Update app.py

app.py

@@ -138,8 +138,12 @@ with tab3:
 
                         hold_file = flex_file
                         overall_file = flex_file
-                        salary_file = flex_file
                         
+                        overall_players = overall_file[['Player']]
+
+                        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', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
                         overall_file.astype('int').dtypes
 
@@ -166,8 +170,8 @@ with tab3:
                         final_outcomes = players_only[['Player', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '10%', '90%']]
 
                         final_Proj = pd.merge(hold_file, final_outcomes, on="Player")
-                        final_Proj = final_Proj[['Player', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '10%', 'Median', '90%']]
-                        
+                        final_Proj = final_Proj[['Player', '10%', 'Median', '90%', 'Top_finish', 'Top_5_finish', 'Top_10_finish']]
+
                         st.dataframe(final_Proj.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
     
 with tab4:
@@ -194,11 +198,11 @@ with tab4:
 
                         df.replace("", 0, inplace=True)
 
-                        if prop_type_var_h == 'Strikeouts':
+                        if prop_type_var_sp == 'Strikeouts':
                             df['Median'] = df['Strikeouts']
-                        elif prop_type_var_h == 'Wins':
+                        elif prop_type_var_sp == 'Wins':
                             df['Median'] = df['Wins']
-                        elif prop_type_var_h == 'Quality_starts':
+                        elif prop_type_var_sp == 'Quality_starts':
                             df['Median'] = df['Quality_starts']
 
                         flex_file = df
@@ -209,8 +213,12 @@ with tab4:
 
                         hold_file = flex_file
                         overall_file = flex_file
-                        salary_file = flex_file
                         
+                        overall_players = overall_file[['Player']]
+
+                        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', 'Floor', 'Median', 'Ceiling', 'STD'], axis=1)
                         overall_file.astype('int').dtypes
 
@@ -237,6 +245,6 @@ with tab4:
                         final_outcomes = players_only[['Player', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '10%', '90%']]
 
                         final_Proj = pd.merge(hold_file, final_outcomes, on="Player")
-                        final_Proj = final_Proj[['Player', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '10%', 'Median', '90%']]
-                        
+                        final_Proj = final_Proj[['Player', '10%', 'Median', '90%', 'Top_finish', 'Top_5_finish', 'Top_10_finish']]
+
                         st.dataframe(final_Proj.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)