def test_OneHotEncoder(self):
df = get_baseball_df()
p = Pipeline([('e', OneHotEncoder(columns=['League']))])
df = p.transform(df)
info(df)
def test_ScopedTransformer(self):
df = get_baseball_df()
p = Pipeline([('e',
ScopedTransformer(transformer=MinMaxScaler(),
columns=['RS']))])
df = p.fit_transform(df, [])
info(df)
def transform(self, X: pd.DataFrame):
info(X)
return X
from sklearn.linear_model import Lasso from litkit.data import get_baseball_df from litkit.inspect import info m = Lasso() df = get_baseball_df() y = df['RS'] X = df[['RA', 'W', 'OBP', 'SLG']] m.fit(X, y) info(m)
def test_info(self):
df = get_baseball_df()
info(df)
info(df.values)