Skip to main content
A pandas-on-Spark Series for geometric/spatial operations. GeoSeries extends pyspark.pandas.Series to provide spatial operations using Apache Sedona’s spatial functions. It maintains compatibility with GeoPandas GeoSeries while operating on distributed datasets. Initialize a GeoSeries object.

Parameters

array-like, GeoDataFrame, GeoSeries, or pandas Series
default:"None"
The input data for the GeoSeries.
array - like
default:"None"
The index for the GeoSeries.
dtype
default:"None"
Data type for the GeoSeries.
str
default:"None"
Name of the GeoSeries.
bool
default:"False"
Whether to copy the input data.
bool
default:"False"
Internal parameter for fast initialization.
pyproj.CRS
default:"None"
Coordinate Reference System for the GeoSeries.
This implementation differs from GeoPandas in several ways:
  • Uses Spark for distributed processing
  • Geometries are stored in WKB (Well-Known Binary) format internally
  • Some methods may have different performance characteristics
  • Not all GeoPandas methods are implemented yet (see Sedona GeoPandas docs).
Performance Considerations:
  • Operations are distributed across Spark cluster
  • Avoid calling .to_geopandas() on large datasets
  • Use .sample() for testing with large datasets
See also
  • geopandas.GeoSeries: The GeoPandas equivalent
  • sedona.spark.geopandas.GeoDataFrame: DataFrame with geometry column

Examples

Example 1: Initialize with GeoDataFrame

Example 2: Initialize with GeoSeries

Example 3: Initialize with pandas Series

Properties

Methods