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pythonpandasgeopandaspoint-in-polygon

geopandas point in polygon


I have a GeoDataFrame of polygons (~30) and a GeoDataFrame of Points (~10k)

I'm looking to create 30 new columns (with appropriate polygon names) in my GeoDataFrame of Points with a simple boolean True/False if the point is present in the polygon.

As an example, the GeoDataFrame of Polygons is this:

id  geometry
foo POLYGON ((-0.18353,51.51022, -0.18421,51.50767, -0.18253,51.50744, -0.1794,51.50914))
bar POLYGON ((-0.17003,51.50739, -0.16904,51.50604, -0.16488,51.50615, -0.1613,51.5091))

The GeoDataFrame of Points is like this:

counter     points
   1     ((-0.17987,51.50974))
   2     ((-0.16507,51.50925))

Expected output:

counter          points        foo    bar
   1    ((-0.17987,51.50974))  False  False
   1    ((-0.16507,51.50925))  False  False

I can do this manually by:

foo = df_poly.loc[df_poly.id=='foo']
df_points['foo'] = df_points['points'].map(lambda x: True if foo.contains(x).any()==True else False

But given that I have 30 polygons, I was wondering if there is a better way. Appreciate any help!


Solution

  • Not really clear what kind of data structures you actually have. Also, all your expected results are False, so that's kind of hard to check. Assuming GeoSeries and GeoDataFrames, I would do this:

    from shapely.geometry import Point, Polygon
    import geopandas
    
    polys = geopandas.GeoSeries({
        'foo': Polygon([(5, 5), (5, 13), (13, 13), (13, 5)]),
        'bar': Polygon([(10, 10), (10, 15), (15, 15), (15, 10)]),
    })
    
    _pnts = [Point(3, 3), Point(8, 8), Point(11, 11)]
    pnts = geopandas.GeoDataFrame(geometry=_pnts, index=['A', 'B', 'C'])
    pnts = pnts.assign(**{key: pnts.within(geom) for key, geom in polys.items()})
    
    print(pnts)
    

    And that gives me:

            geometry    bar    foo
    A    POINT (3 3)  False  False
    B    POINT (8 8)  False   True
    C  POINT (11 11)   True   True