Update app.py

app.py

@@ -287,8 +287,6 @@ def get_correlated_dk_portfolio_for_sim(Total_Sample_Size, sharp_split, field_gr
     
     RandomPortfolio, maps_dict, ranges_dict, full_pos_player_dict = create_random_portfolio(sizesplit, raw_baselines, field_growth)
     
-    st.table(RandomPortfolio.head(50))
-    
     RandomPortfolio['C1'] = pd.Series(list(RandomPortfolio['C1'].map(full_pos_player_dict['pos_dicts'][0])), dtype="string[pyarrow]")
     RandomPortfolio['C2'] = pd.Series(list(RandomPortfolio['C2'].map(full_pos_player_dict['pos_dicts'][0])), dtype="string[pyarrow]")
     RandomPortfolio['W1'] = pd.Series(list(RandomPortfolio['W1'].map(full_pos_player_dict['pos_dicts'][1])), dtype="string[pyarrow]")
@@ -303,8 +301,6 @@ def get_correlated_dk_portfolio_for_sim(Total_Sample_Size, sharp_split, field_gr
     RandomPortfolio = RandomPortfolio[RandomPortfolio['plyr_count'] == 10].drop(columns=['plyr_list','plyr_count']).\
         reset_index(drop=True)
     
-    st.table(RandomPortfolio.head(50))
-    
     RandomPortfolio['C1s'] = RandomPortfolio['C1'].map(maps_dict['Salary_map']).astype(np.int32)
     RandomPortfolio['C2s'] = RandomPortfolio['C2'].map(maps_dict['Salary_map']).astype(np.int32)
     RandomPortfolio['W1s'] = RandomPortfolio['W1'].map(maps_dict['Salary_map']).astype(np.int32)
@@ -1446,4 +1442,4 @@ del insert_port1, Contest_Size, sharp_split, Strength_var, scaling_var, Sort_fun
 del raw_baselines
 del freq_format
 
-gc.collect()       
+gc.collect()