[Python] [Data Visualization] Geocode AIP를 사용하여 위치 정보 불러오기

Google Maps API 활용 지도 시각화¶

In [33]:

import googlemaps

gmaps_key = 'Your API Key'
gmaps = googlemaps.Client(key=gmaps_key)

geocode = gmaps.geocode(address='1547 N. Wells St Chicago')
geocode

Out[33]:

[{'address_components': [{'long_name': '1547',
    'short_name': '1547',
    'types': ['street_number']},
   {'long_name': 'North Wells Street',
    'short_name': 'N Wells St',
    'types': ['route']},
   {'long_name': 'Near North Side',
    'short_name': 'Near North Side',
    'types': ['neighborhood', 'political']},
   {'long_name': 'Chicago',
    'short_name': 'Chicago',
    'types': ['locality', 'political']},
   {'long_name': 'Cook County',
    'short_name': 'Cook County',
    'types': ['administrative_area_level_2', 'political']},
   {'long_name': 'Illinois',
    'short_name': 'IL',
    'types': ['administrative_area_level_1', 'political']},
   {'long_name': 'United States',
    'short_name': 'US',
    'types': ['country', 'political']},
   {'long_name': '60610', 'short_name': '60610', 'types': ['postal_code']}],
  'formatted_address': '1547 N Wells St, Chicago, IL 60610, USA',
  'geometry': {'bounds': {'northeast': {'lat': 41.9105488,
     'lng': -87.63420149999999},
    'southwest': {'lat': 41.9104894, 'lng': -87.6345554}},
   'location': {'lat': 41.9105258, 'lng': -87.6343775},
   'location_type': 'ROOFTOP',
   'viewport': {'northeast': {'lat': 41.91186808029151,
     'lng': -87.63309861970849},
    'southwest': {'lat': 41.90917011970851, 'lng': -87.6357965802915}}},
  'place_id': 'ChIJDcIHTEHTD4gRv4ogAyUDBsE',
  'types': ['premise']}]

"geocode"를 .json으로 저장해서 저장된 형태 확인해보기¶

In [34]:

import json
print(json.dumps(geocode, indent=1))

[
 {
  "address_components": [
   {
    "long_name": "1547",
    "short_name": "1547",
    "types": [
     "street_number"
    ]
   },
   {
    "long_name": "North Wells Street",
    "short_name": "N Wells St",
    "types": [
     "route"
    ]
   },
   {
    "long_name": "Near North Side",
    "short_name": "Near North Side",
    "types": [
     "neighborhood",
     "political"
    ]
   },
   {
    "long_name": "Chicago",
    "short_name": "Chicago",
    "types": [
     "locality",
     "political"
    ]
   },
   {
    "long_name": "Cook County",
    "short_name": "Cook County",
    "types": [
     "administrative_area_level_2",
     "political"
    ]
   },
   {
    "long_name": "Illinois",
    "short_name": "IL",
    "types": [
     "administrative_area_level_1",
     "political"
    ]
   },
   {
    "long_name": "United States",
    "short_name": "US",
    "types": [
     "country",
     "political"
    ]
   },
   {
    "long_name": "60610",
    "short_name": "60610",
    "types": [
     "postal_code"
    ]
   }
  ],
  "formatted_address": "1547 N Wells St, Chicago, IL 60610, USA",
  "geometry": {
   "bounds": {
    "northeast": {
     "lat": 41.9105488,
     "lng": -87.63420149999999
    },
    "southwest": {
     "lat": 41.9104894,
     "lng": -87.6345554
    }
   },
   "location": {
    "lat": 41.9105258,
    "lng": -87.6343775
   },
   "location_type": "ROOFTOP",
   "viewport": {
    "northeast": {
     "lat": 41.91186808029151,
     "lng": -87.63309861970849
    },
    "southwest": {
     "lat": 41.90917011970851,
     "lng": -87.6357965802915
    }
   }
  },
  "place_id": "ChIJDcIHTEHTD4gRv4ogAyUDBsE",
  "types": [
   "premise"
  ]
 }
]

위도, 경도가 저장된 형태¶

In [35]:

lat = geocode[0].get('geometry')['location']['lat']
lng = geocode[0].get('geometry')['location']['lng']

lat, lng

Out[35]:

(41.9105258, -87.6343775)

