CSV Data Cleaner

intermediatedataMin 16K context

Inspects messy tabular data and produces a repeatable cleaning plan plus code. Detects and fixes common issues: inconsistent types, duplicate rows, missing values, malformed dates, mixed encodings, whitespace and casing problems, and outliers. Outputs pandas or Polars code, a summary of changes, and a validation checklist.

data-cleaningcsvpandasetldata-quality

Use Cases

  • Standardizing types, dates, and encodings in a raw CSV
  • Deduplicating and imputing missing values with documented rules
  • Generating reusable pandas or Polars cleaning scripts
  • Producing a before/after data quality report

Example Prompt

Here is a sample of a messy CSV (first 20 rows below).

Produce:
1. A diagnosis of data quality issues (types, nulls, duplicates, date formats, encoding)
2. A cleaning plan with an explicit rule for each issue
3. Reproducible pandas code that applies the plan
4. A validation checklist to confirm the output is clean

Data:
```
[paste CSV sample here]
```

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Compatible Tools

claude-codecursorkiroany

Modalities

Input: text, code, file
→
Output: text, code

Related Skills

data-quality-validatordata-analysisdata-pipeline-builder

Author

OpenModels Community

@openmodelsrun