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Clean and prepare messy data

Process tabular data without affecting the original.

Difficulty Easy
Time horizon 5m

Drag in or mention a messy CSV or spreadsheet, describe the problems you see, and ask ChatGPT to write a cleaned copy while keeping the original file unchanged.

Best for

  • CSV or spreadsheet exports with mixed dates, currencies, duplicates, summary rows, or missing values.
  • Teams who work with data from multiple sources.

Contents

    ← All use cases

    Clean and prepare messy data

    Process tabular data without affecting the original.

    Drag in or mention a messy CSV or spreadsheet, describe the problems you see, and ask ChatGPT to write a cleaned copy while keeping the original file unchanged.

    Easy
    5m

    Drag in or mention a messy CSV or spreadsheet, describe the problems you see, and ask ChatGPT to write a cleaned copy while keeping the original file unchanged.

    Easy
    5m

    Related links

    Analyze data with ChatGPT File inputs Agent skills

    Best for

    • CSV or spreadsheet exports with mixed dates, currencies, duplicates, summary rows, or missing values.
    • Teams who work with data from multiple sources.

    Skills & Plugins

    • Spreadsheet
      Inspect tabular files, clean columns, and produce reviewable outputs.
    Skill Why use it
    Spreadsheet Inspect tabular files, clean columns, and produce reviewable outputs.

    Starter prompt

    Clean @marketplace-risk-rollout-export.csv. What's wrong: - dates are mixed between MM/DD/YYYY and YYYY-MM-DD - currency values include $, commas, and blank cells - a few duplicate customer rows came from repeated exports - region and category names use several aliases - there are pasted summary rows mixed into the data What I want: - write a cleaned CSV - keep the original file unchanged - use one date format - keep blank currency cells blank - preserve source row IDs when possible - add a short data-quality note with rows you changed, removed, or could not clean confidently
    Clean @marketplace-risk-rollout-export.csv. What's wrong: - dates are mixed between MM/DD/YYYY and YYYY-MM-DD - currency values include $, commas, and blank cells - a few duplicate customer rows came from repeated exports - region and category names use several aliases - there are pasted summary rows mixed into the data What I want: - write a cleaned CSV - keep the original file unchanged - use one date format - keep blank currency cells blank - preserve source row IDs when possible - add a short data-quality note with rows you changed, removed, or could not clean confidently

    Introduction

    ChatGPT is great at cleaning systematically tabular data. When a CSV or spreadsheet has mixed dates, duplicate rows, currency strings, blank cells, aliases, or pasted summary rows, ask ChatGPT to clean a copy and leave the original file unchanged.

    How to use

    1. Drag the file into ChatGPT or mention it in your prompt, such as @customer-export.csv.
    2. Describe the problems you already see.
    3. Tell ChatGPT what the cleaned version should be: CSV, spreadsheet tab, or upload-ready file.
    4. Review the cleaned copy before using it.

    Use the starter prompt on this page for the first cleaning pass. Replace the file name and bullets with your own. The useful details are the problems you already see and the file you need next: a cleaned CSV, a clean spreadsheet tab, or an upload-ready file. After ChatGPT writes the clean copy, open the cleaned file and the data-quality note from the task before using the data downstream.

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