Link Each Point In One Geopandas Dataframe To Polygons In Another Dataframe

I searched for my problem and found this question which is different from my issue. I have two geo data frames, one contains houses locations as points (~700 points) and the other

Solution 1:

I found a way to accomplish this by joining the two data frames using a spatial join

joinDF=gpd.sjoin(pointsDF, polysgdf, how='left',op="within")

Solution 2:

Use shapely's Point-in-Polygon analysis using .contains function as follows.

import geopandas as gpd
from shapely.geometry import Point
from shapely.geometry.polygon import Polygon

polys = gpd.GeoSeries({
    '6672': Polygon([(0, 0), (0, 1), (1, 0)]),
    '6372': Polygon([(0, 1), (1, 1), (1, 0)]),
})

#creating geo dataframe
polysgdf = gpd.GeoDataFrame(geometry=gpd.GeoSeries(polys))
polysgdf
Out[48]: 
                            geometry
6672  POLYGON ((00, 01, 10, 00))
6372  POLYGON ((01, 11, 10, 01))

points=[Point(0.25,0.25), Point(0.75,0.75), 
        Point(145.02190, -37.85450)]

pointsDF = gpd.GeoDataFrame(geometry=points,
                                  index=['house1_ID', 'house2_ID', 'house3_ID'])

pointsDF
Out[49]: 
                            geometry
house1_ID          POINT (0.250.25)
house2_ID          POINT (0.750.75)
house3_ID  POINT (145.0219 -37.8545)

polysgdf['house_ID'] = ''for i inrange(0,len(pointsDF)):
    print('Check for house '+str(pointsDF.index.values.astype(str)[i]))
    for j inrange(0,len(polysgdf)):
        print('Check for suburb '+str(polysgdf.index.values.astype(str)[j]))
        if polysgdf['geometry'][j].contains(pointsDF['geometry'][i]) == True:
            polysgdf['house_ID'][j] = pointsDF.index.values.astype(str)[i]

print(polysgdf)
                            geometry   house_ID
6672  POLYGON ((00, 01, 10, 00))  house1_ID
6372  POLYGON ((01, 11, 10, 01))  house2_ID