pandera.api.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, default=None, metadata=None, drop_invalid_rows=False)[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 theAny
input 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.default (
Optional
[Any
]) – The default value for missing values in the series.drop_invalid_rows (
bool
) – if True, drop invalid rows on validation.