Update app.py

app.py

@@ -2,16 +2,16 @@ import requests
 from bs4 import BeautifulSoup
 import pandas as pd
 import folium
-from folium.plugins import MarkerCluster
+from folium.plugins import MarkerCluster, HeatMap
 import plotly.graph_objects as go
-import plotly.express as px  # Add this import
+import plotly.express as px
 from geopy.geocoders import Nominatim
 import re
 import streamlit as st
 
 # Streamlit title and description
 st.title("米其林餐廳指南爬蟲")
-st.write("Extract restaurant data, visualize with a pie chart and bar chart, and display locations on a map.")
+st.write("Extract restaurant data, visualize with charts, and display locations on maps.")
 
 # Read data from Google Sheets
 sheet_id = "1xUfnD1WCF5ldqECI8YXIko1gCpaDDCwTztL17kjI42U"
@@ -58,7 +58,6 @@ def fetch_data():
             address = None
             region = "Unknown"
         
-        # Try to extract phone number
         try:
             phone = soup.find("a", {"data-event": "CTA_tel"}).get("href").replace("tel:", "")
         except AttributeError:
@@ -158,8 +157,8 @@ if st.button("爬取餐廳資料"):
     # Display a map using Folium
     st.subheader("Restaurant Locations Map")
 
-    # Create map centered around Tainan
-    m = folium.Map(location=[23.0, 120.2], zoom_start=12)
+    # Create map centered around the mean latitude and longitude
+    m = folium.Map(location=[df['Latitude'].mean(), df['Longitude'].mean()], zoom_start=10)
 
     # Add marker cluster to the map
     marker_cluster = MarkerCluster().add_to(m)
@@ -173,3 +172,37 @@ if st.button("爬取餐廳資料"):
 
     # Display the map in Streamlit
     st.components.v1.html(m._repr_html_(), height=600)
+
+    # New section for heatmap
+    st.header("餐廳分布熱力圖")
+
+    # Prepare data for heatmap
+    heat_data = [[row['Latitude'], row['Longitude']] for index, row in df.iterrows() if pd.notnull(row['Latitude']) and pd.notnull(row['Longitude'])]
+
+    # Create a new map for the heatmap
+    heatmap = folium.Map(location=[df['Latitude'].mean(), df['Longitude'].mean()], zoom_start=10)
+
+    # Add heatmap to the map
+    HeatMap(heat_data).add_to(heatmap)
+
+    # Display the heatmap in Streamlit
+    st.components.v1.html(heatmap._repr_html_(), height=600)
+
+    # Regional restaurant count analysis
+    st.header("各區域餐廳數量分析")
+
+    # Create bar chart for restaurant count by region using Plotly Express
+    fig_bar = px.bar(region_group, x='Region', y='Count', 
+                     title="各區域餐廳數量比較", 
+                     color='Count',
+                     color_continuous_scale=px.colors.sequential.Viridis)
+    st.plotly_chart(fig_bar)
+
+    # Create a scatter mapbox for individual restaurant locations
+    fig_scatter = px.scatter_mapbox(df, lat="Latitude", lon="Longitude", 
+                                    hover_name="Store Name", 
+                                    hover_data=["Address", "Phone"],
+                                    zoom=10, height=600,
+                                    title="餐廳位置分布圖")
+    fig_scatter.update_layout(mapbox_style="open-street-map")
+    st.plotly_chart(fig_scatter)