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Clean and Standardize Messy Customer Address Data

Data Data Cleaning Intermediate 🤖 ChatGPT 👁 3 views

📝 The Prompt

I have a messy customer address dataset (~500K rows, CSV). Issues observed: inconsistent capitalization, missing zip codes, abbreviations ('St' vs 'Street'), typos in city names, duplicate entries with formatting differences. Provide a Python pandas pipeline that: 1. Standardizes capitalization (proper case for city/street, uppercase for state) 2. Expands or normalizes street suffixes consistently 3. Validates zip codes against state (flag mismatches) 4. Handles missing zip codes by lookup if city+state present 5. Deduplicates using fuzzy matching (rapidfuzz, threshold 90) 6. Outputs a 'data quality score' per row (0-100) 7. Generates a summary report of issues found Use libraries: pandas, rapidfuzz, usaddress. Memory-efficient for 500K rows.

🎯 What this prompt does

This AI prompt helps you clean and standardize messy customer address data. Designed for data cleaning workflows in the data category, it's a intermediate-level prompt you can copy directly into ChatGPT to get instant, production-ready results.

Use it when you need a intermediate prompt that produces clear, actionable output without wrestling with trial-and-error wording. Just copy, customize, and run.

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🚀 How to use this prompt

  1. Copy the prompt using the 📋 button above.
  2. Open ChatGPT (or Claude, Gemini, Perplexity, or your preferred LLM).
  3. Paste the prompt into a new chat. Add any extra context about your situation if helpful.
  4. Run the prompt and review the AI's response. Most outputs are usable immediately.
  5. Iterate if needed — if the tone, length, or structure isn't quite right, reply with "make it shorter", "use bullet points", or "make it more formal" and the AI will refine it.

💡 Tips for better results

  • Tailor the prompt to your specific context — the more detail you give, the better the output.
  • If the first output isn't quite right, ask the AI to refine, rewrite, or add more detail — iteration is key.
  • For long outputs, ask for a section at a time (e.g. 'start with the introduction only') to keep quality high.
  • Combine this with other data prompts to build an end-to-end workflow.
  • Save your favorite variations — small wording tweaks often produce noticeably different results.
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✨ What you'll get

When you run this prompt, expect ChatGPT to return:

  • A directly usable data cleaning output tailored to the details you provided
  • Clear structure (headings, bullets, or numbered sections) that you can drop into your workflow
  • Content that matches your specified tone and context
  • Results in under 30 seconds — no manual drafting required

Need a different angle? Just ask follow-up questions. The AI will adjust without you starting over.

🔄 3 variations to try

1

Make it more formal

Add "Use a formal, professional tone suitable for enterprise clients" at the start of the prompt.

2

Ask for multiple options

Append "Give me 5 alternative versions, each with a different angle or approach." after the main instruction.

3

Request structured output

Add "Return the response as a markdown table (or bullet list, or JSON)" so you can paste the result directly into your docs or code.

🏷 Tags

🔎 Find more prompts like this

Browse 101 more data prompts or search the full library.

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