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How to use prepare_series_check_output method in pandera

Best Python code snippet using pandera_python

check_utils.py

Source:check_utils.py

...67    return isinstance(obj, _supported_types().multiindex_types)68def is_supported_check_obj(obj):69    """Verifies whether an object is table- or field-like."""70    return is_table(obj) or is_field(obj)71def prepare_series_check_output(72    check_obj: Union[pd.Series, pd.DataFrame],73    check_output: pd.Series,74    ignore_na: bool = True,75    n_failure_cases: Optional[int] = None,76) -> Tuple[pd.Series, pd.Series]:77    """Prepare the check output and failure cases for a Series check output.78    check_obj can be a dataframe, since a check function can potentially return79    a Series resulting from applying some check function that outputs a Series.80    """81    if ignore_na:82        isna = (83            check_obj.isna().any(axis="columns")84            if isinstance(check_obj, pd.DataFrame)85            else check_obj.isna()...

utils.py

Source:utils.py

...90            ignore_na=False,91        )92    elif check_utils.is_field(data_container):93        check_output = numpy_pandas_coercible(data_container, data_type)94        _, failure_cases = check_utils.prepare_series_check_output(95            data_container,96            check_output,97            ignore_na=False,98        )99    else:100        raise TypeError(101            f"type of data_container {type(data_container)} not understood. "102            "Must be a pandas Series, Index, or DataFrame."103        )104    return error_formatters.reshape_failure_cases(105        failure_cases, ignore_na=False...

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