dataset-comparer

Compare CSV or Excel datasets to identify row, value, and schema differences.

86|18|Updated Dec 14, 2025
One-click install
npx skills add https://github.com/dkyazzentwatwa/chatgpt-skills --skill dataset-comparer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dataset-comparer
Source: https://github.com/dkyazzentwatwa/chatgpt-skills/tree/main/dataset-comparer
Command: npx skills add https://github.com/dkyazzentwatwa/chatgpt-skills --skill dataset-comparer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, and includes scripts (resource) components.

What problem does it solve?

This Skill helps you quickly identify discrepancies between two datasets, ensuring data integrity and accuracy.

Core Features & Use Cases

  • Row Comparison: Detect added, removed, and modified rows.
  • Value Changes: Pinpoint specific cell value differences.
  • Schema Comparison: Identify added or removed columns and data type changes.
  • Use Case: Validate that a data migration was successful by comparing the source and target datasets, or verify that an ETL process correctly updated records.

Quick Start

Compare 'old_data.csv' and 'new_data.csv' using the 'id' column as the key.

Frequently Asked Questions about dataset-comparer

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

FAQPage Schema
How do I compare two CSV files to find row and value differences?

To compare two CSV files for row and value differences, you can use key-based or positional comparison. This identifies added, removed, and modified rows, pinpointing specific cell value changes for data validation.

Can I validate an ETL process by comparing source and target datasets?

Yes, you can validate ETL processes by comparing source and target datasets. It detects schema changes like added or removed columns and data type changes, ensuring data migration accuracy and integrity.

How do I generate an HTML report of data differences between two Excel files?

You can generate an HTML report of data differences between two Excel files by running a dataset comparison. It outputs detailed reports highlighting row, value, and schema discrepancies in HTML, CSV, or JSON formats.

Does dataset comparison work if the schemas of the two files do not match exactly?

Dataset comparison works when schemas do not match exactly by identifying added or removed columns and data type changes. You can also ignore specific columns or compare only selected columns during the process.

What is the best way to diff two large datasets using Python and pandas?

The best way to diff two large datasets using Python and pandas is to use a dedicated comparison script that handles key-based matching. It leverages pandas and numpy to process rows efficiently and output structured difference reports.