class CrimeMap:
def __init__(self):
self.dr = DataReader()
def hook(self):
self.crate_seoul_crime_map()
def crate_seoul_crime_map(self):
self.dr.context = './saved_data/'
self.dr.fname = 'police_norm.csv'
pn = self.dr.csv_to_dframe()
# print("===============")
# print(pn)
self.dr.context = './data'
self.dr.fname = '/geo_simple.json'
seoul_geo = self.dr.json_load()
m = folium.Map(location=[37.5502, 126.982],
zoom_start=12,
title='Stamen Toner')
m.choropleth(
geo_data=seoul_geo,
name='choropleth',
data=tuple(zip(pn['구별'], pn['범죄'])),
# columns=['State', 'Unemployment'],
key_on='feature.id',
fill_color='PuRd',
fill_opacity=0.7,
line_opacity=0.2,
legend_name='Crime Rate (%)')
m.save('./saved_data/Seoul_Crime.html')
class CrimeMap:
def __init__(self):
self.dr = DataReader()
def hook(self):
self.create_seoul_crime_map()
def create_seoul_crime_map(self):
self.dr.context = './saved_data/'
self.dr.fname = 'police_norm.csv'
police_norm = self.dr.csv_to_dframe()
# print(pn)
self.dr.context = './data/'
self.dr.fname = 'geo_simple.json'
seoul_geo = self.dr.json_load()
self.dr.context = './data/'
self.dr.fname = 'crime_in_seoul.csv'
crime = self.dr.csv_to_dframe()
station_names = []
for name in crime['관서명']:
station_names.append('서울' + str(name[:-1] + '경찰서'))
station_addrs = []
station_lats = [] # 위도
station_lngs = [] # 경도
gmaps = self.dr.create_gmaps()
for name in station_names:
t = gmaps.geocode(name, language='ko')
station_addrs.append(t[0].get('formatted_address'))
t_loc = t[0].get('geometry')
station_lats.append(t_loc['location']['lat'])
station_lngs.append(t_loc['location']['lng'])
# print(name + '---------> ' + t[0].get('formatted_address'))
# 기존 코드
self.dr.context = './data/'
self.dr.fname = 'police_position.csv'
police_pos = self.dr.csv_to_dframe()
police_pos['lat'] = station_lats
police_pos['lng'] = station_lngs
# print(police_pos)
col = ['살인 검거', '강도 검거', '강간 검거', '절도 검거', '폭력 검거']
tmp = police_pos[col] / police_pos[col].max()
police_pos['검거'] = np.sum(tmp, axis=1)
self.dr.fname = 'geo_simple.json'
m = folium.Map(location=[37.5502, 126.982],
zoom_start=12,
title='Stamen Toner')
m.choropleth(geo_data=seoul_geo,
name='choropleth',
data=tuple(zip(police_norm['구별'], police_norm['범죄'])),
key_on='feature.id',
fill_color='PuRd',
fill_opacity=0.7,
line_opacity=0.2,
legend_name='CRIME RATE (%)')
for i in police_pos.index:
folium.CircleMarker([police_pos['lat'][i], police_pos['lng'][i]],
radius=police_pos['검거'][i] * 10,
fill_color='#0a0a32').add_to(m)
m.save('./saved_data/Seoul_Crime_Map.html')
class CrimeMap:
def __init__(self):
self.dr = DataReader()
def hook(self):
self.create_seoul_crime_map()
def create_seoul_crime_map(self):
#생성한 객체의 변수에 값 할당
self.dr.context = "./saved_data/"
self.dr.fname = "police_nomr.csv"
police = self.dr.csv_dframe()
print(police)
self.dr.context = "./data/"
self.dr.fname = 'geo_simple.json'
seoul_geo = self.dr.json_load()
self.dr.context = "./data/"
self.dr.fname = "crime_in_seoul.csv"
crime = self.dr.csv_dframe()
station_names = []
for name in crime["관서명"]:
station_names.append("서울" + str(name[:-1] + "경찰서"))
station_addrs = []
station_lats = [] # 위도
station_lngs = [] # 경도
gmaps = self.dr.create_gmaps()
for name in station_names:
t = gmaps.geocode(name, language="ko")
station_addrs.append(t[0].get("formatted_address"))
