Update app.py

app.py

@@ -407,61 +407,56 @@ with tab2:
                             lineup_final = lineup_final.drop(columns=['Names'])
                             lineup_final.rename(columns={"sorted": "Names"}, inplace = True)
                               
-                        # elif site_var1 == 'Fanduel':
-                        #     line_hold = lineup_final[['Names']]
-                        #     line_hold['pos'] = line_hold['Names'].map(player_pos)
-
-                        #     for pname in range(0,len(line_hold)):
-                        #         if line_hold.iat[pname,1] == 'QB':
-                        #             if line_hold.iat[pname,0] not in p_used:
-                        #                 sorted_lineup.append(line_hold.iat[pname,0])
-                        #     p_used.extend(sorted_lineup)        
-                        #     rbvar = 0
-                        #     for pname in range(0,len(line_hold)):
-                        #         if rbvar == 2:
-                        #             pname = len(line_hold)
-                        #         elif rbvar < 2:
-                        #             if line_hold.iat[pname,1] == 'RB':
-                        #                 if line_hold.iat[pname,0] not in p_used:
-                        #                     sorted_lineup.append(line_hold.iat[pname,0])
-                        #                     rbvar = rbvar + 1
-                        #     p_used.extend(sorted_lineup)
-                        #     wrvar = 0
-                        #     for pname in range(0,len(line_hold)):
-                        #         if wrvar == 3:
-                        #             pname = len(line_hold)
-                        #         elif wrvar < 3:
-                        #             if line_hold.iat[pname,1] == 'WR':
-                        #                 if line_hold.iat[pname,0] not in p_used:
-                        #                     sorted_lineup.append(line_hold.iat[pname,0])
-                        #                     wrvar = wrvar + 1
-                        #     p_used.extend(sorted_lineup)
-                        #     tevar = 0
-                        #     for pname in range(0,len(line_hold)):
-                        #         if tevar == 1:
-                        #             pname = len(line_hold)
-                        #         elif tevar < 1:
-                        #             if line_hold.iat[pname,1] == 'TE':
-                        #                 if line_hold.iat[pname,0] not in p_used:
-                        #                     sorted_lineup.append(line_hold.iat[pname,0])
-                        #                     tevar = tevar + 1
-                        #     p_used.extend(sorted_lineup)
+                        elif site_var1 == 'Fanduel':
+                            line_hold = lineup_final[['Names']]
+                            line_hold['pos'] = line_hold['Names'].map(player_pos)
+                            
+                            cvar = 0
+                            for pname in range(0,len(line_hold)):
+                                if cvar == 2:
+                                    pname = len(line_hold)
+                                elif cvar < 2:
+                                    if line_hold.iat[pname,1] == 'C':
+                                        if line_hold.iat[pname,0] not in p_used:
+                                            sorted_lineup.append(line_hold.iat[pname,0])
+                                            cvar = cvar + 1
+                            p_used.extend(sorted_lineup)
+                            wvar = 0
+                            for pname in range(0,len(line_hold)):
+                                if wvar == 2:
+                                    pname = len(line_hold)
+                                elif wvar < 2:
+                                    if line_hold.iat[pname,1] == 'C':
+                                        if line_hold.iat[pname,0] not in p_used:
+                                            sorted_lineup.append(line_hold.iat[pname,0])
+                                            wvar = wvar + 1
+                            p_used.extend(sorted_lineup)
+                            dvar = 0
+                            for pname in range(0,len(line_hold)):
+                                if dvar == 2:
+                                    pname = len(line_hold)
+                                elif dvar < 2:
+                                    if line_hold.iat[pname,1] == "D":
+                                        if line_hold.iat[pname,0] not in p_used:
+                                            sorted_lineup.append(line_hold.iat[pname,0])
+                                            dvar = dvar + 1
+                            p_used.extend(sorted_lineup)
                             
-                        #     for pname in range(0,len(line_hold)):
-                        #         if line_hold.iat[pname,1] != 'DST':
-                        #             if line_hold.iat[pname,0] not in p_used:
-                        #                 sorted_lineup.append(line_hold.iat[pname,0])
-                        #     p_used.extend(sorted_lineup)
+                            for pname in range(0,len(line_hold)):
+                                if line_hold.iat[pname,1] != 'G':
+                                    if line_hold.iat[pname,0] not in p_used:
+                                        sorted_lineup.append(line_hold.iat[pname,0])
+                            p_used.extend(sorted_lineup)
                             
