Update app.py

app.py

@@ -9,7 +9,7 @@ import networkx as nx
 from datetime import datetime, timedelta
 import gradio as gr
 
-# 中文顯示設置 (只需設置一次)
+# 中文顯示設置
 plt.rcParams['font.sans-serif'] = ['Microsoft JhengHei', 'Arial Unicode MS', 'SimHei', 'DejaVu Sans']
 plt.rcParams['axes.unicode_minus'] = False
 
@@ -60,7 +60,7 @@ def run_analysis():
         # 統計每日情緒
         summary = all_df.groupby(['候選人', '情緒']).size().unstack(fill_value=0)
         summary['總貼文'] = summary.sum(axis=1)
-        summary['正面比率'] = summary.get('positive', 0) / summary['總貼文'].replace(0, 1)  # Avoid division by zero
+        summary['正面比率'] = summary.get('positive', 0) / summary['總貼文'].replace(0, 1)
         summary['負面比率'] = summary.get('negative', 0) / summary['總貼文'].replace(0, 1)
 
         # 更新歷史資料
@@ -92,7 +92,7 @@ def run_analysis():
         plt.legend()
         img_b64_trend = plot_to_base64(fig2)
 
-        # 3. 社群情感趨勢 (使用實際資料而非隨機)
+        # 3. 社群情感趨勢
         sentiment_trend = all_df.groupby([pd.Grouper(key='日期', freq='D'), '情緒']).size().unstack(fill_value=0)
         sentiment_trend = sentiment_trend.div(sentiment_trend.sum(axis=1), axis=0).fillna(0)
         fig3 = plt.figure(figsize=(8, 5))
@@ -105,7 +105,7 @@ def run_analysis():
         plt.legend()
         img_social_sentiment = plot_to_base64(fig3)
 
-        # 4. 各平台表現 (模擬平台數據)
+        # 4. 各平台表現
         platforms = ["X", "Facebook", "Instagram", "PTT", "Line"]
         platform_counts = pd.Series({p: random.randint(10, 100) for p in platforms})
         fig4 = plt.figure(figsize=(8, 5))