Refactor init_team_data function in app.py to streamline team data output. Added filtering to include only relevant columns and implemented dropna() and reset_index() for cleaner dataframe presentation.

app.py

@@ -66,11 +66,13 @@ def init_team_data(team, win_loss, kill_prediction, death_prediction):
         if win_loss == "Win":
             team_data['Kill_Proj'] = team_data['wKill%'] * kill_prediction
             team_data['Death_Proj'] = team_data['wDeath%'] * death_prediction
+            team_data = team_data[['playername', 'teamname', 'wKill%', 'wDeath%', 'wAssist%', 'wCS', 'Kill_Proj', 'Death_Proj']]
         else:
             team_data['Kill_Proj'] = team_data['lKill%'] * kill_prediction
             team_data['Death_Proj'] = team_data['lDeath%'] * death_prediction
+            team_data = team_data[['playername', 'teamname', 'lKill%', 'lDeath%', 'lAssist%', 'lCS', 'Kill_Proj', 'Death_Proj']]
 
-        return team_data
+        return team_data.dropna().reset_index(drop=True)
 
 if st.button("Run"):
     st.dataframe(init_team_data(selected_team, win_loss, kill_prediction, death_prediction).style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(display_formats, precision=2), use_container_width = True)