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.

Installation

$ pip install bowline

Minimal implementation

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")

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