t_loc = t[0].get("geometry")
# 구글의 컬럼 명 그대로lat, lng -> api
station_lats.append(t_loc["location"]["lat"])
station_lngs.append(t_loc["location"]["lng"])
print(name + "--------------->" + t[0].get("formatted_address"))
# 기존 코드
self.dr.context = './data/'
self.dr.fname = 'police_position.csv'
police_pos = self.dr.csv_dframe()
police_pos['lat'] = station_lats
police_pos['lng'] = station_lngs
print(police_pos)
col = ['살인 검거', '강도 검거', '강간 검거', '절도 검거', ' 폭력 검거']
tmp = police_pos[col] / police_pos[col].max
police_pos['검거'] = np.sum(tmp, axis=1)
self.dr.fname = 'geo_simple.json'
m = folium.Map(location=[37.5902, 126.982],
zoom_start=12,
title='Stamen Toner')
# 속성값
m.choropleth(
geo_data=seoul_geo,
name="choropleth",
data=tuple(zip(police['구별'], police['범죄'])),
#columns=["State", "Unemployment"],
key_on="feature.id",
fill_color="PuRd",
fill_opacity=0.7,
line_opacity=0.2,
lengend_name="CRIME RATE (%)")
for i in police_pos.index:
#동그란 이미지 추가
folium.CircleMarker([police_pos['lat'][i], police_pos['lng'][i]],
radius=police_pos['검거'][i] * 10,
fill_color='#0a0a32').add_to(m)
#저장하기
m.save('./saved_data/Seoul_Crime_Map.html')
class CrimeMap:
def __init__(self):
self.dr = DataReader()
def hook(self):
self.create_seoul_crime_map()
def create_seoul_crime_map(self):
self.dr.context = './saved_data/'
self.dr.fname = 'police_norm.csv'
police_norm = self.dr.csv_to_dframe()
# print(pn) #dataframe으로 제대로 불러들였는지 확인하기 위함
self.dr.context = './data/'
self.dr.fname = 'geo_simple.json'
seoul_geo = self.dr.json_load()
#폴리움 코딩은 템플릿화되어있으므로 가져와서 붙이고 데이터만 한국지도에 맞게 수정하면 됨
self.dr.context = './data/'
self.dr.fname = 'crime_in_seoul.csv'
crime = self.dr.csv_to_dframe()
station_names = []
for name in crime['관서명']:
station_names.append('서울' + str(name[:-1] + '경찰서'))
station_addrs = []
station_lats = [] #위도
station_lngs = [] #경도
gmaps = self.dr.create_gmaps()
for name in station_names:
t = gmaps.geocode(name, language='ko')
station_addrs.append(t[0].get('formatted_address'))
t_loc = t[0].get('geometry')
station_lats.append(
t_loc['location']['lat']
) #formatted_address, lat, lng, location 구글맵 내부에 기재되어있는 정보들이므로 그대로 사용해야함
station_lngs.append(t_loc['location']['lng'])
# print(name + '--------> '+t[0].get('formatted_address')) # 구글키가 작동하는지 확인
# 기존 코드
self.dr.context = './data/'
self.dr.fname = 'police_position.csv'
police_pos = self.dr.csv_to_dframe()
police_pos['lat'] = station_lats
police_pos['lng'] = station_lngs
# print(police_pos) # 제대로 불러읽어들였는지 확인
col = ['살인 검거', '강도 검거', '강간 검거', '절도 검거', '폭력 검거']
tmp = police_pos[col] / police_pos[col].max
police_pos['검거'] = np.sum(tmp, axis=1)
self.dr.fname = 'geo_simple.json'
m = folium.Map(location=[37.5502, 126.982],
zoom_start=12,
title='stamen Toner') # 한국 위도, 경도 설정 및 지도 스타일 설정
m.choropleth(
geo_data=seoul_geo,
name='choropleth',
# json에서의 id와 police_norm에 있는 스키마(변수명, 컬럼)의 내용 값을 일치시켜야 하므로 pn안에서 [구별] [범죄]를 체크해야함
# 폴리움 데이터에서 state, unemployment를 컬럼으로 가지도록 한 것과 같은 패턴
data=tuple(zip(police_norm['구별'], police_norm['범죄'])),
key_on='feature.id',
fill_color='PuRd',
fill_opacity=0.7,
line_opacity=0.2,
legend_name='Crime Rate (%)')
# 괄호안의 파라메터들에 관해 파고들어갈 필요까지는 없음
# 기존 지도에 검거율 추가
for i in police_pos.index:
folium.CircleMarker([police_pos['lat'][i], police_pos['lng'][i]],
radius=police_pos['검거'][i] * 10,
fill_color='#0a0a32').add_to(m)
m.save('./saved_data/Seoul_Crime.html')
