full mongo integration

app.py

@@ -97,16 +97,10 @@ def init_baselines():
     raw_display.replace('#DIV/0!', np.nan, inplace=True)
     game_model = raw_display.dropna()
 
-    try:
-        sh = gcservice_account.open_by_url(NBA_Data)
-        worksheet = sh.worksheet('DK_Build_Up')
-        raw_display = pd.DataFrame(worksheet.get_all_records())
-        
-    except:
-        sh = gcservice_account2.open_by_url(NBA_Data)
-        worksheet = sh.worksheet('DK_Build_Up')
-        raw_display = pd.DataFrame(worksheet.get_all_records())
+    collection = db["Player_Stats"] 
+    cursor = collection.find()
 
+    raw_display = pd.DataFrame(list(cursor))
     raw_display.replace('', np.nan, inplace=True)
     raw_display = raw_display.rename(columns={"Name": "Player"})
     raw_baselines = raw_display[['Player', 'Position', 'Team', 'Opp', 'Minutes', 'FGM', 'FGA', 'FG2M', 'FG2A', 'Threes', 'FG3A', 'FTM', 'FTA', 'TRB', 'AST', 'STL', 'BLK', 'TOV', 'PRA', 'PR', 'PA', 'RA']]
@@ -125,14 +119,22 @@ def init_baselines():
     worksheet = sh.worksheet('Timestamp')
     timestamp = worksheet.acell('A1').value
 
-    worksheet = sh.worksheet('Prop_Frame')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
+    collection = db["Prop_Trends"] 
+    cursor = collection.find()
+
+    raw_display = pd.DataFrame(list(cursor))
     raw_display.replace('', np.nan, inplace=True)
+    raw_display = raw_display[['Name', 'over_prop', 'over_line', 'under_prop', 'under_line', 'OddsType', 'PropType', 'No Vig', 'Team', 'L5 Success', 'L10_Success', 'L20_success', 'L10 Avg', 'Projection',
+                               'Proj Diff', 'Matchup Boost', 'Implied Over', 'Trending Over', 'Over Edge', 'Implied Under', 'Trending Under', 'Under Edge']]
     raw_display = raw_display.rename(columns={"Name": "Player", "OddsType": "book", "PropType": "prop_type"})
     prop_frame = raw_display.dropna(subset='Player')
     
-    worksheet = sh.worksheet('Pick6_ingest')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
+    collection = db["Pick6_Trends"] 
+    cursor = collection.find()
+
+    raw_display = pd.DataFrame(list(cursor))
+    raw_display = raw_display[['Player', 'over_prop', 'over_line', 'under_prop', 'under_line', 'book', 'prop_type', 'No Vig', 'Team', 'L5 Success', 'L10_Success', 'L20_success', 'L10 Avg', 'Projection',
+                               'Proj Diff', 'Matchup Boost', 'Implied Over', 'Trending Over', 'Over Edge', 'Implied Under', 'Trending Under', 'Under Edge']]
     pick_frame = raw_display.drop_duplicates(subset=['Player', 'prop_type'], keep='first')
     pick_frame = pick_frame.reset_index(drop=True)