geopandas.GeoDataFrame.to_parquet#

GeoDataFrame.to_parquet(path, index=None, compression='snappy', geometry_encoding='WKB', write_covering_bbox=False, schema_version=None, **kwargs)[source]#

Write a GeoDataFrame to the Parquet format.

By default, all geometry columns present are serialized to WKB format in the file.

Requires ‘pyarrow’.

Added in version 0.8.

Parameters:
pathstr, path object
indexbool, default None

If True, always include the dataframe’s index(es) as columns in the file output. If False, the index(es) will not be written to the file. If None, the index(ex) will be included as columns in the file output except RangeIndex which is stored as metadata only.

compression{‘snappy’, ‘gzip’, ‘brotli’, None}, default ‘snappy’

Name of the compression to use. Use None for no compression.

geometry_encoding{‘WKB’, ‘geoarrow’}, default ‘WKB’

The encoding to use for the geometry columns. Defaults to “WKB” for maximum interoperability. Specify “geoarrow” to use one of the native GeoArrow-based single-geometry type encodings. Note: the “geoarrow” option is part of the newer GeoParquet 1.1 specification, should be considered as experimental, and may not be supported by all readers.

write_covering_bboxbool, default False

Writes the bounding box column for each row entry with column name ‘bbox’. Writing a bbox column can be computationally expensive, but allows you to specify a bbox in : func:read_parquet for filtered reading. Note: this bbox column is part of the newer GeoParquet 1.1 specification and should be considered as experimental. While writing the column is backwards compatible, using it for filtering may not be supported by all readers.

schema_version{‘0.1.0’, ‘0.4.0’, ‘1.0.0’, ‘1.1.0’, None}

GeoParquet specification version; if not provided, will default to latest supported stable version (1.0.0).

kwargs

Additional keyword arguments passed to pyarrow.parquet.write_table().

See also

GeoDataFrame.to_feather

write GeoDataFrame to feather

GeoDataFrame.to_file

write GeoDataFrame to file

Examples

>>> gdf.to_parquet('data.parquet')