class pandera.api.pandas.components.Index(dtype=None, checks=None, nullable=False, unique=False, report_duplicates='all', coerce=False, name=None, title=None, description=None, default=None)[source]#

Validate types and properties of a DataFrame Index.

Initialize array schema.

  • 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:

  • checks (Union[Check, List[Union[Check, Hypothesis]], None]) –

    If element_wise is True, then callable signature should be:

    Callable[Any, bool] where the Any input is a scalar element in the column. Otherwise, the input is assumed to be a pandas.Series object.

  • 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 duplicates

  • coerce (bool) – If True, when schema.validate is called the column will be coerced into the specified dtype. This has no effect on columns where dtype=None.

  • name (Optional[Any]) – column name in dataframe to validate.

  • 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.




Get the pandas dtype


Get index names in the Index schema component.


Get the properties of the schema for serialization purposes.



Generate an example of a particular size.


Create a hypothesis strategy for generating an Index.


Generate column data object for use by MultiIndex strategy.


Validate DataFrameSchema or SeriesSchema Index.


Alias for validate method.