sedona.spark.geoarrow package

Submodules

sedona.spark.geoarrow.geoarrow module

sedona.spark.geoarrow.geoarrow.create_spatial_dataframe(spark: SparkSession, gdf: gpd.GeoDataFrame) → DataFrame

sedona.spark.geoarrow.geoarrow.crs_to_json(crs)

sedona.spark.geoarrow.geoarrow.dataframe_to_arrow(df, crs=None)

Collect a DataFrame as a PyArrow Table

In the output Table, geometry will be encoded as a GeoArrow extension type. The resulting output is compatible with lonboard.viz(), geopandas.GeoDataFrame.from_arrow(), or any library compatible with GeoArrow extension types.

Parameters:

• df – A Spark DataFrame

• crs – A CRS-like object (e.g., pyproj.CRS or string interpretable by pyproj.CRS). If provided, this will override any CRS present in the output geometries. If omitted, the CRS will be inferred from the values present in the output if exactly one CRS is present in the output.

Returns:

sedona.spark.geoarrow.geoarrow.dataframe_to_arrow_raw(df)

Backport of toArrow() (available in Spark 4.0)

sedona.spark.geoarrow.geoarrow.infer_schema(gdf: gpd.GeoDataFrame) → StructType

sedona.spark.geoarrow.geoarrow.try_register_extension_types()

Try to register extension types using geoarrow-types

Do this defensively, because it can fail if the extension type was registered in some other way (notably: old versions of geoarrow-pyarrow, which is a dependency of Kepler).

sedona.spark.geoarrow.geoarrow.unique_srid_from_ewkb(obj)

sedona.spark.geoarrow.geoarrow.wrap_geoarrow_extension(col, spec, crs)

sedona.spark.geoarrow.geoarrow.wrap_geoarrow_field(field, col, crs)

Module contents