-                        #     for pname in range(0,len(line_hold)):
-                        #         if line_hold.iat[pname,1] == 'DST':
-                        #             if line_hold.iat[pname,0] not in p_used:
-                        #                 sorted_lineup.append(line_hold.iat[pname,0])
-                        #     p_used.extend(sorted_lineup)
+                            for pname in range(0,len(line_hold)):
+                                if line_hold.iat[pname,1] == 'G':
+                                    if line_hold.iat[pname,0] not in p_used:
+                                        sorted_lineup.append(line_hold.iat[pname,0])
+                            p_used.extend(sorted_lineup)
                             
-                        #     lineup_final['sorted'] = sorted_lineup
-                        #     lineup_final = lineup_final.drop(columns=['Names'])
-                        #     lineup_final.rename(columns={"sorted": "Names"}, inplace = True)
+                            lineup_final['sorted'] = sorted_lineup
+                            lineup_final = lineup_final.drop(columns=['Names'])
+                            lineup_final.rename(columns={"sorted": "Names"}, inplace = True)
                               
                         lineup_test = lineup_final
                         lineup_final = lineup_final.T
@@ -493,32 +488,33 @@ with tab2:
                         x += 1
     
                     if site_var1 == 'Draftkings':
-                        portfolio.rename(columns={0: "C1", 1: "C2", 2: "W1", 3: "W2", 4: "WW3", 5: "D1", 6: "D2", 7: "UTIL", 8: "G"}, inplace = True)
+                        portfolio.rename(columns={0: "C1", 1: "C2", 2: "W1", 3: "W2", 4: "W3", 5: "D1", 6: "D2", 7: "UTIL", 8: "G"}, inplace = True)
                     elif site_var1 == 'Fanduel':
-                        portfolio.rename(columns={0: "QB", 1: "RB1", 2: "RB2", 3: "WR1", 4: "WR2", 5: "WR3", 6: "TE", 7: "UTIL", 8: "DST"}, inplace = True)
+                        portfolio.rename(columns={0: "C1", 1: "C2", 2: "W1", 3: "W2", 4: "D1", 5: "D2", 6: "UTIL1", 7: "UTIL2", 8: "G"}, inplace = True)
                     portfolio = portfolio.dropna()
                     portfolio = portfolio.reset_index()
                     portfolio['Lineup_num'] = portfolio['index'] + 1
                     portfolio.rename(columns={'Lineup_num': "Lineup"}, inplace = True)
                     portfolio = portfolio.set_index('Lineup')
                     portfolio = portfolio.drop(columns=['index'])
-
-                    final_outcomes = portfolio[['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G', 'Cost', 'Proj', 'Own']]
-                    final_outcomes = final_outcomes.set_axis(['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G', 'Cost', 'Proj', 'Own'], axis=1)
-                    final_outcomes_export = pd.DataFrame()
-                    final_outcomes_export['C1'] = final_outcomes['C1']
-                    final_outcomes_export['C2'] = final_outcomes['C2']
-                    final_outcomes_export['W1'] = final_outcomes['W1']
-                    final_outcomes_export['W2'] = final_outcomes['W2']
-                    final_outcomes_export['W3'] = final_outcomes['W3']
-                    final_outcomes_export['D1'] = final_outcomes['D1']
-                    final_outcomes_export['D2'] = final_outcomes['D2']
-                    final_outcomes_export['UTIL'] = final_outcomes['UTIL']
-                    final_outcomes_export['G'] = final_outcomes['G']
-                    final_outcomes_export['Salary'] = final_outcomes['Cost']
-                    final_outcomes_export['Own'] = final_outcomes['Own']
-                    final_outcomes_export['Proj'] = final_outcomes['Proj']
+                    
                     if site_var1 == 'Draftkings':
+                        final_outcomes = portfolio[['C1', 'C2', 'W1', 'W2', 'W3', 'D1', 'D2', 'UTIL', 'G', 'Cost', 'Proj', 'Own']]
+                        
+                        final_outcomes_export = pd.DataFrame()
+                        final_outcomes_export['C1'] = final_outcomes['C1']
+                        final_outcomes_export['C2'] = final_outcomes['C2']
+                        final_outcomes_export['W1'] = final_outcomes['W1']
+                        final_outcomes_export['W2'] = final_outcomes['W2']
+                        final_outcomes_export['W3'] = final_outcomes['W3']
+                        final_outcomes_export['D1'] = final_outcomes['D1']
