Update app.py

app.py

@@ -1,146 +1,70 @@
 import pandas as pd
 import streamlit as st
 import plotly.graph_objects as go
+from geopy.distance import geodesic as GD
 
 df = pd.read_excel("result.xlsx")
-def get_lat_lon(row):
-    row = eval(row['result_dadata'])[0]
-    lat = row['geo_lat']
-    lon = row['geo_lon']
-    adress = row['result']
 
-    return lat, lon, adress
+df['lon'] = [eval(x)[0]['geo_lon'] for x in df['result_dadata']]
+df['lat'] = [eval(x)[0]['geo_lat'] for x in df['result_dadata']]
+df['address'] = [eval(x)[0]['result'] for x in df['result_dadata']]
+
+target_coordinates = (55.7307614,37.6299091)
+
+for i in df.index:
+    lat = df.loc[i,'lat'] 
+    lon = df.loc[i,'lon'] 
+    result = GD((lat,lon),target_coordinates).km
+    df.loc[i,'distance'] = result
+    print(result)
+    if result<=2:
+        df.loc[i,'2km_from_target'] = 1
+        df.loc[i,'3km_from_target'] = 1
+        df.loc[i,'5km_from_target'] = 1
+        df.loc[i,'more_than_5km_from_target'] = 0
+    if result<=3:
+        df.loc[i,'2km_from_target'] = 0
+        df.loc[i,'3km_from_target'] = 1
+        df.loc[i,'5km_from_target'] = 1
+        df.loc[i,'more_than_5km_from_target'] = 0
+    if result<=5:
+        df.loc[i,'2km_from_target'] = 0
+        df.loc[i,'3km_from_target'] = 0
+        df.loc[i,'5km_from_target'] = 1
+        df.loc[i,'more_than_5km_from_target'] = 0
+    else:
+        df.loc[i,'2km_from_target'] = 0
+        df.loc[i,'3km_from_target'] = 0
+        df.loc[i,'5km_from_target'] = 0
+        df.loc[i,'more_than_5km_from_target'] = 1
 
 def get_colors(row):
-    if row > 10000:
+    if row >= 10:
+        return 'black'
+    elif row <= 10 and row>5:
+        return 'grey'
+    elif row<=5 and row>3:
         return 'red'
-    elif row <= 10000 and row > 4000:
+    elif row<=3 and row>2:
         return 'blue'
-    elif row <= 4000 and row > 2000:
-        return 'yellow'
-    # elif row <= 2000 and row > 1000:
-    #     return 'green'
-    # elif row <= 200 and row > 100:
-    #     return 'purple'
-    # elif row <= 100 and row > 30:
-    #     return 'orange'
-    else:
-        return 'black'
+    elif row<=2:
+        return 'green'
 
-df[['lat', 'lon', 'adress']] = df.apply(get_lat_lon, axis=1, result_type='expand')
-viz_df = df[['lpu_name','lat', 'lon', 'adress', 'MT_SUM_RUR']].copy()
-viz_df['MT_SUM_RUR'] = viz_df['MT_SUM_RUR']/1000
+df['colors'] = df['distance'].apply(get_colors)
 
