dtoolkit.geoaccessor.geoseries.duplicated_geometry_groups#

dtoolkit.geoaccessor.geoseries.duplicated_geometry_groups(s: GeoSeries, /, predicate: Literal['intersects', 'crosses', 'overlaps', 'touches', 'covered_by', 'contains_properly', 'contains', 'within', 'covers'] = 'intersects') → Series[source]#

Labels of duplicate geometries.

Parameters:

predicate{‘intersects’, ‘crosses’, ‘overlaps’, ‘touches’, ‘covered_by’, ‘contains_properly’, ‘contains’, ‘within’, ‘covers’}, default ‘intersects’: The binary predicate is used to validate whether the geometries are duplicates or not.

Returns:

Series(int64): index is the index of inputting, values is the labels of groups. And labels are natural numbers.

Warns:

UserWarning: If the index of the inputting is not unique.

See also

geopandas.sjoin
dtoolkit.geoaccessor.geoseries.duplicated_geometry
dtoolkit.geoaccessor.geoseries.duplicated_geometry_groups
dtoolkit.geoaccessor.geodataframe.duplicated_geometry
dtoolkit.geoaccessor.geodataframe.duplicated_geometry_groups

Examples

>>> import dtoolkit.geoaccessor
>>> import geopandas as gpd
>>> from shapely import Polygon
>>> df = gpd.GeoDataFrame(
...     geometry=[
...         Polygon([(0,0), (1,0), (1,1), (0,1)]),
...         Polygon([(1,1), (2,1), (2,2), (1,2)]),
...         Polygon([(2,2), (3,2), (3,3), (2,3)]),
...         Polygon([(2, 0), (3, 0), (3, 1)]),
...     ],
... )
>>> df
                                            geometry
0  POLYGON ((0.00000 0.00000, 1.00000 0.00000, 1....
1  POLYGON ((1.00000 1.00000, 2.00000 1.00000, 2....
2  POLYGON ((2.00000 2.00000, 3.00000 2.00000, 3....
3  POLYGON ((2.00000 0.00000, 3.00000 0.00000, 3....

0 and 1 are intersecting.
1 and 2 are intersecting.
3 is alone.

So there are two groups: (0, 1, 2) and (3,).

>>> df.duplicated_geometry_groups()
0    0
1    0
2    0
3    1
dtype: int64