changed hold_file to over_file based on local ROO sequence

app.py

@@ -1,4 +1,5 @@
 import numpy as np
+from numpy import random
 import pandas as pd
 import streamlit as st
 import gspread
@@ -169,29 +170,27 @@ with tab1:
                     salary_file = flex_file.copy()
     
                     overall_players = overall_file[['Player']]
-    
+
                     for x in range(0,total_sims):    
                         salary_file[x] = salary_file['Salary']
-    
+                        overall_file[x] = random.normal(overall_file['Median'],overall_file['STD'])
+
                     salary_file=salary_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
                     salary_file.astype('int').dtypes
-    
+
                     salary_file = salary_file.div(1000)
-    
-                    for x in range(0,total_sims):    
-                        overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
-    
+
                     overall_file=overall_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
                     overall_file.astype('int').dtypes
-    
+
                     players_only = hold_file[['Player']]
                     raw_lineups_file = players_only
-    
+
                     for x in range(0,total_sims):
-                        maps_dict = {'proj_map':dict(zip(hold_file.Player,hold_file[x]))}
+                        maps_dict = {'proj_map':dict(zip(hold_file.Player,overall_file[x]))}
                         raw_lineups_file[x] = sum([raw_lineups_file['Player'].map(maps_dict['proj_map'])])
                         players_only[x] = raw_lineups_file[x].rank(ascending=False)
-    
+
                     players_only=players_only.drop(['Player'], axis=1)
                     players_only.astype('int').dtypes
     
@@ -256,29 +255,27 @@ with tab1:
                         salary_file = flex_file.copy()
                         
                         overall_players = overall_file[['Player']]
-    
+
                         for x in range(0,total_sims):    
                             salary_file[x] = salary_file['Salary']
-        
+                            overall_file[x] = random.normal(overall_file['Median'],overall_file['STD'])
+
                         salary_file=salary_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
                         salary_file.astype('int').dtypes
-        
+
                         salary_file = salary_file.div(1000)
-        
-                        for x in range(0,total_sims):    
-                            overall_file[x] = np.random.normal(overall_file['Median'],overall_file['STD'])
-        
+
                         overall_file=overall_file.drop(['Player', 'Position', 'Salary', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
                         overall_file.astype('int').dtypes
-        
+
                         players_only = hold_file[['Player']]
                         raw_lineups_file = players_only
-        
+
                         for x in range(0,total_sims):
-                            maps_dict = {'proj_map':dict(zip(hold_file.Player,hold_file[x]))}
+                            maps_dict = {'proj_map':dict(zip(hold_file.Player,overall_file[x]))}
                             raw_lineups_file[x] = sum([raw_lineups_file['Player'].map(maps_dict['proj_map'])])
                             players_only[x] = raw_lineups_file[x].rank(ascending=False)
-        
+
                         players_only=players_only.drop(['Player'], axis=1)
                         players_only.astype('int').dtypes