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How to use numpy_pandas_coerce_failure_cases method in pandera

Best Python code snippet using pandera_python

utils.py

Source:utils.py

...19            return True20        except Exception:  # pylint:disable=broad-except21            return False22    return series.map(_coercible)23def numpy_pandas_coerce_failure_cases(24    data_container: Union[PandasObject, np.ndarray], type_: Any25) -> PandasObject:26    """27    Get the failure cases resulting from trying to coerce a pandas/numpy object28    into particular data type.29    """30    # pylint: disable=import-outside-toplevel,cyclic-import31    from pandera import error_formatters32    from pandera.engines import pandas_engine33    data_type = pandas_engine.Engine.dtype(type_)34    if isinstance(data_container, np.ndarray):35        if len(data_container.shape) == 1:36            data_container = pd.Series(data_container)37        elif len(data_container.shape) == 2:...

test_engine_utils.py

Source:test_engine_utils.py

...27        pd.DataFrame({0: [1, 2, 3, 4]}),28        np.array([[1], [2], [3], [4]]),29    ],30)31def test_numpy_pandas_coerce_failure_cases(data_container):32    """33    Test that different data container types can be checked for coerce failure34    cases.35    """36    failure_cases = utils.numpy_pandas_coerce_failure_cases(37        data_container, int38    )39    assert isinstance(failure_cases, pd.DataFrame)40    assert failure_cases.empty41@pytest.mark.parametrize(42    "invalid_data_container, exception_type",43    [44        [1, TypeError],45        [5.1, TypeError],46        ["foobar", TypeError],47        [[1, 2, 3], TypeError],48        [{0: 1}, TypeError],49        # pylint: disable=too-many-function-args50        [np.array([1]).reshape(1, 1, 1), ValueError],51    ],52)53def test_numpy_pandas_coerce_failure_cases_exceptions(54    invalid_data_container, exception_type55):56    """57    Test exceptions of trying to get failure cases for invalid input types.58    """59    error_msg = {60        TypeError: "type of data_container .+ not understood",61        ValueError: "only numpy arrays of 1 or 2 dimensions are supported",62    }[exception_type]63    with pytest.raises(exception_type, match=error_msg):...

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