Metadata-Version: 2.1
Name: bowline
Version: 0.2.1
Summary: Configurable tools to easily pre and post process your data for data-science and machine learning.
Home-page: https://github.com/mgancita/bowline
License: MIT
Keywords: preprocess,machine learning,data science
Author: Marco Gancitano
Author-email: marco.gancitano97@gmail.com
Requires-Python: >=3.7,<4.0
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Pre-processors
Requires-Dist: pandas (>=1.0.0,<2.0.0)
Requires-Dist: scikit-learn (>=0.23.2,<0.24.0)
Project-URL: Repository, https://github.com/mgancita/bowline
Description-Content-Type: text/markdown

# Bowline

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Configurable tools to easily pre and post process your data for data-science and machine learning.

## Quickstart
This will show you how to install and create a minimal implementation of `Bowline`. For more in-depth examples visit the [Official Docs](https://mgancita.github.io/bowline).

### Installation
```
$ pip install bowline
```

### Minimal implementation
```python
from bowline import StandardPreprocessor
import pandas as pd

raw_data = pd.read_csv('path/to/your/file')
preprocessor = StandardPrepreocessor(
    data = data,
    numerical_features = ["age", "capital-gain"],
    binary_features = ["sex"],
    categoric_features = ["occupation", "education"]
)
processed_data = preprocessor.process(target="sex")
```

