append latest values for apr and roi

corrected_apr_roi_data.csv

@@ -34,4 +34,19 @@ Date,APR,ROI,Adjusted_APR
 2025-05-26,-21.85055074,-2.58899862,-31.064766
 2025-05-27,-10.18089882,-1.359963996,-39.581903
 2025-05-28,-7.71710982,-0.78076962,-0.977322
-2025-05-29,-3.45090984,-0.3380187,-12.790661
+2025-05-29,-3.45090984,-0.3380187,-12.790661
+2025-05-30,147.73021584340188,30.294773082653603,112.4
+2025-05-31,129.06534856719827,26.154208404078816,102.58000000000001
+2025-06-01,133.92093787156588,30.4576658286432,108.39
+2025-06-02,160.88904048962308,26.32814109129394,131.4075
+2025-06-03,247.91781591486583,56.89729073635785,212.09
+2025-06-04,259.4271795709086,30.62716497864707,235.52083333333331
+2025-06-05,256.3495870321672,35.92619676062162,229.02500000000003
+2025-06-06,126.93919776063137,19.315107123633574,103.89500000000001
+2025-06-07,-50.79867270417318,-50.79867270417318,-50.79867270417318
+2025-06-08,-38.086190567520944,-38.086190567520944,-38.086190567520944
+2025-06-09,-46.312258747012297,-46.312258747012297,-46.312258747012297
+2025-06-10,-30.2952437792478,-30.2952437792478,-30.2952437792478
+2025-06-11,-30.4574310175401,-30.4574310175401,-30.4574310175401
+2025-06-12,-22.497274867067427,-22.497274867067427,-22.497274867067427
+2025-06-13,-28.84912891375869,-28.84912891375869,-28.84912891375869

modius_performance/data/data_processor.py

@@ -169,13 +169,8 @@ class DataProcessor:
             apr_df = pd.DataFrame(apr_data_list)
             roi_df = pd.DataFrame(roi_data_list)
             
-            # Filter data to end at May 29, 2025
-            end_date = datetime(2025, 5, 29)
-            apr_df = apr_df[apr_df['timestamp'] <= end_date]
-            roi_df = roi_df[roi_df['timestamp'] <= end_date]
-            
-            logger.info(f"Created APR DataFrame with {len(apr_df)} rows (filtered to end at May 29, 2025)")
-            logger.info(f"Created ROI DataFrame with {len(roi_df)} rows (filtered to end at May 29, 2025)")
+            logger.info(f"Created APR DataFrame with {len(apr_df)} rows (using all available dates)")
+            logger.info(f"Created ROI DataFrame with {len(roi_df)} rows (using all available dates)")
             
             if not apr_df.empty:
                 logger.info(f"APR date range: {apr_df['timestamp'].min()} to {apr_df['timestamp'].max()}")