Update app.py

app.py

@@ -23,8 +23,8 @@ st.markdown("### Group Members")
 st.markdown("""
 - Zhang, Yuanyuan [yz133@illinois.edu](mailto:yz133@illinois.edu)
 - Peng, Yongzhen [ypeng16@illinois.edu](mailto:ypeng16@illinois.edu)
-- Wei, Jiahe[wei51@illinois.edu](mailto:wei51@illinois.edu)
-- Wang, Tiannuo[tiannuo3@illinois.edu](mailto:tiannuo3@illinois.edu)
+- Wei, Jiahe [wei51@illinois.edu](mailto:wei51@illinois.edu)
+- Wang, Tiannuo [tiannuo3@illinois.edu](mailto:tiannuo3@illinois.edu)
 """)
 
 
@@ -55,7 +55,7 @@ st.markdown(
 
 
 
-# 获取股票数据
+
 end_date = datetime.now().strftime('%Y-%m-%d')
 start_date = "2022-01-01"
 
@@ -77,44 +77,44 @@ company_names = {
 tickers = list(company_names.keys())
 stock_data = yf.download(tickers, start=start_date, end=end_date)
 
-# 处理 MultiIndex 数据
+
 if isinstance(stock_data.columns, pd.MultiIndex):
     stock_data.columns = ['_'.join(col).strip() for col in stock_data.columns]
 
 stock_data.reset_index(inplace=True)
 
-# 添加月度聚合数据
+
 stock_data["Month"] = stock_data["Date"].dt.to_period("M")
 monthly_data = stock_data.groupby("Month").mean()
 
-# Streamlit 应用
+
 st.title("Stock Dashboard")
 
-# 用户选择
+
 selected_stock = st.selectbox("Select a Stock:", options=company_names.keys())
 metric1 = st.selectbox("Select Metric 1:", options=["Open", "High", "Low", "Close", "Adj Close", "Volume"])
 metric2 = st.selectbox("Select Metric 2:", options=["Open", "High", "Low", "Close", "Adj Close", "Volume"])
 
-# 数据过滤
+
 dates = stock_data["Date"]
 metric1_data = stock_data[f"{metric1}_{selected_stock}"]
 metric2_data = stock_data[f"{metric2}_{selected_stock}"]
 
-# 绘制折线图
+
 fig1 = go.Figure()
 fig1.add_trace(go.Scatter(x=dates, y=metric1_data, mode='lines', name=metric1))
 fig1.update_layout(title=f"{metric1} Over Time for {selected_stock}", xaxis_title="Date", yaxis_title=metric1)
 
-# 绘制散点图
+
 fig2 = go.Figure()
 fig2.add_trace(go.Scatter(x=metric1_data, y=metric2_data, mode='markers', name=f"{metric1} vs {metric2}"))
 fig2.update_layout(title=f"{metric1} vs {metric2} for {selected_stock}", xaxis_title=metric1, yaxis_title=metric2)
 
-# 显示图表
+
 st.plotly_chart(fig1)
 st.plotly_chart(fig2)
 
-# 热力图显示月度平均数据
+
 metrics10 = ["Adj Close", "Open", "High", "Low"]
 
 for metric in metrics10:
@@ -187,7 +187,7 @@ st.markdown("[GitHub Repository: IS_445_FINAL](https://github.com/WJHWJH1208/IS_
 
 
 
-# 添加相关性热力图
+
 metrics = ["Adj Close", "Volume", "Open", "High", "Low"]
 st.header("Correlation Heatmap")
 metric_corr = st.selectbox("Select a Metric for Correlation Analysis:", metrics)
@@ -196,24 +196,24 @@ cols = [col for col in stock_data.columns if col.startswith(metric_corr + "_")]
 if cols:
     corr = stock_data[cols].corr()
 
-    # 绘制相关性热力图
+    
     fig, ax = plt.subplots(figsize=(10, 8))
     im = ax.imshow(corr, cmap="coolwarm", vmin=-1, vmax=1)
 
-    # 设置标签
+    
     tickers = [col.replace(metric_corr + "_", "") for col in cols]
     ax.set_xticks(np.arange(len(tickers)))
     ax.set_yticks(np.arange(len(tickers)))
     ax.set_xticklabels(tickers, rotation=45, ha="right")
     ax.set_yticklabels(tickers)
 
-    # 在热力图上显示相关性值
+    
     for i in range(len(tickers)):
         for j in range(len(tickers)):
             text_color = "white" if abs(corr.iloc[i, j]) > 0.5 else "black"
             ax.text(j, i, f"{corr.iloc[i, j]:.2f}", ha="center", va="center", color=text_color)
 
-    # 添加颜色条
+    
     cbar = plt.colorbar(im, ax=ax)
     cbar.set_label("Correlation Coefficient")