Update app.py

app.py

@@ -37,14 +37,13 @@ st.markdown("""
 @st.cache_data
 def load_data():
     try:
-        # Load data
-        df = pd.read_csv("Frontier AI DC Emissions - Frontier Timeline.csv")
+        # Load data, skipping the first empty row (header=1 means Row 2 is the header)
+        df = pd.read_csv("Frontier AI DC Emissions - Frontier Timeline.csv", header=1)
         
-        # --- FIX 1: Sanitize Headers ---
-        # Removes hidden spaces (e.g. "Power (MW) " -> "Power (MW)")
+        # Sanitize Headers (removes hidden spaces)
         df.columns = df.columns.str.strip()
         
-        # Validation: Check if columns exist, if not, show what was found
+        # Validation: Check if columns exist
         required_cols = ['Power (MW)', 'Carbon Intensity', 'Annual Million tCO2']
         missing = [c for c in required_cols if c not in df.columns]
         if missing:
@@ -65,8 +64,9 @@ def load_data():
     df['Carbon Intensity'] = df['Carbon Intensity'].apply(clean_numeric)
     df['Annual Million tCO2'] = df['Annual Million tCO2'].apply(clean_numeric)
 
-    # --- FIX 2: Math Check (Power * Intensity vs Reported) ---
+    # --- MATH CHECK (Verification) ---
     # Formula: MW * 8760 hours * (Intensity kg/MWh / 1000 to get tonnes) / 1,000,000 to get Million Tonnes
+    # We calculate this to double-check the CSV's reported numbers
     df['Calculated_Mt'] = (df['Power (MW)'] * 8760 * df['Carbon Intensity']) / 1e9
     
     # Use the Reported number, but normalize it (Handle the 13,093 vs 13.1 issue)
@@ -74,7 +74,6 @@ def load_data():
     df['Emissions_Mt'] = df['Annual Million tCO2'].apply(lambda x: x / 1000 if x > 100 else x)
     
     # --- Geocoding (Manual Overrides for missing Lat/Long) ---
-    # Add coordinates for known projects if missing
     overrides = {
         'Fermi': [35.344, -101.373],       # Amarillo, TX
         'Crane': [40.154, -76.725],        # Three Mile Island