def test_BasicDatasetProfiler_null_column():
    '\n    The profiler should determine that null columns are of null cardinality and of null type and\n    not to generate expectations specific to types and cardinality categories.\n\n    We verify this by running the basic profiler on a Pandas dataset with an empty column\n    and asserting the number of successful results for the empty columns.\n    '
    toy_dataset = PandasDataset({'x': [1, 2, 3], 'y': [None, None, None]}, data_asset_name='toy_dataset')
    assert (len(toy_dataset.get_expectation_suite(suppress_warnings=True)['expectations']) == 0)
    (expectations_config, evr_config) = BasicDatasetProfiler.profile(toy_dataset)
    assert (len([result for result in evr_config['results'] if ((result['expectation_config']['kwargs'].get('column') == 'y') and result['success'])]) == 4)
    assert (len([result for result in evr_config['results'] if ((result['expectation_config']['kwargs'].get('column') == 'y') and result['success'])]) < len([result for result in evr_config['results'] if ((result['expectation_config']['kwargs'].get('column') == 'x') and result['success'])]))
The profiler should determine that null columns are of null cardinality and of null type and
not to generate expectations specific to types and cardinality categories.

We verify this by running the basic profiler on a Pandas dataset with an empty column
and asserting the number of successful results for the empty columns.
def test_BasicDatasetProfiler_null_column():
    '\n    The profiler should determine that null columns are of null cardinality and of null type and\n    not to generate expectations specific to types and cardinality categories.\n\n    We verify this by running the basic profiler on a Pandas dataset with an empty column\n    and asserting the number of successful results for the empty columns.\n    '
    toy_dataset = PandasDataset({'x': [1, 2, 3], 'y': [None, None, None]}, data_asset_name='toy_dataset')
    assert (len(toy_dataset.get_expectation_suite(suppress_warnings=True)['expectations']) == 0)
    (expectations_config, evr_config) = BasicDatasetProfiler.profile(toy_dataset)
    assert (len([result for result in evr_config['results'] if ((result['expectation_config']['kwargs'].get('column') == 'y') and result['success'])]) == 4)
    assert (len([result for result in evr_config['results'] if ((result['expectation_config']['kwargs'].get('column') == 'y') and result['success'])]) < len([result for result in evr_config['results'] if ((result['expectation_config']['kwargs'].get('column') == 'x') and result['success'])]))