Analyze, clean, and validate tabular datasets with quality reports.
npx skills add https://github.com/brook-miller/claude-skill-data-cleaner --skill data-cleaner
Please help me install this Agent Skill. Skill: Data Cleaner Source: https://github.com/brook-miller/claude-skill-data-cleaner/tree/main/. Command: npx skills add https://github.com/brook-miller/claude-skill-data-cleaner --skill data-cleaner
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.
Use the Data Cleaner skill to analyze and clean a dataset. Steps:
High-intent search queries and answers about installing and using this skill.
Data Cleaner automatically detects data types—numeric, categorical, ordinal, text, datetime, boolean—across all columns in CSV, Excel, JSON, and JSONL files. Run the type detection script to classify each column and guide your cleaning strategy.
Generate value mappings with Data Cleaner to identify inconsistencies, then apply standardization rules automatically. The skill produces a cleaned dataset and validation report, reducing manual correction work across large tables.
Data Cleaner analyzes completeness and quality metrics across all columns, generating a quality report that highlights missing values, inconsistencies, and data issues. Use this report to prioritize which columns need cleaning first.
Yes. Data Cleaner integrates with pandas and numpy—the core dependencies—and works with tabular data in CSV, Excel, JSON, and JSONL formats. Reproducible execution runs via uv-managed Python scripts.
Column analysis lists all columns with basic statistics and sample values to understand dataset structure. This step precedes type detection and helps identify which columns need attention before cleaning.
Yes. Data Cleaner includes validation reporting to confirm that cleaning operations succeeded and data quality improved. Run the validation script after applying cleaning rules to verify the output dataset.
Jignesh-PonamwarAnalyze tabular datasets with pandas to uncover insights and data-quality issues.
bendruckerProcess JSON data with jq filters for parsing, filtering, and transforming.
jixu-aiRead, write, edit, and analyze Excel files using pandas.
Adelie-SquadClean and transform raw datasets into analysis-ready tables with pandas pipelines.