+viz_df = viz_df = df[['lpu_name','lat', 'lon', 'address', 'distance','colors']].copy()
 viz_df[['lat','lon']] = viz_df[['lat','lon']].astype(float)
-viz_df['colors'] = viz_df['MT_SUM_RUR'].apply(get_colors)
-
-text_series ="Название клиники: "+ viz_df['lpu_name'] + "<br>" + "Адрес: " + viz_df["adress"] + "<br>" + "Сумма:" + viz_df['MT_SUM_RUR'].astype(str) + " тыс.руб"
-fig_bubbles_coords = go.Figure(data=go.Scattermapbox(
-    lat=viz_df['lat'],
-    lon=viz_df['lon'],
-    mode='markers',
-    marker=go.scattermapbox.Marker(
-        size=viz_df['MT_SUM_RUR'],
-        color='red',
-        sizemode='area',
-        sizeref=5,
-        opacity=0.6
-    ),
-    text=text_series,
-))
-
-fig_bubbles_coords.update_layout(
-    mapbox_style='open-street-map',
-    autosize=True,
-    hovermode='closest',
-    showlegend=False,
-    mapbox=dict(
-        center=dict(lat=viz_df['lat'].mean(), lon=viz_df['lon'].mean()),
-        zoom=9
-    ),
-    width=900,
-    height=900
-)
-
-fig_bubbles = go.Figure(data=go.Scattermapbox(
-    lat=viz_df['lat'],
-    lon=viz_df['lon'],
-    mode='markers',
-    marker=go.scattermapbox.Marker(
-        size=viz_df['MT_SUM_RUR'],
-        color='red',
-        sizemode='area',
-        sizeref=5,
-        opacity=0.6,
-    ),
-    customdata=text_series,
-))
-
-fig_bubbles.update_layout(
-    mapbox_style='open-street-map',
-    autosize=True,
-    hovermode='closest',
-    showlegend=False,
-    mapbox=dict(
-        center=dict(lat=viz_df['lat'].mean(), lon=viz_df['lon'].mean()),
-        zoom=9
-    ),
-    width=900,
-    height=900
-)
-
-fig_bubbles.update_traces(hovertemplate='<b>%{customdata}</b>')
-
-fig_heatbar = go.Figure(data=go.Scattermapbox(
-    lat=viz_df['lat'],
-    lon=viz_df['lon'],
-    mode='markers',
-    marker=go.scattermapbox.Marker(
-        color=viz_df['MT_SUM_RUR'],
-        sizemode='area',
-        sizeref=5,
-        opacity=1,
-        colorscale='rdylbu',  # Градиент цветов от светло-синего до темно-синего
-        colorbar=dict(title='MT_SUM_RUR')
-    ),
-    customdata=text_series,
-))
-
-fig_heatbar.update_layout(
-    mapbox_style='open-street-map',
-    autosize=True,
-    hovermode='closest',
-    showlegend=False,
-    mapbox=dict(
-        center=dict(lat=viz_df['lat'].mean(), lon=viz_df['lon'].mean()),
-        zoom=9
-    ),
-    width=900,
-    height=900
-)
-
-fig_heatbar.update_traces(hovertemplate='<b>%{customdata}</b>')
-
-dct_colors = {'red':'больше 10000',
-              'blue':'10000-4000',
-              'yellow':'4000-2000',
-            #   'green':'400-200',
-            #   'purple':'200-100',
-            #   'orange':'100-30',
-              'black':'меньше 2000'}
-colors = ['red',
-          'blue', 
-          'yellow', 
-        #   'green',
-        #   'purple',
-        #   'orange',
-          'black']
 
+dct_colors = {'black':'больше 10',
+              'grey':'5-10',
+              'red':'3-5',
+              'blue':'2-3',
+              'green':'меньше 2'}
+colors = ['black', 'grey', 'red','blue','green']
 fig_colored = go.Figure()
-
 for color in colors:
     temp_df = viz_df[viz_df['colors'] == color]
-    text_series_temp = "Название клиники: "+ temp_df['lpu_name'] + "<br>" + "Адрес: " + temp_df["adress"] + "<br>" + "Сумма: " + temp_df['MT_SUM_RUR'].astype(str) + " тыс.руб"
+    text_series_temp = "Название клиники: "+ temp_df['lpu_name'] + "<br>" + "Адрес: " + temp_df["address"] + "<br>" + "Расстояние от  Валовая 20: " + temp_df['distance'].astype(str)
     fig_colored.add_trace(go.Scattermapbox(
         lat=temp_df['lat'],
         lon=temp_df['lon'],
@@ -155,26 +79,20 @@ for color in colors:
         customdata=text_series_temp,
     ))
 
-
 fig_colored.update_layout(
     mapbox_style='open-street-map',
     autosize=True,
     hovermode='closest',
     showlegend=True,
     mapbox=dict(
-        center=dict(lat=viz_df['lat'].mean(), lon=viz_df['lon'].mean()),
+        center=dict(lat=target_coordinates[0], lon=target_coordinates[1]),
         zoom=9
     ),
     width=900,
     height=900
 )
-fig_colored.update_traces(hovertemplate='<b>%{customdata}</b>')
 
-viz_df = viz_df.rename(columns={"MT_SUM_RUR":"Сумма"})
 
-st.dataframe(data=viz_df[['lpu_name', 'Сумма', 'adress']])
-st.plotly_chart(fig_bubbles)
-st.plotly_chart(fig_heatbar)
+fig_colored.update_traces(hovertemplate='<b>%{customdata}</b>')
 st.plotly_chart(fig_colored)
-
-# %%
+st.dataframe(data=viz_df[['lpu_name', 'distance', 'address']])