Update app.py

app.py

@@ -13,7 +13,7 @@ from streamlit_folium import st_folium
 
 def load_polygon(filepath):
     return gpd.read_file(filepath)
-path='Z:/Shared/Axeria Shared/Pricing/Immopolis Pricing Review/DATA/'
+path=''
 # Polygon1 = load_polygon(path + 'risk_zones.shp')
 # Polygon2 = load_polygon(path + 'Flooding/n_inondable_01_01for_s.shp')
 # Polygon3 = load_polygon(path + 'ZUS/ZUS_FRM_BDA09_L93.shp')
@@ -32,93 +32,6 @@ if 'polygons'  in st.session_state:
     st.session_state.polygons["Polygon2"]['geometry'] = st.session_state.polygons["Polygon2"]['geometry'].to_crs(epsg=4326)
     st.session_state.polygons["Polygon3"]['geometry'] = st.session_state.polygons["Polygon3"]['geometry'].to_crs(epsg=4326)
 
-    #Polygon1['geometry'] = Polygon1['geometry'].to_crs(epsg=4326)
-    #Polygon2=load_polygon(path+'Flooding/n_inondable_01_01for_s.shp')
-    # Polygon1=load_polygon(path+'risk_zones.shp')
-    # Polygon1['geometry'] = Polygon1['geometry'].to_crs(epsg=4326)
-    # Polygon2=load_polygon(path+'Flooding/n_inondable_01_01for_s.shp')
-    # Polygon3=load_polygon(path+'ZUS/ZUS_FRM_BDA09_L93.shp')
-
-# # Function to plot an interactive histogram
-# # fig = px.histogram(polygon_gdf['poverty'], nbins=20)
-# # st.plotly_chart(fig)
-# fig = px.ecdf(polygon_gdf['poverty'])
-# fig.show()
-# # # #28% --> 5% of squares
-# # #
-# # #
-# fig = px.ecdf(polygon_gdf['densite'])
-#  # #9000 --> 5% of squares
-# fig.show()
-# #
-# #
-# #
-# # #Load geographical layers
-#
-
-# zus=gpd.read_file(path+'ZUS/ZUS_FRM_BDA09_L93.shp')
-# polygon_gdf = gpd.read_file(path+'Geo_metropole/Filosofi2017_carreaux_nivNaturel_met.shp')
-# polygon_gdf2 = gpd.read_file(path+'Filosofi2017_carreaux_1km_shp/Filosofi2017_carreaux_1km_met.shp')
-# polygon_gdf2['densite']=polygon_gdf2['Ind']
-# polygon_gdf2['poverty']=polygon_gdf2['Men_pauv']/polygon_gdf2['Men']
-# polygon_gdf['tmaille']=pd.to_numeric(polygon_gdf['tmaille'])
-# polygon_gdf['tmaillem2']=polygon_gdf['tmaille']**2
-# polygon_gdf['densite']=1000000*polygon_gdf['Ind']/polygon_gdf['tmaillem2']
-# polygon_gdf['poverty']=polygon_gdf['Men_pauv']/polygon_gdf['Men']
-
-
-# risk_zones2=polygon_gdf2[polygon_gdf2.poverty>=0.30]
-# risk_zones2=risk_zones2[risk_zones2.densite>=7000]
-#risk_zones2.to_file(filename=path+'risk_zones2.shp', driver='ESRI Shapefile')
-
-# risk_zones=gpd.read_file(filename=path+'risk_zones.shp')
-# flooding = gpd.read_file(path+'Flooding/n_inondable_01_01for_s.shp')
-#
-# #
-# #
-# # #FLooding zones
-#risk_zones=polygon_gdf[polygon_gdf.poverty>=0.28]
-# risk_zones=risk_zones[risk_zones.densite>=7000]
-#
-# risk_zones.to_file(filename=path+'risk_zones.shp', driver='ESRI Shapefile')
-#
-# # #
-# m =folium.Map(location = [48.885805,2.366191], zoom_start = 6)
-# folium.GeoJson(Polygon2[Polygon2.index<1000],color='blue').add_to(m)
-#folium.CircleMarker([48.885805, 2.366191],radius=1,color='red').add_to(m)
-# folium.GeoJson(flooding[flo,color='yellow').add_to(m)
-# #folium.GeoJson(risk_zones2,color='orange').add_to(m)
-# folium.GeoJson(zus).add_to(m)
-# #
-# #
-# # # m.save(path+"map2.html")
-# # # webbrowser.open_new_tab(path+"map2.html")
-# # #
-# # #
-# policies = pd.read_pickle(path+"DB_immoplus.pkl")
-# geometry = [Point(xy) for xy in zip(policies['longitude'], policies['latitude'])]
-# policies_geo = gpd.GeoDataFrame(policies, geometry=geometry,crs="EPSG:4326")
-# #
-# large_claims=policies_geo[policies_geo.Charge>20000]
-# large_claims=large_claims.dropna(subset=['latitude'])
-# # #
-# for arr in large_claims["geometry"]:
-#      lat=arr.y
-#      lon=arr.x
-#      folium.CircleMarker([lat, lon],radius=1,color='red').add_to(m)
-# m.save(path+"map2.html")
-# webbrowser.open_new_tab(path+"map2.html")
-#
-#
-# sum(risk_zones['tmaille'])/sum(polygon_gdf['tmaille'])*100
-# sum(risk_zones['Ind'])/sum(polygon_gdf['Ind'])*100
-
-# #
-# #
-# #
-# # flooding["zone_inond_freq"]=1
-# # zus['flag_ZUS']=1
-# # Function to get address suggestions from the Autocomplete API
 def create_geodataframe(longitude, latitude):
     geometry = [Point(longitude, latitude)]
     gdf = gpd.GeoDataFrame(geometry=geometry, crs="EPSG:4326")