This library is a quick way to do exploratory statistical analysis to evaluate variable relationship and importance

From your notebook environment:

!pip install tuaneda

Import the library

from tuaneda import tuanfuncs

Show available functions in the library:

help(tuanfuncs)

Example on information value:

from sklearn.datasets import load_iris
iris = load_iris()
iris_data = pd.DataFrame(data= np.c_[iris['data'], iris['target']],
                     columns= iris['feature_names'] + ['target'])

X = iris_data.iloc[:,:5]
y = iris_data['target']

obj = tuanfuncs.Eda(X,y)

woe_dict, iv_dict = obj.woe_iv_continuous()
iv_graph = obj.barchart_dict(iv_dict)