614ff7af666ecaab6dfa42f7377ec4c1608b1ff6,aif360/datasets/adult_dataset.py,AdultDataset,__init__,#AdultDataset#,25

Before Change

        train_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
                                  "../data/raw/adult/adult.data")
        test_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
                                  "../data/raw/adult/adult.test")
        // as given by adult.names
        column_names = ["age", "workclass", "fnlwgt", "education",
            "education-num", "marital-status", "occupation", "relationship",
            "race", "sex", "capital-gain", "capital-loss", "hours-per-week",
            "native-country", "income-per-year"]
        train = pd.read_csv(train_path, header=None, names=column_names,
            skipinitialspace=True, na_values=na_values)
        test = pd.read_csv(test_path, header=0, names=column_names,
            skipinitialspace=True, na_values=na_values)

        df = pd.concat([train, test], ignore_index=True)

        super(AdultDataset, self).__init__(df=df, label_name=label_name,

After Change

        train_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
                                  "..", "data", "raw", "adult", "adult.data")
        test_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
                                  "..", "data", "raw", "adult", "adult.test")
        // as given by adult.names
        column_names = ["age", "workclass", "fnlwgt", "education",
            "education-num", "marital-status", "occupation", "relationship",
            "race", "sex", "capital-gain", "capital-loss", "hours-per-week",
            "native-country", "income-per-year"]
        try:
            train = pd.read_csv(train_path, header=None, names=column_names,
                skipinitialspace=True, na_values=na_values)
            test = pd.read_csv(test_path, header=0, names=column_names,
                skipinitialspace=True, na_values=na_values)
        except IOError as err:
            print("IOError: {}".format(err))
            print("To use this class, please download the following files:")
            print("\n\thttps://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data")
            print("\thttps://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.test")
            print("\thttps://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.names")
            print("\nand place them, as-is, in the folder:")
            print("\n\t{}\n".format(os.path.abspath(os.path.join(
               os.path.abspath(__file__), "..", "..", "data", "raw", "adult"))))
            import sys
            sys.exit(1)

        df = pd.concat([train, test], ignore_index=True)

        super(AdultDataset, self).__init__(df=df, label_name=label_name,
            favorable_classes=favorable_classes,

Instances