data-clean

Cleans CSV, TSV, and Excel files by normalizing headers and removing duplicates.

3.7k|104|Updated Dec 11, 2020

Search Tags:#validation #excel #csv #headers #data-quality #data-cleaning #dedup

Ready to run

npx skills add https://github.com/dathere/qsv --skill data-clean-dathere

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-clean
Source: https://github.com/dathere/qsv/tree/main/.claude/skills/skills/data-clean
Command: npx skills add https://github.com/dathere/qsv --skill data-clean-dathere

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Clean the given tabular data file by fixing common data quality issues such as inconsistent headers, extraneous whitespace, missing or misformatted values, and duplicates.

Core Features & Use Cases

Normalize headers to safe, ASCII-only identifiers
Trim whitespace and standardize field lengths
Remove duplicate rows
Validate data against an optional schema during preprocessing
Use case: Clean a CSV or Excel workbook before analytics or reporting.

Quick Start

Provide the path to a tabular data file (CSV, TSV, or Excel) and run data-clean to produce a cleaned, deduplicated dataset.

Frequently Asked Questions about data-clean

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I clean inconsistent headers and remove duplicates in a CSV file?▼

To clean CSV data, use this Skill to normalize headers to safe ASCII identifiers, trim whitespace, and remove duplicate rows, producing a dataset ready for analysis. It handles inconsistent column names and duplicate records automatically during preprocessing.

What is the best way to standardize column names in Excel workbooks before reporting?▼

Standardizing Excel column names involves normalizing headers to safe, ASCII-only identifiers and trimming whitespace. This Skill processes Excel workbooks to fix header inconsistencies and standardize field lengths, yielding a cleaned dataset for downstream reporting.

Can I validate tabular data against a schema during a data-cleaning process?▼

Yes, schema validation is supported during preprocessing. This Skill validates tabular data against an optional schema while simultaneously cleaning headers, trimming whitespace, and removing duplicates, outputting a fully validated and cleaned dataset.

Does data-clean work with TSV files or only CSV and Excel formats?▼

Data-clean works with CSV, TSV, and Excel workbook formats. It cleans and normalizes tabular data across all three file types by fixing headers, normalizing row lengths, and removing duplicates to produce analysis-ready datasets.

Why does my CSV export have misaligned rows and how do I fix it?▼

Misaligned CSV rows often stem from inconsistent field lengths or extraneous whitespace. This Skill normalizes row lengths and trims whitespace during data cleaning, fixing structural misalignment and producing a properly formatted dataset.