pandera.core.pandas.array.SeriesSchema.__init__#
- SeriesSchema.__init__(dtype=None, checks=None, index=None, nullable=False, unique=False, report_duplicates='all', coerce=False, name=None, title=None, description=None)[source]#
Initialize series schema base object.
- Parameters
dtype (
Union[str,type,DataType,Type,ExtensionDtype,dtype,None]) – datatype of the column. If a string is specified, then assumes one of the valid pandas string values: http://pandas.pydata.org/pandas-docs/stable/basics.html#dtypeschecks (
Union[Check,List[Union[Check,Hypothesis]],None]) –If element_wise is True, then callable signature should be:
Callable[Any, bool]where theAnyinput is a scalar element in the column. Otherwise, the input is assumed to be a pandas.Series object.index – specify the datatypes and properties of the index.
nullable (
bool) – Whether or not column can contain null values.unique (
bool) – Whether or not column can contain duplicate values.report_duplicates (
Union[Literal[‘exclude_first’],Literal[‘exclude_last’],Literal[‘all’]]) – how to report unique errors - exclude_first: report all duplicates except first occurence - exclude_last: report all duplicates except last occurence - all: (default) report all duplicatescoerce (
bool) – If True, when schema.validate is called the column will be coerced into the specified dtype. This has no effect on columns wheredtype=None.title (
Optional[str]) – A human-readable label for the series.description (
Optional[str]) – An arbitrary textual description of the series.