+                        final_outcomes_export['D2'] = final_outcomes['D2']
+                        final_outcomes_export['UTIL'] = final_outcomes['UTIL']
+                        final_outcomes_export['G'] = final_outcomes['G']
+                        final_outcomes_export['Salary'] = final_outcomes['Cost']
+                        final_outcomes_export['Own'] = final_outcomes['Own']
+                        final_outcomes_export['Proj'] = final_outcomes['Proj']
+                        
                         final_outcomes_export['C1'].replace(dkid_dict, inplace=True)
                         final_outcomes_export['C2'].replace(dkid_dict, inplace=True)
                         final_outcomes_export['W1'].replace(dkid_dict, inplace=True)
@@ -529,16 +525,32 @@ with tab2:
                         final_outcomes_export['UTIL'].replace(dkid_dict, inplace=True)
                         final_outcomes_export['G'].replace(dkid_dict, inplace=True)
                     elif site_var1 == 'Fanduel':
-                        final_outcomes_export['QB'].replace(fdid_dict, inplace=True)
-                        final_outcomes_export['RB1'].replace(fdid_dict, inplace=True)
-                        final_outcomes_export['RB2'].replace(fdid_dict, inplace=True)
-                        final_outcomes_export['WR1'].replace(fdid_dict, inplace=True)
-                        final_outcomes_export['WR2'].replace(fdid_dict, inplace=True)
-                        final_outcomes_export['WR3'].replace(fdid_dict, inplace=True)
-                        final_outcomes_export['TE'].replace(fdid_dict, inplace=True)
-                        final_outcomes_export['UTIL'].replace(fdid_dict, inplace=True)
-                        final_outcomes_export['DST'].replace(fdid_dict, inplace=True)
-
+                        final_outcomes = portfolio[['C1', 'C2', 'W1', 'W2', 'D1', 'D2', 'UTIL1', 'UTIL2', 'G', 'Cost', 'Proj', 'Own']]
+                        
+                        final_outcomes_export = pd.DataFrame()
+                        final_outcomes_export['C1'] = final_outcomes['C1']
+                        final_outcomes_export['C2'] = final_outcomes['C2']
+                        final_outcomes_export['W1'] = final_outcomes['W1']
+                        final_outcomes_export['W2'] = final_outcomes['W2']
+                        final_outcomes_export['D1'] = final_outcomes['D1']
+                        final_outcomes_export['D2'] = final_outcomes['D2']
+                        final_outcomes_export['UTIL1'] = final_outcomes['UTIL1']
+                        final_outcomes_export['UTIL2'] = final_outcomes['UTIL2']
+                        final_outcomes_export['G'] = final_outcomes['G']
+                        final_outcomes_export['Salary'] = final_outcomes['Cost']
+                        final_outcomes_export['Own'] = final_outcomes['Own']
+                        final_outcomes_export['Proj'] = final_outcomes['Proj']
+                        
+                        final_outcomes_export['C1'].replace(dkid_dict, inplace=True)
+                        final_outcomes_export['C2'].replace(dkid_dict, inplace=True)
+                        final_outcomes_export['W1'].replace(dkid_dict, inplace=True)
+                        final_outcomes_export['W2'].replace(dkid_dict, inplace=True)
+                        final_outcomes_export['D1'].replace(dkid_dict, inplace=True)
+                        final_outcomes_export['D2'].replace(dkid_dict, inplace=True)
+                        final_outcomes_export['UTIL1'].replace(dkid_dict, inplace=True)
+                        final_outcomes_export['UTIL2'].replace(dkid_dict, inplace=True)
+                        final_outcomes_export['G'].replace(dkid_dict, inplace=True)
+                    
                     player_freq = pd.DataFrame(np.column_stack(np.unique(portfolio.iloc[:,0:8].values, return_counts=True)),
                                         columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
                     player_freq['Freq'] = player_freq['Freq'].astype(int)
@@ -559,7 +571,7 @@ with tab2:
                     st.download_button(
                         label="Export Optimals",
                         data=convert_df_to_csv(final_outcomes_export),
-                        file_name='NFL_optimals_export.csv',
+                        file_name='NHL_optimals_export.csv',
                         mime='text/csv',
                     )
                 with freq_container: