Core

Schemas

pandera.api.pandas.container.DataFrameSchema	A light-weight pandas DataFrame validator.
pandera.api.pandas.array.SeriesSchema	A pandas Series validator.
pandera.api.polars.container.DataFrameSchema	A polars LazyFrame or DataFrame validator.
pandera.api.pyspark.container.DataFrameSchema	A light-weight PySpark DataFrame validator.
pandera.api.dataframe.container.DataFrameSchema	Library-agnostic base class for DataFrameSchema definitions.

Schema Components

pandera.api.pandas.components.Column	Validate types and properties of pandas DataFrame columns.
pandera.api.pandas.components.Index	Validate types and properties of a pandas DataFrame Index.
pandera.api.pandas.components.MultiIndex	Validate types and properties of a pandas DataFrame MultiIndex.
pandera.api.polars.components.Column	Polars column schema component.
pandera.api.pyspark.components.Column	Validate types and properties of DataFrame columns.
pandera.api.dataframe.components.ComponentSchema	Base class for data container component, e.g. columns.

Checks

pandera.api.checks.Check	Check a data object for certain properties.
pandera.api.hypotheses.Hypothesis	Special type of Check that defines hypothesis tests on data.

Data Objects

pandera.api.polars.types.PolarsData	Create new instance of PolarsData(lazyframe, key)
pandera.api.pyspark.types.PysparkDataframeColumnObject	Pyspark Object which holds dataframe and column value in a named tuble

Configuration

pandera.config.PanderaConfig	Pandera config base class.
pandera.config.ValidationDepth	Whether to apply checks at schema- or data-level, or both.
pandera.config.ValidationScope	Indicates whether a check/validator operates at a schema of data level.
pandera.config.config_context	Temporarily set pandera config options to custom settings.
pandera.config.get_config_context	Gets the configuration context.