Update app.py

app.py

@@ -84,13 +84,26 @@ with st.spinner(f"Simulating poles at {selected_site}..."):
         df = pd.DataFrame(poles_data)
         site_df = df[df['Site'] == selected_site]
 
-with st.spinner(f"Simulating poles at {selected_site}..."):
-    import time
-    time.sleep(2)
-    col1, col2, col3 = st.columns(3)
-    col1.metric("Total Poles", site_df.shape[0])
-    col2.metric("Red Alerts", site_df[site_df['AlertLevel'] == 'Red'].shape[0])
-    col3.metric("Power Insufficiencies", site_df[site_df['Power Status'] == 'Insufficient'].shape[0])
+with# 1. Debug: Print columns in site_df
+st.write("DEBUG: Columns in site_df ➜", site_df.columns.tolist())
+
+# 2. Safely access 'AlertLevel' and count red alerts
+if 'AlertLevel' in site_df.columns:
+    red_alerts = site_df[site_df['AlertLevel'] == 'Red'].shape[0]
+else:
+    red_alerts = 0
+
+# 3. Use Streamlit to display red alert count
+col1, col2, col3 = st.columns(3)
+
+col1.metric("Total Poles", len(site_df))
+
+# Show the red alerts in the second column
+col2.metric("Red Alerts", red_alerts)
+
+# If you have other metrics like energy:
+col3.metric("Energy", int(site_df['Energy'].sum()))
+
 
     # Table View
     st.subheader(f"📋 Pole Data Table for {selected_site}")