create leaderboard equipos

app.py

@@ -15,7 +15,9 @@ load_dotenv()
 # Constants
 DATA_DIR = "data"
 PARTICIPANTS_CSV = os.path.join(DATA_DIR, "participants.csv")
+EQUIPOS_CSV = os.path.join(DATA_DIR, "equipos.csv")
 LEADERBOARD_PERSONAL_CSV = "leaderboard_personal.csv"
+LEADERBOARD_EQUIPOS_CSV = "leaderboard_equipos.csv"
 
 # Column mappings for participants info
 COLUMN_MAP = {
@@ -25,6 +27,16 @@ COLUMN_MAP = {
     "contact_email": "Email de contacto",
 }
 
+# Column mappings for teams info
+TEAM_COLUMNS = {
+    "team_name": "Nombre del equipo",
+    "email_1": "Email 1",
+    "email_2": "Email 2",
+    "email_3": "Email 3",
+    "email_4": "Email 4",
+    "email_5": "Email 5",
+}
+
 # Initialize Argilla client
 try:
     client = rg.Argilla(
@@ -127,6 +139,90 @@ def get_participant_info():
         return {}
 
 
+def get_team_leaderboard(personal_leaderboard_df):
+    """Calculate team leaderboard based on personal scores."""
+    if not os.path.exists(EQUIPOS_CSV):
+        return pd.DataFrame()
+
+    try:
+        teams_df = pd.read_csv(EQUIPOS_CSV)
+        team_leaderboard = []
+
+        for _, team_row in teams_df.iterrows():
+            team_name = team_row.get(TEAM_COLUMNS["team_name"], "")
+            if not team_name:
+                continue
+
+            # Get team member emails
+            team_emails = []
+            for i in range(1, 6):
+                email_col = TEAM_COLUMNS[f"email_{i}"]
+                email = team_row.get(email_col, "")
+                if pd.notna(email) and email.strip():
+                    team_emails.append(email.lower())
+
+            if not team_emails:
+                continue
+
+            # Map emails to Discord usernames and get scores
+            discord_usernames = []
+            team_scores = {"arena": 0, "blend_es": 0, "estereotipos": 0, "include": 0}
+
+            for email in team_emails:
+                # Get Discord username from email
+                discord_username = get_discord_username(email)
+                discord_usernames.append(discord_username)
+
+                # Find this user in the personal leaderboard
+                user_scores = personal_leaderboard_df[
+                    personal_leaderboard_df["Username"].str.lower()
+                    == discord_username.lower()
+                ]
+
+                if not user_scores.empty:
+                    team_scores["arena"] += user_scores.iloc[0]["Arena"]
+                    team_scores["blend_es"] += user_scores.iloc[0]["Blend-ES"]
+                    team_scores["estereotipos"] += user_scores.iloc[0]["Estereotipos"]
+                    team_scores["include"] += user_scores.iloc[0]["INCLUDE"]
+
+            # Pad Discord usernames list to 5 elements
+            while len(discord_usernames) < 5:
+                discord_usernames.append("")
+
+            # Create team row
+            team_row_data = {
+                "team_name": team_name,
+                "discord_1": discord_usernames[0],
+                "discord_2": discord_usernames[1],
+                "discord_3": discord_usernames[2],
+                "discord_4": discord_usernames[3],
+                "discord_5": discord_usernames[4],
+                "total_arena": team_scores["arena"],
+                "ptos_arena": 0,  # Set to 0 for now as requested
+                "total_blend_es": team_scores["blend_es"],
+                "ptos_blend_es": 0,  # Set to 0 for now as requested
+                "total_estereotipos": team_scores["estereotipos"],
+                "ptos_estereotipos": 0,  # Set to 0 for now as requested
+                "total_include": team_scores["include"],
+                "ptos_include": 0,  # Set to 0 for now as requested
+                "ptos_total": 0,  # Set to 0 for now as requested
+            }
+
+            team_leaderboard.append(team_row_data)
+
+        # Create DataFrame and sort by total_arena
+        if team_leaderboard:
+            team_df = pd.DataFrame(team_leaderboard)
+            team_df.sort_values("total_arena", ascending=False, inplace=True)
+            return team_df
+        else:
+            return pd.DataFrame()
+
+    except Exception as e:
+        print(f"Error calculating team leaderboard: {e}")
+        return pd.DataFrame()
+
+
 def get_blend_es_data():
     """Get blend-es data from Argilla."""
     if not client:
@@ -349,6 +445,11 @@ def consolidate_all_data():
         full_df.sort_values("Arena", ascending=False, inplace=True)
         full_df.to_csv(LEADERBOARD_PERSONAL_CSV, index=False, encoding="utf-8")
 
+    # Generate and save team leaderboard
+    team_df = get_team_leaderboard(full_df)
+    if not team_df.empty:
+        team_df.to_csv(LEADERBOARD_EQUIPOS_CSV, index=False, encoding="utf-8")
+
     # Return display dataframe for UI
     display_df = pd.DataFrame(display_rows)
     if not display_df.empty:

leaderboard_equipos.csv

@@ -0,0 +1,13 @@
+team_name,discord_1,discord_2,discord_3,discord_4,discord_5,total_arena,ptos_arena,total_blend_es,ptos_blend_es,total_estereotipos,ptos_estereotipos,total_include,ptos_include,ptos_total
+Cresia,roverico,cresia.aillm,roverico,,,280,0,0,0,0,0,608,0,0
+TralaleloTralala-MemeAlign,andres_seba,andres_seba,peroloso,,,240,0,0,0,0,0,880,0,0
+IberoTales,mcdaqc,,,,,118,0,0,0,0,0,449,0,0
+SabiduriaPopular Castellana,alvaro8gb,enrique.solera.navarro,angustias22,comasberto,,105,0,0,0,0,0,2,0,0
+Think Paraguayo,enpaiva93,luceldasilva,edmenciab,,,93,0,0,0,0,0,505,0,0
+HoCV-COL,dreamripper1,,,,,83,0,0,0,0,0,987,0,0
+Refranero Afro-Cubano,rasel3132,bel21093,,,,0,0,0,0,0,0,0,0,0
+Comida Colombia + Ecuador,pablo.ce,pablo.ce,magodyboy,nestoralarcon.ed,diegomarquez2008,0,0,0,0,0,0,5660,0,0
+Equipo LeIA,susanazhou,cosntanzapjeldres,,,,0,0,0,0,0,0,560,0,0
+PeruWhisper,vandread13,vandread13,,,,0,0,0,0,0,0,0,0,0
+Falsos_Amigos,yeisonm3011,erick bustamante,dinho9779,,,0,0,0,0,0,0,0,0,0
+MP,rvk6212,,,,,0,0,0,0,0,0,0,0,0