pandera.schemas.SeriesSchema#
- class pandera.schemas.SeriesSchema(dtype=None, checks=None, index=None, nullable=False, unique=False, report_duplicates='all', coerce=False, name=None, title=None, description=None)[source]#
Series validator.
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
,Hypothesis
,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 column values should be unique.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.
Attributes
checks
Return list of checks or hypotheses.
coerce
Whether to coerce series to specified type.
description
An arbitrary textual description of the series.
dtype
Get the pandas dtype
name
Get SeriesSchema name.
nullable
Whether the series is nullable.
title
A human-readable label for the series.
unique
Whether to check for duplicates in check object
Methods
Initialize series schema base object.
Validate a Series object.
Alias for
SeriesSchema.validate()
method.