pandera.geopandas.GeoDataFrameModel¶

class pandera.geopandas.GeoDataFrameModel(*args, **kwargs)[source]¶

Class-based schema for geopandas.GeoDataFrame data.

Inherits DataFrameModel and reuses the same schema-building and validation logic. Use this model when validate(), example(), empty(), and strategy() should return a geopandas.GeoDataFrame (preserving geometry columns and CRS metadata) even if the pandas backend produced a plain pandas.DataFrame.

Requires the geopandas extra. Use with pandera.typing.geopandas.GeoDataFrame for validate-on-init, e.g. GeoDataFrame[MyModel](...).

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]¶

Build a GeoDataFrameSchema from the model definition.

classmethod empty(*_args)[source]¶

Create an empty geopandas.GeoDataFrame with this schema.

classmethod example(cls, **kwargs)[source]¶

Generate an example of this data model specification.

classmethod strategy(cls, **kwargs)[source]¶: Create a data synthesis strategy.

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