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How to use test_dataframe_coerce_regex method in pandera

Best Python code snippet using pandera_python

test_schemas.py

Source:test_schemas.py

...181    # columns to int182    schema.coerce = False183    pd_dtypes = [Engine.dtype(pd_dtype) for pd_dtype in schema(df).dtypes]184    assert all(pd_dtype == Engine.dtype(float) for pd_dtype in pd_dtypes)185def test_dataframe_coerce_regex() -> None:186    """Test dataframe pandas dtype coercion for regex columns"""187    schema = DataFrameSchema(188        columns={"column_": Column(float, regex=True, required=False)},189        dtype=int,190        coerce=True,191    )192    no_match_df = pd.DataFrame({"foo": [1, 2, 3]})193    match_valid_df = pd.DataFrame(194        {195            "column_1": [1, 2, 3],196            "column_2": ["1", "2", "3"],197        }198    )199    schema(no_match_df)...

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