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CSV Transformer

Caution

Transforms, cleans, and converts data between CSV, JSON, Excel, and other tabular formats with column mapping, type casting, and validation.

By Data Skills Lab 1,650 v1.2.0 Updated 2026-03-10

Install

Claude Code

Copy the SKILL.md file to your project's .claude/skills/ directory

About This Skill

CSV Transformer handles the messy reality of data formats. It converts between CSV, JSON, TSV, Excel, and other tabular formats while cleaning, normalizing, and validating data along the way. Whether you need a simple format conversion or a complex multi-file merge with column mapping, this skill gets it done.

How It Works

  1. Input analysis — Detects file encoding, delimiter, quoting style, and column types automatically
  2. Schema mapping — Maps source columns to target schema with rename, merge, split, and type cast operations
  3. Data cleaning — Normalizes dates, trims whitespace, handles nulls, deduplicates, and fixes encoding issues
  4. Transformation — Applies filters, aggregations, pivots, and computed columns
  5. Output generation — Writes clean data in the target format with proper escaping and encoding

Best For

  • Converting between data formats for different tools and APIs
  • Cleaning vendor-provided data dumps before database import
  • Merging data exports from multiple sources into a unified format
  • Quick data exploration and profiling of unfamiliar datasets

Encoding Support

Handles UTF-8, UTF-16, Latin-1, Shift-JIS, and GB2312 encodings. Automatically detects BOM markers and line ending styles (CRLF/LF).

Use Cases

  • Convert CSV to JSON with nested object structure
  • Clean and normalize messy data: dates, phone numbers, currencies
  • Merge multiple CSV files with different column names into one schema
  • Filter and aggregate rows based on complex conditions

Pros & Cons

Pros

  • + Auto-detects encoding, delimiter, and column types
  • + Handles multi-file merges with schema reconciliation
  • + Supports complex transformations: pivot, aggregate, computed columns

Cons

  • - Very large files (>1GB) may need streaming approach
  • - Excel formatting (merged cells, formulas) may not fully preserve

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