Esempio n. 1
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 def test_inplace_param(self):
     df = pd.DataFrame(np.random.randint(-5, 5, size=[100, 5], dtype='int64'), columns=['a', 'b', 'c', 'd', 'e'])  # noqa: E501
     df_copy = df.copy()
     DFReduce(df_copy, inplace=True).reduce()
     self.assertEqual(np.isclose(df, df_copy, rtol=1e-7, atol=1e-7, equal_nan=False).all(), True)  # noqa: E501
Esempio n. 2
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 def test_string_type(self):
     df = pd.DataFrame(np.random.randn(100000, 1), columns=['a'])
     df.a = df.a.astype(np.str)
     test_df = DFReduce(df).reduce()
     self.assertEqual(test_df.a.dtype.name, 'object')
Esempio n. 3
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 def test_cat_type(self):
     df = pd.DataFrame(['test'] * 100, columns=['a'])
     test_df = DFReduce(df).reduce()
     self.assertEqual(test_df.a.dtype.name, 'category')
Esempio n. 4
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 def test_string_values_equality(self):
     df = pd.DataFrame(np.random.randn(100000, 1), columns=['a'])
     df.a = df.a.astype(np.str)
     test_df = DFReduce(df).reduce()
     self.assertEqual((test_df.a == df.a).all(), True)
Esempio n. 5
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    def test_float_values_equality(self):
        df = pd.DataFrame(np.random.randn(100000, 5), columns=['a', 'b', 'c', 'd', 'e'])  # noqa: E501

        test_df = DFReduce(df).reduce()
        self.assertEqual(np.isclose(df, test_df, rtol=1e-7, atol=1e-7, equal_nan=False).all(), True)  # noqa: E501
Esempio n. 6
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 def test_int16_type_equality(self):
     df = pd.DataFrame(np.random.randint(-12345, 12345, size=[1000, 5], dtype='int64'), columns=['a', 'b', 'c', 'd', 'e'])  # noqa: E501
     test_df = DFReduce(df).reduce()
     self.assertEqual(test_df.a.dtype.name, 'int16')
Esempio n. 7
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 def test_int8_values_equality(self):
     df = pd.DataFrame(np.random.randint(-5, 5, size=[100, 5], dtype='int64'), columns=['a', 'b', 'c', 'd', 'e'])  # noqa: E501
     test_df = DFReduce(df).reduce()
     self.assertEqual(np.isclose(df, test_df, rtol=1e-7, atol=1e-7, equal_nan=False).all(), True)  # noqa: E501
Esempio n. 8
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 def test_check_dataframe_type(self):
     df = 'test'
     with self.assertRaises(ValueError):
         DFReduce(df).reduce()