ST_DBSCAN (Python)

Perform DBSCAN clustering on the given geometry column. SQL reference: ST_DBSCAN

Signature

from sedona.spark.sql.st_functions import ST_DBSCAN

ST_DBSCAN(
    geometry: ColumnOrName,
    epsilon: Union[ColumnOrName, float],
    min_pts: Union[ColumnOrName, int],
    use_spheroid: Optional[Union[ColumnOrName, bool]] = False,
) -> Column

Parameters

ColumnOrName

required

Geometry column or name.

Union[ColumnOrName, float]

required

Maximum distance between two points for them to be considered neighbors.

Union[ColumnOrName, int]

required

Minimum number of neighbors a point must have to form a cluster.

Optional[Union[ColumnOrName, bool]]

default:"False"

Whether to use ST_DistanceSpheroid instead of ST_Distance as the distance metric. Default is False.

Returns

Column

Struct with the cluster the point belongs to and whether it is a core point.

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Signature

Parameters

Returns