleaner skill to analyze and clean a dataset. Steps:

• Run data exploration with the Analyze Columns and Detect Types scripts
• Generate a quality report with data_quality_report.py
• Apply value mappings and cleaning operations with clean_values.py
• Validate the results with validation_report.py