Btukfyl

I have a list of named polygons:

import pandas as pd

import geopandas as gp

from shapely.geometry import Polygon

from shapely.geometry import Point

import matplotlib.path as mpltPath

df = gp.GeoDataFrame([['a', Polygon([(1, 0), (1, 1), (2,2), (1,2)])],

                     ['b', Polygon([(1, 1), (2,2), (3,1)])]],

                     columns = ['name','geometry'])

df = gp.GeoDataFrame(df, geometry = 'geometry')

and a list of points:

points = gp.GeoDataFrame( [['box', Point(1.5, 1.75)],

                          ['cone', Point(3.0,2.0)],

                        ['triangle', Point(2.5,1.25)]],

                     columns=['id', 'geometry'], 

                     geometry='geometry')

I am trying to find out what points are in what polygons and add a column to the point dataframe with 'True' or 'False'

I've previously been shown the methods here which show some ways of quickly doing this and have got the script:

point = points['geometry']

path = mpltPath.Path(df['geometry'])

points['inside'] = path.contains_points(point)

but I get the error: float() argument must be a string or a number, not 'Polygon'

How do I fix this?

Alternatively I have been trying this method:

points['inside'] = 

for geo1 in df['geometry']:

    for geo2 in points['geometry']:

        if geo1.contains(geo2):

            points['inside'].append('True')

however here I also get an error: Length of values des not match length of index

Any help with either of these would be greatly appreciated!

I didn't get the "true/false column", but this should do the job:

points.apply(lambda row: (row['id'], list(map(lambda e: e[0], list(filter(lambda p: p[1].contains(row['geometry']), df.values))))), axis=1)

For each point you get the polygons that contains it, output:

0         (box, [a])

1         (cone, )

2    (triangle, [b])

dtype: object