pandera.api.pandas.model.DataFrameModel

class pandera.api.pandas.model.DataFrameModel(*args, **kwargs)[source]

Model of a pandas DataFrameSchema.

new in 0.5.0

See the User Guide for more.

Validate a DataFrame based on the schema specification.

Parameters:

  • check_obj (pd.DataFrame) – the dataframe to be validated.

  • head – validate the first n rows. Rows overlapping with tail or sample are de-duplicated.

  • tail – validate the last n rows. Rows overlapping with head or sample are de-duplicated.

  • sample – validate a random sample of n rows. Rows overlapping with head or tail are de-duplicated.

  • random_state – random seed for the sample argument.

  • lazy – if True, lazily evaluates dataframe against all validation checks and raises a SchemaErrors. Otherwise, raise SchemaError as soon as one occurs.

  • inplace – if True, applies coercion to the object of validation, otherwise creates a copy of the data.

Returns:

validated DataFrame

Raises:

SchemaError – when DataFrame violates built-in or custom checks.

Methods

classmethod build_schema_(**kwargs)[source]
Return type:

DataFrameSchema

classmethod empty(*_args)[source]

Create an empty DataFrame with the schema of this model.

Return type:

DataFrame[Self]

classmethod to_json_schema()[source]

Serialize schema metadata into json-schema format.

Parameters:

dataframe_schema – schema to write to json-schema format.

Note

This function is currently does not fully specify a pandera schema, and is primarily used internally to render OpenAPI docs via the FastAPI integration.

classmethod validate(check_obj, head=None, tail=None, sample=None, random_state=None, lazy=False, inplace=False)[source]

Validate a DataFrame based on the schema specification.

Parameters:

  • check_obj (pd.DataFrame) – the dataframe to be validated.

  • head (Optional[int]) – validate the first n rows. Rows overlapping with tail or sample are de-duplicated.

  • tail (Optional[int]) – validate the last n rows. Rows overlapping with head or sample are de-duplicated.

  • sample (Optional[int]) – validate a random sample of n rows. Rows overlapping with head or tail are de-duplicated.

  • random_state (Optional[int]) – random seed for the sample argument.

  • lazy (bool) – if True, lazily evaluates dataframe against all validation checks and raises a SchemaErrors. Otherwise, raise SchemaError as soon as one occurs.

  • inplace (bool) – if True, applies coercion to the object of validation, otherwise creates a copy of the data.

Return type:

DataFrame[Self]

Returns:

validated DataFrame

Raises:

SchemaError – when DataFrame violates built-in or custom checks.