Project-AutoML/automl/data.py [47:73]:
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        train_x, train_y, test_x, test_y = load_split_csv_data(
            data_path, label_column, test_size=test_size, random_state=random_state
        )

    else:
        raise Exception(PATH_ERROR_MESSAGE)

    return train_x, train_y, test_x, test_y


def load_split_csv_data(data_path, label_column, test_size=0.25, random_state=1):

    data = pd.read_csv(data_path)
    train, test = train_test_split(data, test_size=test_size, random_state=random_state)
    train_x = train.drop([label_column], axis=1)
    test_x = test.drop([label_column], axis=1)
    train_y = train[[label_column]]
    test_y = test[[label_column]]
    return train_x, train_y, test_x, test_y


def load_csv_data(data_path, label_column):

    data = pd.read_csv(data_path)
    x = data.drop([label_column], axis=1)
    y = data[[label_column]]
    return x, y
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Project-BasicAlgorithm/core/data.py [44:70]:
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        train_x, train_y, test_x, test_y = load_split_csv_data(
            data_path, label_column, test_size=test_size, random_state=random_state
        )

    else:
        raise Exception(PATH_ERROR_MESSAGE)

    return train_x, train_y, test_x, test_y


def load_split_csv_data(data_path, label_column, test_size=0.25, random_state=1):

    data = pd.read_csv(data_path)
    train, test = train_test_split(data, test_size=test_size, random_state=random_state)
    train_x = train.drop([label_column], axis=1)
    test_x = test.drop([label_column], axis=1)
    train_y = train[[label_column]]
    test_y = test[[label_column]]
    return train_x, train_y, test_x, test_y


def load_csv_data(data_path, label_column):

    data = pd.read_csv(data_path)
    x = data.drop([label_column], axis=1)
    y = data[[label_column]]
    return x, y
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