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app.py

@@ -217,16 +217,19 @@ async def get_historical_data():
         df['timestamp'] = pd.to_datetime(df['timestamp'])
         df = df.sort_values('timestamp')
         
-        # Get last 48 hours of data (48 data points max for performance)
-        cutoff_time = datetime.now(timezone.utc) - pd.Timedelta(hours=48)
-        df_filtered = df[df['timestamp'] >= cutoff_time]
+        # Use all available data to show full historical range
+        df_filtered = df.copy()
         
-        logger.info(f"Filtered to {len(df_filtered)} records in last 48 hours")
+        logger.info(f"Using all {len(df_filtered)} records for full historical view")
         
-        # If no recent data, use all available data for initial display
-        if df_filtered.empty:
-            logger.info("No data in last 48 hours, using all available data")
-            df_filtered = df.tail(100)  # Use last 100 records
+        # For performance, limit to reasonable number of points per provider
+        max_points_per_provider = 500
+        if len(df_filtered) > max_points_per_provider * len(PROVIDERS):
+            # Sample data to keep it manageable while preserving time range
+            df_filtered = df_filtered.groupby('provider').apply(
+                lambda x: x.iloc[::max(1, len(x) // max_points_per_provider)]
+            ).reset_index(drop=True)
+            logger.info(f"Sampled down to {len(df_filtered)} records for performance")
         
         # Prepare data for Chart.js line chart
         historical_data = {}
@@ -249,11 +252,21 @@ async def get_historical_data():
         
         logger.info(f"Returning {total_data_points} total data points across {len([p for p in historical_data.values() if p])} providers")
         
+        # Calculate date range for display
+        if not df_filtered.empty:
+            earliest_date = df_filtered['timestamp'].min().strftime('%Y-%m-%d %H:%M')
+            latest_date = df_filtered['timestamp'].max().strftime('%Y-%m-%d %H:%M')
+            date_range = f"From {earliest_date} to {latest_date}"
+        else:
+            date_range = "No data"
+
         return {
             "historical_data": historical_data,
             "last_updated": datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
             "total_data_points": total_data_points,
-            "data_range": f"Last {len(df_filtered)} records" if not df_filtered.empty else "No data"
+            "data_range": date_range,
+            "earliest_date": df_filtered['timestamp'].min().isoformat() if not df_filtered.empty else None,
+            "latest_date": df_filtered['timestamp'].max().isoformat() if not df_filtered.empty else None
         }
         
     except Exception as e: