Population Stability Index

Calculate the PSI between the features in two dataframes, X1 and X2.

X1 and X2 should be bucketed (outputs of fitted bucketers).

\[ PSI = \sum((\%{ Good } - \%{ Bad }) imes \ln rac{\%{ Good }}{\%{ Bad }}) \]

Parameters:

Name	Type	Description	Default
X1	pd.DataFrame	bucketed features, expected	required
X2	pd.DataFrame	bucketed features, actual data	required
epsilon	float	Amount to be added to relative counts in order to avoid division by zero in the WOE calculation.	0.0001
digits		(int): number of significant decimal digits in the IV calculation	None

Examples:

from skorecard import datasets
from sklearn.model_selection import train_test_split
from skorecard.bucketers import DecisionTreeBucketer
from skorecard.reporting import psi

X, y = datasets.load_uci_credit_card(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(
    X,y,
    test_size=0.25,
    random_state=42
)

dbt = DecisionTreeBucketer()
X_train_bins = dbt.fit_transform(X_train,y_train)
X_test_bins = dbt.transform(X_test)

psi_dict = psi(X_train_bins, X_test_bins)

---

Last update: 2021-11-24