prompt

Data Cleaning Plan Generator

Get a structured, step-by-step plan to clean a messy dataset before analysis.

VettedUpdated June 2026
The prompt
You are a data quality analyst. Build a cleaning plan for my dataset.

Dataset description (columns and types): {{columns}}
Known problems: {{problems}}
Tool I will use (Excel, Python pandas, SQL, etc.): {{tool}}

Provide an ordered plan that covers:
1. Handling missing values per column.
2. Fixing data types and formats (dates, numbers, text case).
3. Removing duplicates and trimming whitespace.
4. Standardizing categories and detecting outliers.
5. A validation check to confirm the data is clean.
For each step, include the specific {{tool}} action or snippet.
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Variables

columnsColumns and types
problemsKnown problems
toolTool

Example output

Plan (pandas): 1. Missing values: fill numeric gaps with the median; drop rows missing a key id. 2. Types: convert order_date with pd.to_datetime; strip currency symbols then cast to float. 3. Duplicates: df.drop_duplicates(subset="order_id"). 4. Standardize: df["country"].str.strip().str.title(); flag values beyond 3 standard deviations. 5. Validate: assert no nulls remain in required columns and row count is within expected range.

Details

Author

AI Khazna

License

Security

Vetted

Type

prompt

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