Configurable tools to easily pre and post process your data for data-science and machine learning.
This will show you how to install and create a minimal implementation of Bowline. For more in-depth examples visit the Official Docs.
$ pip install bowline
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")