1.7.0: New features.

scripts/analyze_dmg_per_1k.py

@@ -0,0 +1,74 @@
+
+import sqlite3
+import pandas as pd
+import os
+
+# Config
+L2_DB_PATH = r'database/L2/L2_Main.sqlite'
+L3_DB_PATH = r'database/L3/L3_Features.sqlite'
+
+def analyze_team_dmg_per_1k():
+    if not os.path.exists(L3_DB_PATH):
+        print(f"Error: L3 DB not found at {L3_DB_PATH}")
+        return
+
+    conn_l3 = sqlite3.connect(L3_DB_PATH)
+    conn_l2 = sqlite3.connect(L2_DB_PATH)
+    
+    print("--- Analysis: Team Dmg/$1k (Economy Efficiency) ---")
+    
+    try:
+        # 1. Get all L3 features
+        query = """
+        SELECT f.steam_id_64, f.eco_avg_damage_per_1k, p.username
+        FROM dm_player_features f
+        LEFT JOIN dim_players p ON f.steam_id_64 = p.steam_id_64
+        ORDER BY f.eco_avg_damage_per_1k DESC
+        """
+        
+        # Attach L2 for username lookup
+        # We can't attach across connections easily in sqlite python without ATTACH DATABASE command
+        # So let's fetch L3 first, then map names from L2
+        
+        df_l3 = pd.read_sql_query("SELECT steam_id_64, eco_avg_damage_per_1k FROM dm_player_features", conn_l3)
+        
+        if df_l3.empty:
+            print("No data in L3 Features.")
+            return
+
+        # Fetch names
+        ids = tuple(df_l3['steam_id_64'].tolist())
+        placeholders = ','.join(['?'] * len(ids))
+        q_names = f"SELECT steam_id_64, username FROM dim_players WHERE steam_id_64 IN ({placeholders})"
+        df_names = pd.read_sql_query(q_names, conn_l2, params=ids)
+        
+        # Merge
+        df = df_l3.merge(df_names, on='steam_id_64', how='left')
+        
+        # Sort
+        df = df.sort_values('eco_avg_damage_per_1k', ascending=False)
+        
+        print(f"{'Rank':<5} {'Player':<20} {'Dmg/$1k':<10}")
+        print("-" * 40)
+        
+        for idx, row in df.iterrows():
+            rank = idx + 1 # This index is not rank if we iterated row by row after sort, wait.
+            # reset_index to get rank
+            pass
+        
+        df = df.reset_index(drop=True)
+        for idx, row in df.iterrows():
+            name = row['username'] if row['username'] else row['steam_id_64']
+            val = row['eco_avg_damage_per_1k']
+            print(f"#{idx+1:<4} {name:<20} {val:.2f}")
+            
+    except Exception as e:
+        print(f"Error: {e}")
+        import traceback
+        traceback.print_exc()
+    finally:
+        conn_l2.close()
+        conn_l3.close()
+
+if __name__ == "__main__":
+    analyze_team_dmg_per_1k()