Source code for evalml.demos.fraud

import os

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. Args: 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, y """ currdir_path = os.path.dirname(os.path.abspath(__file__)) data_folder_path = os.path.join(currdir_path, "data") fraud_data_path = os.path.join(data_folder_path, "fraud_transactions.csv.tar.gz") X, y = load_data(path=fraud_data_path, index="id", label="fraud", n_rows=n_rows, verbose=verbose) return X, y