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csv-excel-merger

Merge multiple CSV/Excel files with column mapping, deduplication, and conflict resolution.

245|39|Updated Oct 22, 2025
Search Tags:#data processing#excel#csv#spreadsheet automation#data merge#deduplication#data cleaning
One-click install
npx skills add https://github.com/OneWave-AI/claude-skills --skill csv-excel-merger
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: csv-excel-merger
Source: https://github.com/OneWave-AI/claude-skills/tree/main/csv-excel-merger
Command: npx skills add https://github.com/OneWave-AI/claude-skills --skill csv-excel-merger

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the complex task of merging multiple CSV/Excel files, intelligently handling different schemas, deduplicating data, and resolving conflicts. It saves data analysts and business users hours of manual data cleaning and consolidation.

Core Features & Use Cases

  • Intelligent Column Matching: Automatically map similar columns across different files, even with inconsistent naming conventions.
  • Data Deduplication: Identify and remove duplicate rows based on primary keys (e.g., email address), ensuring a clean dataset.
  • Conflict Resolution: Define strategies for handling conflicting data when the same record appears in multiple files (e.g., keep latest, keep longest).
  • Use Case: A marketing analyst has customer data spread across three different CSV files with inconsistent column names. This Skill merges them into a single, clean file, deduplicates entries, and resolves data conflicts, ready for analysis.

Quick Start

Example: Merge CSV files

"Merge these two CSV files: 'contacts_q1.csv' and 'contacts_q2.csv'. Use 'email' as the primary key for deduplication. Handle conflicting 'phone' numbers by keeping the most recent."

Frequently Asked Questions about csv-excel-merger

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

FAQPage Schema
How do I merge multiple CSV files with different column names?▼

Merging CSV files with inconsistent schemas uses intelligent column matching to automatically map similar columns across files, even with different naming conventions, then consolidates them into a single dataset ready for analysis.

What's the best way to deduplicate data when combining spreadsheets?▼

Data deduplication identifies and removes duplicate rows based on primary keys like email addresses or IDs, ensuring your merged dataset contains only unique records from all source files.

How do I handle conflicting data when merging Excel files from different sources?▼

Conflict resolution strategies let you define how to handle the same record appearing in multiple files—for example, keeping the most recent value or the longest entry—ensuring consistent data in your final output.

Can I merge large CSV and Excel files without performance issues?▼

Chunked processing enables merging of large files efficiently by processing data in segments, supporting outputs in CSV, Excel, JSON, Parquet, or SQL formats with a detailed merge report.

What output formats are available after merging spreadsheets?▼

Merged datasets can be exported as CSV, Excel, JSON, Parquet, or SQL, plus a detailed merge report documenting column mappings, deduplication results, and conflict resolution decisions.

Do I need to manually map columns when merging files with different structures?▼

No—intelligent column matching automatically normalizes headers and detects encoding across files, eliminating manual mapping while detecting and handling schema differences transparently.

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