Trying to find the point closest to a user inputted point in a geopandas dataframe

Question

import datetime as dt
import pandas as pd
import pandas_datareader as pdr
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.dates as dates
import numpy as np
#import natlparks as pnp
import geopandas as gpd
import geopy as gp
import googlemaps as gm
import shapely
import scipy
from geopy.geocoders import Nominatim
from shapely.geometry import Point
from shapely.ops import nearest_points
#import streamlit as st
#st.title("Finding NY National Parks Near You")
def close_by(pt, location):
    data = pd.read_csv('National_Register_of_Historic_Places (3).csv')
    close_locations = []
    location_latitude = float(location.latitude)
    location_longitude = float(location.longitude)
    #for index, row in data.itterrows():
    close_locations = [shapely.geometry.Point(lon, lat) for lon,lat in zip(data['Longitude'], data['Latitude'])]
    gdf = gpd.GeoDataFrame(data, geometry=close_locations, crs={"init":"EPSG:4326"})
    pts = gdf.geometry.unary_union
    for i, row in gdf:
        print(nearest_points(pt, pts)[0])
    print(gpd[nearest].get_values()[0])
    print(pts)
    print(gdf)




def main():
    data = pd.read_csv('National_Register_of_Historic_Places (3).csv')
    streetNum = input("Enter your number")
    streetName = input("Enter Your Street Name")
    city = input("Enter your city")
    geolocator = Nominatim(user_agent="Final_Project_Python")
    location = geolocator.geocode(f"{streetNum} {streetName} {city} ")
    print(location.address)
    print(location.latitude, location.longitude)
    pt = Point(location.longitude, location.latitude)
    print(float(location.latitude))
    print(float(location.longitude))
    close_by(pt, location)
main()

Currently, the program is meant to try and find the closest national park from the csv data by finding the nearest point after the user enters their address. What do I do to run through the dataset and find the closest point? CSV has columns 'Resource Name', 'County', 'National Register Date', 'National Register Number', 'Longitude', 'Latitude', and 'Georeference'

Answer 1

• use public sources of geojson for national parks
• use public source of addresses - picked hospitals
• these addresses do include longitude / latitude. This can be looked up with APIs if you have a post code
• real approach
  1. generate combinations of NPs and addresses
  2. calculate distances using geopy
  3. filter down to nearest NP to address
• provide sample output - from my knowledge of England looks correct

import geopandas as gpd
import pandas as pd
import requests, io, json
import geopy.distance

# get national parks in England
np = gpd.read_file(io.StringIO(json.dumps(requests.get("https://opendata.arcgis.com/datasets/d333c7529754444894e2d7f5044d1bbf_0.geojson").json())))
# get some public addressess - hospitals
dfhos = pd.read_csv(io.StringIO(requests.get("http://media.nhschoices.nhs.uk/data/foi/Hospital.csv").text), sep="¬", engine="python")

# use centre of NP as geo co-ords.  Ignore warning of CRS system!
np["centre"] = np.centroid.apply(lambda x: (x.y,x.x))

# pick an address in each county...
dfhos = dfhos.dropna(subset=["County"]).loc[dfhos.groupby("County", as_index=False).cumcount().lt(1)]

# cartesian product of addresses to NPs - all combinations
dfm = pd.merge(
    np.loc[:,["NAME","centre"]].reset_index().rename(columns={"index":"np_index"}).assign(foo=1)
    ,dfhos.loc[:,["OrganisationName","County","Postcode","Longitude","Latitude"]].reset_index().rename(columns={"index":"addr_index"}).assign(foo=1)
    ,on="foo"
).drop(columns="foo")

# calc distance between centre of NP and addresses, then filter down to nearest NP
dfnearest = (dfm.assign(distance=dfm.apply(lambda r: geopy.distance.geodesic(r["centre"], 
                                                                             (r["Latitude"], r["Longitude"])).km, axis=1))
 .sort_values(["addr_index","distance"], ascending=[1,1])
 .groupby(["addr_index"], as_index=False).first()
)

dfnearest.sort_values("distance").loc[:,["np_index","NAME","OrganisationName","County","Postcode","distance"]].head(10)

	np_index	NAME	OrganisationName	County	Postcode	distance
26	6	NEW FOREST	Southampton General Hospital	Hampshire	SO16 6YD	14.0999
42	5	NORTH YORK MOORS	Guisborough General Hospital	Cleveland	TS14 6HZ	21.3057
27	3	PEAK DISTRICT	Charles Clifford Dental Hospital	South Yorkshire	S10 2SZ	22.4807
51	6	NEW FOREST	St Mary's	Isle of Wight	PO30 5TG	26.3622
5	4	DARTMOOR	Torbay Hospital	Devon	TQ2 7AA	27.3006
21	3	PEAK DISTRICT	Chesterfield Royal Hospital	Derbyshire	S44 5BL	27.7963
36	8	LAKE DISTRICT	Cockermouth Community Hospital	Cumbria	CA13 9HT	28.9103
13	3	PEAK DISTRICT	The Christie main site	Greater Manchester	M20 4BX	31.9218
2	0	SOUTH DOWNS	Royal Surrey County Hospital	Surrey	GU2 7XX	32.5091
15	5	NORTH YORK MOORS	St Monicas Hospital	North Yorkshire	YO61 3JD	34.7372