Update app.py

app.py

@@ -62,8 +62,10 @@ def grab_baseline_stuff():
     fd_raw_proj['Median'] = fd_raw_proj['Median'].astype(float)
     dk_raw_proj['Own'] = dk_raw_proj['Median'].astype(float)
     fd_raw_proj['Own'] = fd_raw_proj['Median'].astype(float)
-    dk_ids = dict(zip(dk_raw_proj['Player'], dk_raw_proj['player_id']))
-    fd_ids = dict(zip(fd_raw_proj['Player'], fd_raw_proj['player_id']))
+    dk_raw_proj['Name_ID'] = dk_raw_proj['Player'] + '(' + dk_raw_proj['player_id'].astype(str) + ')'
+    fd_raw_proj['Name_ID'] = fd_raw_proj['player_id'].astype(str) + ':' + fd_raw_proj['Player']
+    dk_ids = dict(zip(dk_raw_proj['Player'], dk_raw_proj['Name_ID']))
+    fd_ids = dict(zip(fd_raw_proj['Player'], fd_raw_proj['Name_ID']))
     
     worksheet = sh.worksheet('Timestamp')
     timestamp = worksheet.acell('A1').value
@@ -148,17 +150,17 @@ with tab2:
                 ownframe['Own%'] = np.where((ownframe['Position'] == 'G') & (ownframe['Own'] - ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean() >= 0), ownframe['Own'] * (10 * (ownframe['Own'] - ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean())/100) + ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean(), ownframe['Own'])
                 ownframe['Own%'] = np.where((ownframe['Position'] != 'G') & (ownframe['Own'] - ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean() >= 0), ownframe['Own'] * (5 * (ownframe['Own'] - ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean())/100) + ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean(), ownframe['Own%'])
                 ownframe['Own%'] = np.where(ownframe['Own%'] > 75, 75, ownframe['Own%'])
-                ownframe['Own'] = ownframe['Own%'] * (800 / ownframe['Own%'].sum())
+                ownframe['Own'] = ownframe['Own%'] * (900 / ownframe['Own%'].sum())
         if contest_var1 == 'Small Field GPP':
                 ownframe['Own%'] = np.where((ownframe['Position'] == 'G') & (ownframe['Own'] - ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean() >= 0), ownframe['Own'] * (6 * (ownframe['Own'] - ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean())/100) + ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean(), ownframe['Own'])
                 ownframe['Own%'] = np.where((ownframe['Position'] != 'G') & (ownframe['Own'] - ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean() >= 0), ownframe['Own'] * (3 * (ownframe['Own'] - ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean())/100) + ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean(), ownframe['Own%'])
                 ownframe['Own%'] = np.where(ownframe['Own%'] > 75, 75, ownframe['Own%'])
-                ownframe['Own'] = ownframe['Own%'] * (800 / ownframe['Own%'].sum())
+                ownframe['Own'] = ownframe['Own%'] * (900 / ownframe['Own%'].sum())
         if contest_var1 == 'Large Field GPP':
                 ownframe['Own%'] = np.where((ownframe['Position'] == 'G') & (ownframe['Own'] - ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean() >= 0), ownframe['Own'] * (3 * (ownframe['Own'] - ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean())/100) + ownframe.loc[ownframe['Position'] == 'G', 'Own'].mean(), ownframe['Own'])
                 ownframe['Own%'] = np.where((ownframe['Position'] != 'G') & (ownframe['Own'] - ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean() >= 0), ownframe['Own'] * (1.5 * (ownframe['Own'] - ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean())/100) + ownframe.loc[ownframe['Position'] != 'G', 'Own'].mean(), ownframe['Own%'])
                 ownframe['Own%'] = np.where(ownframe['Own%'] > 75, 75, ownframe['Own%'])
-                ownframe['Own'] = ownframe['Own%'] * (800 / ownframe['Own%'].sum())
+                ownframe['Own'] = ownframe['Own%'] * (900 / ownframe['Own%'].sum())
         raw_baselines = ownframe[['Player', 'Salary', 'Position', 'Team', 'Opp', 'Line', 'PP Unit', 'Median', 'Own']]
         raw_baselines = raw_baselines.sort_values(by='Median', ascending=False)
         raw_baselines['lock'] = np.where(raw_baselines['Player'].isin(lock_var1), 1, 0)