Folium 사용해서 지도에 시각화 하기¶

In [36]:

import folium
import pandas as pd
import numpy as np
from tqdm import tqdm

In [38]:

# 표시할 주소 데이터 불러오기
df = pd.read_csv('../data/chicago_sandwich2.csv', index_col=0)
df.tail()

Out[38]:

	Cafe	Menu	Price	Address
Rank
46	Chickpea	Kufta	$8.	2018 W. Chicago Ave
47	The Goddess and Grocer	Debbie’s Egg Salad	$6.50	. 25 E. Delaware Pl
48	Zenwich	Beef Curry	$7.50	. 416 N. York St
49	Toni Patisserie	Le Végétarien	$8.75	. 65 E. Washington St
50	Phoebe’s Bakery	The Gatsby	$6.85	. 3351 N. Broadwa

In [52]:

for idx, row in df.iterrows():
    print(str(idx) + '.\t' + row['Address'])

1.	 2109 W. Chicago Ave
2.	 800 W. Randolph St
3.	. 445 N. Clark St
4.	. 914 Noyes St
5.	 825 W. Fulton Mkt
6.	. 100 E. Walton St
7.	 1639 S. Wabash Ave
8.	 2211 W. North Ave
9.	 3619 W. North Ave
10.	 3267 S. Halsted St
11.	 2537 N. Kedzie Blvd
12.	. Multiple location
13.	 3124 N. Broadwa
14.	 3455 N. Southport Ave
15.	 2657 N. Kedzie Ave
16.	. 1120 W. Grand Ave
17.	. 1141 S. Jefferson St
18.	. 333 E. Benton Pl
19.	. 1411 N. Wells St
20.	 1747 N. Damen Ave
21.	 3209 W. Irving Park Rd
22.	 Multiple location
23.	 5347 N. Clark St
24.	. 2954 W. Irving Park Rd
25.	. Multiple location
26.	. 191 Skokie Valley Rd
27.	. Multiple location
28.	. 1818 W. Wilson Ave
29.	 2517 W. Division St
30.	 218 W. Kinzie St
31.	. Multiple location
32.	. 1547 N. Wells St
33.	 415 N. Milwaukee Ave
34.	. 1840 N. Damen Ave
35.	 1220 W. Webster Ave
36.	 5357 N. Ashland Ave
37.	 1834 W. Montrose Ave
38.	 615 N. State St
39.	 Multiple location
40.	 241 N. York Rd
41.	. 1323 E. 57th St
42.	 655 Forest Ave
43.	 Hotel Lincol
44.	 100 S. Marion St
45.	. 26 E. Congress Pkwy
46.	 2018 W. Chicago Ave
47.	. 25 E. Delaware Pl
48.	. 416 N. York St
49.	. 65 E. Washington St
50.	. 3351 N. Broadwa

In [53]:

# 다음과 같은 경우 googlmaps로 찾을 수 없음
# 예외 처리 필요
df.loc[25, 'Address']

Out[53]:

'. Multiple location'

In [55]:

geocode = gmaps.geocode(address='. Multiple location')
geocode

Out[55]:

[]

Geocoding AIP를 통해 위경도 값 찾기¶

In [60]:

lat_list = []
lng_list = []

gmaps_key = 'Your API Key'
gmaps = googlemaps.Client(key=gmaps_key)

wrong_add = '. Multiple location'
for idx, row in tqdm(df.iterrows(), total=len(df.index)):
    if row['Address'] == wrong_add:
        lat = np.nan
        lng = np.nan
    else:
        geocode = gmaps.geocode(row['Address'] + ', Chicago')
        lat = geocode[0].get('geometry')['location']['lat']
        lng = geocode[0].get('geometry')['location']['lng']

    lat_list.append(lat)
    lng_list.append(lng)
    

100%|██████████| 50/50 [00:05<00:00,  9.04it/s]

Geocoding AIP로 찾은 위경도 값을 데이터 프레임에 추가¶

In [61]:

df['lat'] = lat_list
df['lng'] = lng_list

Folium을 사용하여 시각화¶

In [62]:

mapping = folium.Map(location=[lat_list[0], lng_list[0]], zoom_start=11)

In [63]:

for idx, row in df.iterrows():
    if np.isnan(row['lat']) or np.isnan(row['lng']):
        continue
    else:
        folium.Marker(location=[row['lat'], row['lng']], popup=row['Cafe']).add_to(mapping)

mapping

Out[63]:

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