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import json

# 한국의 지도 데이터 참조
# @ https://github.com/southkorea/southkorea-maps
geo_path = 'skorea_municipalities_geo_simple.json'
geo_str = json.load(open(geo_path, encoding='utf-8'))

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from pyprnt import prnt

prnt(geo_str, truncate=True, width=80)

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import folium

# Folium 공식문서 @ https://goo.gl/5UgneX
seoul_map = folium.Map(location=, zoom_start=, tiles=) 

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# Choropleth map @ https://goo.gl/yrTRHU
seoul_map.choropleth(geo_data = geo_str,
               data = gu_df['살인'],
               columns = [gu_df.index, gu_df['살인']],
               fill_color = 'PuRd',
               key_on = 'feature.id')

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def re_range(x, oldMin, old_max, new_min, new_max):
    return (x - old_min)*(new_max - new_min) /
           (old_max - old_min) + new_min 

df['점수'] = re_range(df['검거율'], min(df['검거율']),
                     max(df['검거율']), 1, 100)

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import googlemaps

gmaps = googlemaps.Client(key='your-api-key')
gangnam_police_map = gmaps.geocode('서울강남경찰서', language="ko")

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[{'address_components': [{'long_name': '１１',
    'short_name': '１１',
    'types': ['premise']},
   {'long_name': '테헤란로114길',
    'short_name': '테헤란로114길',
    'types': ['political', 'sublocality', 'sublocality_level_4']},
   {'long_name': '강남구',
    'short_name': '강남구',
    'types': ['political', 'sublocality', 'sublocality_level_1']},
   {'long_name': '서울특별시',
    'short_name': '서울특별시',
    'types': ['administrative_area_level_1', 'political']},
   {'long_name': '대한민국',
    'short_name': 'KR',
    'types': ['country', 'political']},
   {'long_name': '06175', 'short_name': '06175', 'types': ['postal_code']}],
  'formatted_address': '대한민국 서울특별시 강남구 테헤란로114길 11',
  'geometry': {'location': {'lat': 37.5094352, 'lng': 127.0669578},
   'location_type': 'ROOFTOP',
   'viewport': {'northeast': {'lat': 37.5107841802915,
     'lng': 127.0683067802915},
    'southwest': {'lat': 37.5080862197085, 'lng': 127.0656088197085}}},
  'partial_match': True,
  'place_id': 'ChIJcbaB0UakfDURoyy8orQOWFg',
  'plus_code': {'compound_code': 'G358+QQ 대한민국 서울특별시',
   'global_code': '8Q99G358+QQ'},
  'types': ['establishment', 'point_of_interest', 'police']}]

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lat = []
lng = []

for name in df['경찰서']:
    police_map = gmaps.geocode(name, language='ko')
    police_loc = seoul_police_map[0].get('geometry')
    lat.append(police_loc['location']['lat'])
    lng.append(police_loc['location']['lng'])

df['lat'] = lat
df['lng'] = lng

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police_map = folium.Map(location=, zoom_start=)

for n in df.index:
    folium.CircleMarker([df.at[n, 'lat'], df.at[n, 'lng']], 
                        radius=df.at[n, '점수']*0.5, # meter 단위
                        color='#3186cc', fill=True, 
                        fill_color='#3186cc').add_to(map)

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police_map = folium.Map(location=, zoom_start=)

police_map.choropleth(geo_data = geo_str,
                      data = crime_ratio['전체발생비율'],
                      columns = [crime_ratio.index,
                                 crime_ratio['전체발생비율']],
                      fill_color = 'PuRd',
                      key_on = 'feature.id')

for n in df.index:
    folium.CircleMarker([df.at[n, 'lat'], df.at[n, 'lng']], 
                        radius=df.at[n, '점수']*0.7,
                        color='#3186cc', fill=True, fill_color='#3186cc').add_to(police_map)

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df.to_csv('processed_data.csv', encoding='utf-8')

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from pandas import ExcelWriter

writer = ExcelWriter('file_name.xlsx')
df.to_excel(writer)
writer.save()

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folium_map.save('folium_map.html')

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geo_path = 'skorea-2018-municipalities-geo.json'
geo_str = json.load(open(geo_path, encoding='utf-8'))

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in_seoul = []

for feature in geo_str['features']:
    if feature['properties']['code'].startswith('11'):
        in_seoul.append(feature)