Update app.py

app.py

@@ -3,33 +3,27 @@ import requests
 import plotly.express as px
 import streamlit as st
 import time
-import matplotlib.font_manager as fm
-import matplotlib as mpl
 from io import StringIO
 
-# Download and set custom font
+# Download and set custom font (unchanged)
 font_url = "https://drive.google.com/uc?id=1eGAsTN1HBpJAkeVM57_C7ccp7hbgSz3_&export=download"
 font_response = requests.get(font_url)
 with open("TaipeiSansTCBeta-Regular.ttf", "wb") as font_file:
     font_file.write(font_response.content)
 
-# Register the font with matplotlib
-fm.fontManager.addfont("TaipeiSansTCBeta-Regular.ttf")
-mpl.rc('font', family='Taipei Sans TC Beta')
-
 # Function to download and load CSV into a DataFrame
-@st.cache_data  # Add caching to improve performance
+@st.cache_data
 def download_csv(url):
     response = requests.get(url)
     df = pd.read_csv(StringIO(response.text))
     df = df.fillna(0)  # Fill missing values with 0
     return df
 
-# URLs to download data from
+# URLs to download data from (unchanged)
 urls = {
-    "溫室氣體": "https://mopsfin.twse.com.tw/opendata/t187ap46_L_1.csv",  # ESG
-    "再生能源": "https://mopsfin.twse.com.tw/opendata/t187ap46_O_2.csv",  # Renewable Energy
-    "董事會": "https://mopsfin.twse.com.tw/opendata/t187ap46_L_6.csv"   # Board of Directors
+    "溫室氣體": "https://mopsfin.twse.com.tw/opendata/t187ap46_L_1.csv",
+    "再生能源": "https://mopsfin.twse.com.tw/opendata/t187ap46_O_2.csv",
+    "董事會": "https://mopsfin.twse.com.tw/opendata/t187ap46_L_6.csv"
 }
 
 # Set page config for a wider layout
@@ -50,7 +44,6 @@ st.markdown('<p class="big-font">ESG Data Visualization</p>', unsafe_allow_html=
 # Sidebar for data selection and chart options
 st.sidebar.header("設置")
 selected_option = st.sidebar.selectbox("選擇資料類型", options=list(urls.keys()))
-chart_type = st.sidebar.radio("選擇圖表類型", ("圓餅圖", "柱狀圖", "折線圖"))
 
 # Main content area
 if st.sidebar.button("載入資料"):
@@ -63,37 +56,41 @@ if st.sidebar.button("載入資料"):
         
         df = download_csv(urls[selected_option])
     
-    # Displaying the DataFrame with styling
+    # Displaying the DataFrame without styling
     st.header(f"{selected_option} 資料")
-    st.dataframe(df.style.highlight_max(axis=0))
+    st.dataframe(df)
     
     # Data summary
     st.subheader("資料摘要")
-    col1, col2 = st.columns(2)
-    with col1:
-        st.write(df.describe())
-    with col2:
-        st.write(df.info())
-    
-    # Visualization
-    st.subheader("資料視覺化")
-    if chart_type == "圓餅圖":
-        fig = px.pie(df, names=df.columns[0], values=df.columns[1], title=f"{selected_option} 分佈")
-    elif chart_type == "柱狀圖":
-        fig = px.bar(df, x=df.columns[0], y=df.columns[1], title=f"{selected_option} 比較")
-    else:  # 折線圖
-        fig = px.line(df, x=df.columns[0], y=df.columns[1], title=f"{selected_option} 趨勢")
-    
-    # Apply custom font and styling to the plot
-    fig.update_layout(
-        font_family="Taipei Sans TC Beta",
-        title_font_size=24,
-        legend_title_font_size=14,
-        legend_font_size=12
-    )
+    st.write(df.describe())
     
-    # Display the chart
-    st.plotly_chart(fig, use_container_width=True)
+    # Column selection for visualization
+    numeric_columns = df.select_dtypes(include=['int64', 'float64']).columns
+    if len(numeric_columns) > 1:
+        x_column = st.selectbox("選擇 X 軸欄位", options=df.columns)
+        y_column = st.selectbox("選擇 Y 軸欄位", options=numeric_columns)
+        
+        # Visualization
+        st.subheader("資料視覺化")
+        chart_type = st.radio("選擇圖表類型", ("圓餅圖", "柱狀圖"))
+        
+        if chart_type == "圓餅圖":
+            fig = px.pie(df, names=x_column, values=y_column, title=f"{selected_option} 分佈")
+        else:  # 柱狀圖
+            fig = px.bar(df, x=x_column, y=y_column, title=f"{selected_option} 比較")
+        
+        # Apply custom font and styling to the plot
+        fig.update_layout(
+            font_family="Taipei Sans TC Beta",
+            title_font_size=24,
+            legend_title_font_size=14,
+            legend_font_size=12
+        )
+        
+        # Display the chart
+        st.plotly_chart(fig, use_container_width=True)
+    else:
+        st.warning("沒有足夠的數值型欄位來創建圖表。請選擇另一個數據集。")
     
     # Add download button for the data
     csv = df.to_csv(index=False)