Source code for evalml.demos.churn

import os

from evalml.preprocessing import load_data


[docs]def load_churn(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, y """ currdir_path = os.path.dirname(os.path.abspath(__file__)) data_folder_path = os.path.join(currdir_path, "data") churn_data_path = os.path.join(data_folder_path, "churn.csv") X, y = load_data(path=churn_data_path, index="customerID", target="Churn", n_rows=n_rows, verbose=verbose) return X, y