Source code for evalml.demos.fraud

import evalml
from evalml.preprocessing import load_data


[docs]def load_fraud(n_rows=None, verbose=True): """Load credit card fraud dataset. The fraud dataset can be used for binary classification problems. Arguments: n_rows (int): Number of rows from the dataset to return verbose (bool): Whether to print information about features and labels Returns: (pd.Dataframe, pd.Series): X and y """ fraud_data_path = ( "https://api.featurelabs.com/datasets/fraud_transactions.csv.gz?library=evalml&version=" + evalml.__version__ ) X, y = load_data( path=fraud_data_path, index="id", target="fraud", compression="gzip", n_rows=n_rows, verbose=verbose, ) X.ww.set_types(logical_types={"provider": "Categorical", "region": "Categorical"}) return X, y