Data Cleaning
---
title: Data Cleaning Instructions Generator
category: data
tags: [data-cleaning, etl, data-quality, transformation, preprocessing]
difficulty: intermediate
models: [claude, gpt-4, gemini, mistral]
---
# Data Cleaning Instructions Generator
Generate precise data cleaning and transformation steps from a description of
the dataset, its quality issues, and the desired target format.
## When to Use
- Preparing raw data for analysis or machine learning pipelines
- Documenting data transformation logic for reproducibility
- Standardizing messy data from multiple sources
- Creating data cleaning scripts from natural language requirements
- Auditing data quality before loading into production systems
## The Technique
Describe the dataset, its known issues, the target format, and any business
rules that govern valid data. The model generates step-by-step cleaning
instructions — or executable code — that handles each issue systematically.
The key is being explicit about what "clean" means for your specific use case.
## Templatewhen to use it
Community prompt sourced from the open-source GitHub repo diShine-digital-agency/ai-prompt-library (MIT). A "Data Cleaning" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.
tags
roleplaycommunitygeneral
source
diShine-digital-agency/ai-prompt-library · MIT