# geopandas point in polygon

## Question:

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!

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
``````
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