Update app.py

app.py

@@ -18,6 +18,14 @@ st.title("🐣MOMO 🆚 PCHOME 商品搜索和價格分析👁️‍🗨️")
 search_keyword = st.text_input("請輸入要搜索的關鍵字: ", "筆電")
 page_number = st.number_input("請輸入要搜索的頁數: ", min_value=1, max_value=100, value=1, step=1)
 
+# 在Pytrends Analysis部分之前添加日期選擇器
+st.subheader("Google Trends 分析時間範圍")
+default_end_date = datetime.now().date()
+default_start_date = default_end_date - timedelta(days=7)
+
+start_date = st.date_input("開始日期", value=default_start_date)
+end_date = st.date_input("結束日期", value=default_end_date)
+
 # Create a button to start the scraping process
 if st.button("開始搜索"):
     start_time = time.time()
@@ -171,46 +179,53 @@ if st.button("開始搜索"):
     end_time = time.time()
     st.write(f"Execution time: {end_time - start_time:.2f} seconds")
 
+if start_date <= end_date:
     # Pytrends Analysis
     pytrend = TrendReq(hl="zh-TW", tz=-480)
-    keywords = search_keyword #20240204換關鍵字
+    keywords = search_keyword
+    timeframe = f"{start_date} {end_date}"
     pytrend.build_payload(
-        kw_list=keywords,
+        kw_list=[keywords],
         cat=3,
-        timeframe="2024-06-18 2024-06-24", 
+        timeframe=timeframe, 
         geo="TW",
         gprop="")
     
     df = pytrend.interest_over_time()
-    if "isPartial" in df.columns:
-        df = df.drop(["isPartial"], axis=1)
-    
-    # Plotting Trend Data
-    fig, ax = plt.subplots(figsize=(12, 8), dpi=80)
-    ax.plot(df.index, df[keywords[0]], label=keywords[0], lw=3.0, marker='o', markersize=8, color='#4285F4', linestyle='-')
-    
-    ax.set_title("Interest Over Time for "+search_keyword, fontsize=20, fontweight='bold', color='#4285F4')
-    ax.set_xlabel("時間", fontsize=14, fontweight='bold', color='#4285F4')
-    ax.set_ylabel("熱搜度", fontsize=14, fontweight='bold', color='#4285F4')
-    ax.legend()
-    ax.grid(True, linestyle='--', alpha=0.6)
+    if not df.empty:
+        if "isPartial" in df.columns:
+            df = df.drop(["isPartial"], axis=1)
 
-    # Removing spines
-    ax.spines['top'].set_visible(False)
-    ax.spines['right'].set_visible(False)
+        # Plotting Trend Data
+        fig, ax = plt.subplots(figsize=(12, 8), dpi=80)
+        ax.plot(df.index, df[keywords], label=keywords, lw=3.0, marker='o', markersize=8, color='#4285F4', linestyle='-')
+        
+        ax.set_title(f"Interest Over Time for {search_keyword}", fontsize=20, fontweight='bold', color='#4285F4')
+        ax.set_xlabel("時間", fontsize=14, fontweight='bold', color='#4285F4')
+        ax.set_ylabel("熱搜度", fontsize=14, fontweight='bold', color='#4285F4')
+        ax.legend()
+        ax.grid(True, linestyle='--', alpha=0.6)
 
-    # Customize tick colors
-    ax.tick_params(axis='x', colors='#4285F4')
-    ax.tick_params(axis='y', colors='#4285F4')
+        # Removing spines
+        ax.spines['top'].set_visible(False)
+        ax.spines['right'].set_visible(False)
 
-    # Customize legend
-    legend = ax.legend()
-    legend.get_frame().set_alpha(0.5)
-    legend.get_lines()[0].set_linestyle('-')
+        # Customize tick colors
+        ax.tick_params(axis='x', colors='#4285F4')
+        ax.tick_params(axis='y', colors='#4285F4')
 
-    # Display the plot
-    plt.tight_layout()
-    st.pyplot(fig)
+        # Customize legend
+        legend = ax.legend()
+        legend.get_frame().set_alpha(0.5)
+        legend.get_lines()[0].set_linestyle('-')
 
-    # Print out statistics
-    st.write(df.describe())
+        # Display the plot
+        plt.tight_layout()
+        st.pyplot(fig)
+
+        # Print out statistics
+        st.write(df.describe())
+    else:
+        st.write("在選定的時間範圍內沒有數據。請嘗試不同的日期範圍或關鍵字。")
+else:
+    st.error("錯誤：結束日期必須在開始日期之後。")