Update app.py

app.py

@@ -1,4 +1,3 @@
-# file_path: app.py
 import streamlit as st
 import requests
 from bs4 import BeautifulSoup
@@ -140,12 +139,13 @@ def upload_to_google_sheets(df):
     worksheet.update([df1.columns.values.tolist()] + df1.values.tolist())
     return "資料已成功上傳到 Google Sheet！"
 
+# Streamlit app implementation
 if mode == "資料爬取":
     st.header("爬取台南飯店資料")
     if st.button("開始爬取"):
         df = scrape_booking_hotel()
         if not df.empty:
-            st.dataframe(df)  # 顯示數據
+            st.dataframe(df)
             df.to_csv('booking_hotels_tainan.csv', index=False, encoding='utf-8-sig')
             st.success("資料爬取成功，已儲存至 booking_hotels_tainan.csv")
         else:
@@ -155,15 +155,13 @@ elif mode == "資料視覺化":
     st.header("分析與視覺化")
     try:
         df = pd.read_csv('booking_hotels_tainan.csv', encoding='utf-8-sig')
-        df['價格'] = pd.to_numeric(df['價格'], errors='coerce')  # 無效值轉為 NaN
-        df['評分'] = df['評分'].apply(clean_rating)  # 清理評分
-        df = df.dropna(subset=['價格'])  # 移除價格為 NaN 的行
+        df['價格'] = pd.to_numeric(df['價格'], errors='coerce')
+        df['評分'] = df['評分'].apply(clean_rating)
+        df = df.dropna(subset=['價格'])
 
-        # 顯示數據摘要
         st.write(f"有效數據行數：{len(df)}")
         st.write(f"價格缺失值數量：{df['價格'].isna().sum()}")
 
-        # 繪製圖表
         scatter_fig = create_price_rating_scatter(df)
         if scatter_fig:
             st.plotly_chart(scatter_fig)
@@ -180,4 +178,4 @@ elif mode == "上傳至 Google Sheet":
         result = upload_to_google_sheets(df)
         st.success(result)
     except Exception as e:
-        st.error(f"上傳資料時發生錯誤：{e}")
+        st.error(f"上傳資料時發生錯誤：{e}")