Update app.py

app.py

@@ -135,7 +135,7 @@ with tab2:
         data=convert_df_to_csv(qb_stats_disp),
         file_name='NFL_qb_stats_export.csv',
         mime='text/csv',
-        key='pitcher_prop_export',
+        key='NFL_qb_stats_export',
     )
 
 with tab3:
@@ -161,7 +161,7 @@ with tab3:
         data=convert_df_to_csv(non_qb_stats_disp),
         file_name='NFL_nonqb_stats_export.csv',
         mime='text/csv',
-        key='hitter_prop_export',
+        key='NFL_nonqb_stats_export',
     )
     
 with tab4:
@@ -251,8 +251,6 @@ with tab5:
                         player_var = df.loc[df['Player'] == player_check]
                         player_var = player_var.reset_index()
                         
-                        ['NFL_GAME_PLAYER_PASSING_YARDS', 'NFL_GAME_PLAYER_RUSHING_YARDS', 'NFL_GAME_PLAYER_RECEIVING_YARDS', 'NFL_GAME_PLAYER_RECEIVING_RECEPTIONS', 'NFL_GAME_PLAYER_RUSHING_ATTEMPTS', 'NFL_GAME_PLAYER_PASSING_ATTEMPTS']
-
                         if prop_type_var == 'Pass Yards':
                             df['Median'] = df['pass_yards']
                         elif prop_type_var == 'Pass TDs':
@@ -276,7 +274,7 @@ with tab5:
 
                         flex_file = df
                         flex_file['Floor'] = flex_file['Median'] * .20
-                        flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * .80)
+                        flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * 1.80)
                         flex_file['STD'] = flex_file['Median'] / 4
                         flex_file = flex_file[['Player', 'Floor', 'Median', 'Ceiling', 'STD']]
 
@@ -405,21 +403,19 @@ with tab6:
                                 df.replace("", 0, inplace=True)
         
                                 if prop == "pass_yards":
-                                    df['Median'] = df['pass_yards']
+                                    df['Median'] = df['NFL_GAME_PLAYER_PASSING_YARDS']
                                 elif prop == "rush_yards":
-                                    df['Median'] = df['rush_yards']
+                                    df['Median'] = df['NFL_GAME_PLAYER_RUSHING_YARDS']
                                 elif prop == "rec_yards":
-                                    df['Median'] = df['rec_yards']
-                                elif prop == "receptions":
-                                    df['Median'] = df['rec']
+                                    df['Median'] = df['NFL_GAME_PLAYER_RECEIVING_YARDS']
                                 elif prop == "receptions":
-                                    df['Median'] = df['rec']
+                                    df['Median'] = df['NFL_GAME_PLAYER_RECEIVING_RECEPTIONS']
                                 elif prop == "rush_attempts":
-                                    df['Median'] = df['rush_att']
+                                    df['Median'] = df['NFL_GAME_PLAYER_RUSHING_ATTEMPTS']
         
                                 flex_file = df
                                 flex_file['Floor'] = flex_file['Median'] * .20
-                                flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * .80)
+                                flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * 1.80)
                                 flex_file['STD'] = flex_file['Median'] / 4
                                 flex_file['Prop'] = flex_file['Player'].map(prop_dict)
                                 flex_file = flex_file[['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]
@@ -482,9 +478,9 @@ with tab6:
                             elif game_select_var == 'Pick6':
                                 prop_df = pick_frame[['Full_name', 'over_prop', 'over_line', 'under_line', 'prop_type']]
                                 prop_df.rename(columns={"Full_name": "Player"}, inplace = True)
-
+                            
                             if prop_type_var == "pass_yards":
-                                prop_df = prop_df.loc[prop_df['prop_type'] == 'pass_yards']
+                                prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_PASSING_YARDS']
                                 prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -493,7 +489,7 @@ with tab6:
                                 prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "rush_yards":
-                                prop_df = prop_df.loc[prop_df['prop_type'] == 'rush_yards']
+                                prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_RUSHING_YARDS']
                                 prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -502,7 +498,7 @@ with tab6:
                                 prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "rec_yards":
-                                prop_df = prop_df.loc[prop_df['prop_type'] == 'rec_yards']
+                                prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_RECEIVING_YARDS']
                                 prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -511,7 +507,7 @@ with tab6:
                                 prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "receptions":
-                                prop_df = prop_df.loc[prop_df['prop_type'] == 'receptions']
+                                prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_RECEIVING_RECEPTIONS']
                                 prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -520,7 +516,7 @@ with tab6:
                                 prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "rush_attempts":
-                                prop_df = prop_df.loc[prop_df['prop_type'] == 'rush_attempts']
+                                prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_RUSHING_ATTEMPTS']
                                 prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -529,7 +525,7 @@ with tab6:
                                 prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "pass_attempts":
-                                prop_df = prop_df.loc[prop_df['prop_type'] == 'pass_attempts']
+                                prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_PASSING_ATTEMPTS']
                                 prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -538,7 +534,7 @@ with tab6:
                                 prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
                                 df = pd.merge(overall_stats, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
                             elif prop_type_var == "pass_completions":
-                                prop_df = prop_df.loc[prop_df['prop_type'] == 'pass_completions']
+                                prop_df = prop_df.loc[prop_df['prop_type'] == 'NFL_GAME_PLAYER_PASSING_COMPLETIONS']
                                 prop_df = prop_df[['Player', 'over_prop', 'over_line', 'under_line']]
                                 prop_df.rename(columns={"over_prop": "Prop"}, inplace = True)
                                 prop_df = prop_df.loc[prop_df['Prop'] != 0]
@@ -554,23 +550,21 @@ with tab6:
                             total_sims = 5000
     
                             df.replace("", 0, inplace=True)
-    
+                            
                             if prop_type_var == "pass_yards":
-                                df['Median'] = df['pass_yards']
+                                df['Median'] = df['NFL_GAME_PLAYER_PASSING_YARDS']
                             elif prop_type_var == "rush_yards":
-                                df['Median'] = df['rush_yards']
+                                df['Median'] = df['NFL_GAME_PLAYER_RUSHING_YARDS']
                             elif prop_type_var == "rec_yards":
-                                df['Median'] = df['rec_yards']
-                            elif prop_type_var == "receptions":
-                                df['Median'] = df['rec']
+                                df['Median'] = df['NFL_GAME_PLAYER_RECEIVING_YARDS']
                             elif prop_type_var == "receptions":
-                                df['Median'] = df['rec']
+                                df['Median'] = df['NFL_GAME_PLAYER_RECEIVING_RECEPTIONS']
                             elif prop_type_var == "rush_attempts":
-                                df['Median'] = df['rush_att']
+                                df['Median'] = df['NFL_GAME_PLAYER_RUSHING_ATTEMPTS']
     
                             flex_file = df
                             flex_file['Floor'] = flex_file['Median'] * .20
-                            flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * .80)
+                            flex_file['Ceiling'] = flex_file['Median'] + (flex_file['Median'] * 1.80)
                             flex_file['STD'] = flex_file['Median'] / 4
                             flex_file['Prop'] = flex_file['Player'].map(prop_dict)
                             flex_file = flex_file[['Player', 'Prop', 'Floor', 'Median', 'Ceiling', 'STD']]