Final

S34 Draft Sheet - Captains.csv

@@ -0,0 +1,10 @@
+Name:,Dotabuff:,MMR:,Buck's Bucks,Crub Cents,Remaining:
+Space Cowboy,https://www.dotabuff.com/players/123736773,3487,558,593,593
+juicy,https://www.dotabuff.com/players/162015739,4269,518,555,555
+Yop,https://www.dotabuff.com/players/89699373,4751,493,524,524
+MAPPO,https://www.dotabuff.com/players/123919855,4800,491,521,521
+ShadowAce,https://www.dotabuff.com/players/167390514,4800,491,521,521
+Tokc,https://www.dotabuff.com/players/96895570,5016,479,505,505
+Treebeard,https://www.dotabuff.com/players/95576973,6000,429,418,418
+DoomCow33,https://www.dotabuff.com/players/172199571,6031,427,415,415
+TriVal,https://www.dotabuff.com/players/1203364439,6620,397,352,352

app.py

@@ -55,17 +55,34 @@ def prepare_single_player_data(user_id, mmr, comf_1, comf_2, comf_3, comf_4, com
                 if key in EXPECTED_COLUMNS:
                     data[key] = value
         
-        # Add mock statistics for money-related columns
-        # These would normally come from league_money function
-        stats = {
-            'count': 1,
-            'mean': mmr / 200,  # rough approximation
-            'std': mmr / 400,
-            'min': mmr / 250,
-            'max': mmr / 150,
-            'sum': mmr / 200
-        }
-        data.update(stats)
+        # Get statistics from league data
+        try:
+            captains_df = pd.read_csv("S34 Draft Sheet  Captains.csv")
+            bucks_stats = captains_df["Buck's Bucks"].describe()
+            cents_stats = captains_df["Crub Cents"].describe()
+            
+            # Combine stats from both currencies
+            combined_stats = {
+                'count': bucks_stats['count'] + cents_stats['count'],
+                'mean': (bucks_stats['mean'] + cents_stats['mean']) / 2,
+                'std': (bucks_stats['std'] + cents_stats['std']) / 2,
+                'min': min(bucks_stats['min'], cents_stats['min']),
+                'max': max(bucks_stats['max'], cents_stats['max']),
+                'sum': bucks_stats['count'] * bucks_stats['mean'] + cents_stats['count'] * cents_stats['mean']
+            }
+            data.update(combined_stats)
+        except Exception as e:
+            print(f"Error reading captains data: {e}")
+            # Fallback to mock data if file read fails
+            stats = {
+                'count': 1,
+                'mean': mmr / 200,
+                'std': mmr / 400,
+                'min': mmr / 250,
+                'max': mmr / 150,
+                'sum': mmr / 200
+            }
+            data.update(stats)
         
         # Convert to DataFrame
         df = pd.DataFrame([data])