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Data Cleaning Plan Generator
Get a structured, step-by-step plan to clean a messy dataset before analysis.
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.
Variables
columnsColumns and typesproblemsKnown problemstoolToolExample 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
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