dtoolkit.geoaccessor.geodataframe.duplicated_geometry_groups#

dtoolkit.geoaccessor.geodataframe.duplicated_geometry_groups(df: GeoDataFrame, /, 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