Update app.py

app.py

@@ -2,29 +2,35 @@ import streamlit as st
 import pandas as pd
 import numpy as np
 import requests
-import plotly.express as px
 import io
 
-# 設置全局主題
-theme = px.colors.qualitative.Bold
-
 # 下載 CSV 數據
 def download_and_load_csv(url):
     response = requests.get(url)
     response.encoding = 'utf-8'
     df = pd.read_csv(io.StringIO(response.text), encoding='utf-8')
+    
+    # 清理欄位名稱
+    df.columns = df.columns.str.strip().str.replace("\n", "").str.replace("\r", "")
     return df
 
 # 清理數據並合併
 def clean_and_merge_data(urls):
     dfs = [download_and_load_csv(url) for url in urls]
-    
-    # 合併所有數據
     combined_df = pd.concat(dfs, ignore_index=True)
 
     # 指定要清理的排放量欄位
     emission_columns = ["範疇一排放量(噸CO2e)", "範疇二排放量(噸CO2e)", "範疇三排放量(噸CO2e)"]
 
+    # 確保所有欄位名稱都乾淨
+    combined_df.columns = combined_df.columns.str.strip().str.replace("\n", "").str.replace("\r", "")
+
+    # 檢查是否有缺失欄位
+    missing_columns = [col for col in emission_columns if col not in combined_df.columns]
+    if missing_columns:
+        st.write(f"❌ 找不到這些欄位: {missing_columns}")
+        return combined_df  # 直接返回原始數據，避免程式崩潰
+
     # 只清理 emission_columns 內的 0 值，不影響其他欄位
     combined_df[emission_columns] = combined_df[emission_columns].replace(0, np.nan).dropna(subset=emission_columns)