Comparing two dataframes with a function (without common indices) - python-3.x

Question

I have 2 pandas data frames, restaurants:
Lat Long Name
0 43.599503 1.440678 Le Filochard
1 43.602369 1.447368 Le Wallace
2 43.603838 1.435186 Chez Tonton, Pastis Ô Maître
and hotels:
Lat Long Name
0 43.603779 1.444004 Grand Hôtel de l'Opéra
1 43.599482 1.441207 Hôtel Garonne
2 43.549924 1.499821 Ibis Styles
And 1 function distance(origin,destination) with origin = (lat,long) coord.
I am trying to apply the function to the 2 data frames to calculate for each row of the first data frame the number of item from the second data frame for which the distance is inferior to 0.2 ...
I'm trying the apply map function but do not manage to perform it with the 2 data frames; do I need to merge them?

Answer 1

Would this work for you?
Just need to correct function for distance
hotels=pd.DataFrame([[43.599503, 1.440678, 'Le Filochard'],
[43.602369, 1.447368, 'Le Wallace'],
[43.603838, 1.435186, 'Chez Tonton, Pastis Ô Maître']],
columns=['Lat', 'Long', 'Name'])
restaurants=pd.DataFrame([[43.603779, 1.444004, "Grand Hôtel de l'Opéra"],
[43.599482, 1.441207, 'Hôtel Garonne'],
[43.549924, 1.499821, 'Ibis Styles']],
columns=['Lat', 'Long', 'Name'])
hotels['Nearby Resaurants'] = hotels.apply(lambda h: list(restaurants[((restaurants.Lat-h.Lat)**2+(restaurants.Long-h.Long)**2)<0.005].Name), axis=1)
print(hotels)
Lat Long Name \
0 43.599503 1.440678 Le Filochard
1 43.602369 1.447368 Le Wallace
2 43.603838 1.435186 Chez Tonton, Pastis Ô Maître
Nearby Resaurants
0 [Grand Hôtel de l'Opéra, Hôtel Garonne]
1 [Grand Hôtel de l'Opéra, Hôtel Garonne]
2 [Grand Hôtel de l'Opéra, Hôtel Garonne]
EDIT:
Modification to handle function, filtering of hotels also by using lambda function
def distance(X,Y):
return((X[0]-X[1])**2+(Y[0]-Y[1])**2)
hotels['Nearby Resaurants'] = hotels.apply(lambda h: list(restaurants.loc[restaurants.apply(lambda r: distance((r.Lat,h.Lat),(r.Long,h.Long))<0.005, axis=1)].Name), axis=1)
print(hotels)