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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