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__all__ = ['AdultDataset'] |
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import numpy as np |
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import pandas as pd |
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from pkg_resources import resource_filename |
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from ethically.dataset.core import Dataset |
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ADULT_TRAIN_PATH = resource_filename(__name__, |
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'adult.data') |
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ADULT_TEST_PATH = resource_filename(__name__, |
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'adult.test') |
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COLUMN_NAMES = ['age', 'workclass', 'fnlwgt', 'education', |
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'education-num', 'marital_status', 'occupation', |
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'relationship', 'race', 'sex', 'capital_gain', |
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'capital_loss', 'hours_per_week', 'native_country', |
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'income_per_year'] |
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class AdultDataset(Dataset): |
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"""Adult Dataset. |
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See :class:`~ethically.dataset.Dataset` for a description of |
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the arguments and attributes. |
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References: |
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https://archive.ics.uci.edu/ml/datasets/adult |
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""" |
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def __init__(self): |
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super().__init__(target='income_per_year', |
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sensitive_attributes=['sex', 'race']) |
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def _load_data(self): |
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train_df = pd.read_csv(ADULT_TRAIN_PATH, names=COLUMN_NAMES, |
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skipinitialspace=True, |
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header=None, index_col=False, |
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na_values='?') |
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test_df = pd.read_csv(ADULT_TEST_PATH, names=COLUMN_NAMES, |
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skipinitialspace=True, |
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header=0, index_col=False, |
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na_values='?') |
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train_df['dataset'] = 'train' |
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test_df['dataset'] = 'test' |
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return pd.concat([train_df, test_df], ignore_index=True) |
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def _preprocess(self): |
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"""Perform the same preprocessing as the dataset doc file.""" |
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self.df = self.df.dropna() |
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self.df = self.df.drop(['fnlwgt'], axis=1) |
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self.df['income_per_year'] = (self.df['income_per_year'] |
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.str |
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.replace('.', '')) |
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def _validate(self): |
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# pylint: disable=line-too-long |
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super()._validate() |
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assert len(self.df) == 45222, 'the number of rows should be 45222,'\ |
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' but it is {}.'.format(len(self.df)) |
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assert len(self.df.columns) == 15, 'the number of columns should be 15,'\ |
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' but it is {}.'.format(len(self.df.columns)) |
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train_df = self.df[self.df['dataset'] == 'train'] |
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test_df = self.df[self.df['dataset'] == 'test'] |
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assert len(train_df) == 30162, 'the number of train rows should be 30162,'\ |
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' but it is {}.'.format(len(train_df)) |
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assert len(test_df) == 15060, 'the number of train rows should be 15060,'\ |
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' but it is {}.'.format(len(test_df)) |
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ResponsiblyAI /
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