Metadata-Version: 2.4
Name: smart_preprocess-asif
Version: 0.1.0
Summary: One-line smart preprocessing for ML: impute, encode, scale, and (optionally) clip outliers.
Author-email: Asif Pinjari <ap3929@nau.edu>
License: MIT
Project-URL: Homepage, https://github.com/asifpinjari/smart-preprocess
Project-URL: Issues, https://github.com/asifpinjari/smart-preprocess/issues
Keywords: machine-learning,preprocessing,data-cleaning,feature-engineering
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=2.0
Requires-Dist: numpy>=1.24
Requires-Dist: scikit-learn>=1.3
Dynamic: license-file

# smart_preprocess

One-line smart preprocessing for ML: impute, encode, scale, and (optionally) clip outliers.

## Install
```bash
pip install smart_preprocess

import pandas as pd
from smart_preprocess import SmartCleaner

df = pd.DataFrame({
  "age": [20, 21, None, 23, 1000],
  "city": ["A", "B", "A", None, "C"]
})

cleaner = SmartCleaner(outlier_clip=True)
X = cleaner.fit_transform(df)
print(cleaner.report_)


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---

### 🪪 3️⃣ File: `LICENSE`

Paste the MIT license text:
```text
MIT License

Copyright (c) 2025 Asif

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

[...full MIT text...]
__pycache__/
*.py[cod]
.venv/
build/
dist/
*.egg-info/
.vscode/
