vibespatial.api.tools.overlay

Functions

overlay(df1, df2[, how, keep_geom_type, make_valid])

Perform spatial overlay between two GeoDataFrames.

Module Contents

vibespatial.api.tools.overlay.overlay(df1, df2, how='intersection', keep_geom_type=None, make_valid=True)

Perform spatial overlay between two GeoDataFrames.

Currently only supports data GeoDataFrames with uniform geometry types, i.e. containing only (Multi)Polygons, or only (Multi)Points, or a combination of (Multi)LineString and LinearRing shapes. Implements several methods that are all effectively subsets of the union.

See the User Guide page ../../user_guide/set_operations for details.

Parameters

df1 : GeoDataFrame df2 : GeoDataFrame how : string

Method of spatial overlay: ‘intersection’, ‘union’, ‘identity’, ‘symmetric_difference’ or ‘difference’.

keep_geom_typebool

If True, return only geometries of the same geometry type as df1 has, if False, return all resulting geometries. Default is None, which will set keep_geom_type to True but warn upon dropping geometries.

make_validbool, default True

If True, any invalid input geometries are corrected with a call to make_valid(), if False, a ValueError is raised if any input geometries are invalid.

Returns

dfGeoDataFrame

GeoDataFrame with new set of polygons and attributes resulting from the overlay

Examples

>>> from shapely.geometry import Polygon
>>> polys1 = geopandas.GeoSeries([Polygon([(0,0), (2,0), (2,2), (0,2)]),
...                               Polygon([(2,2), (4,2), (4,4), (2,4)])])
>>> polys2 = geopandas.GeoSeries([Polygon([(1,1), (3,1), (3,3), (1,3)]),
...                               Polygon([(3,3), (5,3), (5,5), (3,5)])])
>>> df1 = geopandas.GeoDataFrame({'geometry': polys1, 'df1_data':[1,2]})
>>> df2 = geopandas.GeoDataFrame({'geometry': polys2, 'df2_data':[1,2]})

>>> geopandas.overlay(df1, df2, how='union')
    df1_data  df2_data                                           geometry
0       1.0       1.0                POLYGON ((2 2, 2 1, 1 1, 1 2, 2 2))
1       2.0       1.0                POLYGON ((2 2, 2 3, 3 3, 3 2, 2 2))
2       2.0       2.0                POLYGON ((4 4, 4 3, 3 3, 3 4, 4 4))
3       1.0       NaN      POLYGON ((2 0, 0 0, 0 2, 1 2, 1 1, 2 1, 2 0))
4       2.0       NaN  MULTIPOLYGON (((3 4, 3 3, 2 3, 2 4, 3 4)), ((4...
5       NaN       1.0  MULTIPOLYGON (((2 3, 2 2, 1 2, 1 3, 2 3)), ((3...
6       NaN       2.0      POLYGON ((3 5, 5 5, 5 3, 4 3, 4 4, 3 4, 3 5))

>>> geopandas.overlay(df1, df2, how='intersection')
   df1_data  df2_data                             geometry
0         1         1  POLYGON ((2 2, 2 1, 1 1, 1 2, 2 2))
1         2         1  POLYGON ((2 2, 2 3, 3 3, 3 2, 2 2))
2         2         2  POLYGON ((4 4, 4 3, 3 3, 3 4, 4 4))

>>> geopandas.overlay(df1, df2, how='symmetric_difference')
    df1_data  df2_data                                           geometry
0       1.0       NaN      POLYGON ((2 0, 0 0, 0 2, 1 2, 1 1, 2 1, 2 0))
1       2.0       NaN  MULTIPOLYGON (((3 4, 3 3, 2 3, 2 4, 3 4)), ((4...
2       NaN       1.0  MULTIPOLYGON (((2 3, 2 2, 1 2, 1 3, 2 3)), ((3...
3       NaN       2.0      POLYGON ((3 5, 5 5, 5 3, 4 3, 4 4, 3 4, 3 5))

>>> geopandas.overlay(df1, df2, how='difference')
                                            geometry  df1_data
0      POLYGON ((2 0, 0 0, 0 2, 1 2, 1 1, 2 1, 2 0))         1
1  MULTIPOLYGON (((3 4, 3 3, 2 3, 2 4, 3 4)), ((4...         2

>>> geopandas.overlay(df1, df2, how='identity')
   df1_data  df2_data                                           geometry
0         1       1.0                POLYGON ((2 2, 2 1, 1 1, 1 2, 2 2))
1         2       1.0                POLYGON ((2 2, 2 3, 3 3, 3 2, 2 2))
2         2       2.0                POLYGON ((4 4, 4 3, 3 3, 3 4, 4 4))
3         1       NaN      POLYGON ((2 0, 0 0, 0 2, 1 2, 1 1, 2 1, 2 0))
4         2       NaN  MULTIPOLYGON (((3 4, 3 3, 2 3, 2 4, 3 4)), ((4...

See Also

sjoin : spatial join GeoDataFrame.overlay : equivalent method

Notes

Every operation in GeoPandas is planar, i.e. the potential third dimension is not taken into account.