Transferred DFS data to mongo, established connections

app.py

@@ -55,50 +55,68 @@ fd_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'sal
 
 @st.cache_data(ttl=300)
 def load_overall_stats():
-    try:
-        sh = gcservice_account.open_by_url(NBA_Data)
-    except:
-        sh = gcservice_account2.open_by_url(NBA_Data)  
-    
-    worksheet = sh.worksheet('DK_Build_Up')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
-    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
-    raw_display = raw_display.loc[raw_display['Salary'] > 0]
+    collection = db["DK_Player_Stats"] 
+    cursor = collection.find()
+
+    raw_display = pd.DataFrame(list(cursor))
+    raw_display = raw_display[['Name', 'Salary', 'Position', 'Team', 'Opp', 'Minutes', 'FGM', 'FGA', 'FG2M', 'FG2A', 'Threes', 'FG3A', 'FTM', 'FTA', 'TRB', 'AST', 'STL', 'BLK', 'TOV', '2P', '3P', 'FT',
+                               'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
+    raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
     dk_raw = raw_display.sort_values(by='Median', ascending=False)
     
-    worksheet = sh.worksheet('FD_Build_Up')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
-    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
+    collection = db["FD_Player_Stats"] 
+    cursor = collection.find()
+
+    raw_display = pd.DataFrame(list(cursor))
+    raw_display = raw_display[['Name', 'Salary', 'Position', 'Team', 'Opp', 'Minutes', 'FGM', 'FGA', 'FG2M', 'FG2A', 'Threes', 'FG3A', 'FTM', 'FTA', 'TRB', 'AST', 'STL', 'BLK', 'TOV', '2P', '3P', 'FT',
+                               'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
+    raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
     fd_raw = raw_display.sort_values(by='Median', ascending=False)
     
-    worksheet = sh.worksheet('Secondary_DK_Build')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
-    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
+    collection = db["Secondary_DK_Player_Stats"] 
+    cursor = collection.find()
+
+    raw_display = pd.DataFrame(list(cursor))
+    raw_display = raw_display[['Name', 'Salary', 'Position', 'Team', 'Opp', 'Minutes', 'FGM', 'FGA', 'FG2M', 'FG2A', 'Threes', 'FG3A', 'FTM', 'FTA', 'TRB', 'AST', 'STL', 'BLK', 'TOV', '2P', '3P', 'FT',
+                               'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
+    raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
     dk_raw_sec = raw_display.sort_values(by='Median', ascending=False)
     
-    worksheet = sh.worksheet('Secondary_FD_Build')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
-    raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
+    collection = db["Secondary_FD_Player_Stats"] 
+    cursor = collection.find()
+
+    raw_display = pd.DataFrame(list(cursor))
+    raw_display = raw_display[['Name', 'Salary', 'Position', 'Team', 'Opp', 'Minutes', 'FGM', 'FGA', 'FG2M', 'FG2A', 'Threes', 'FG3A', 'FTM', 'FTA', 'TRB', 'AST', 'STL', 'BLK', 'TOV', '2P', '3P', 'FT',
+                               'Points', 'Rebounds', 'Assists', 'PRA', 'PR', 'PA', 'RA', 'Steals', 'Blocks', 'Turnovers', 'Fantasy', 'Raw', 'Own']]
+    raw_display = raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"})
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
     fd_raw_sec = raw_display.sort_values(by='Median', ascending=False)
 
-    worksheet = sh.worksheet('Player_Level_ROO')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
+    collection = db["Player_Range_Of_Outcomes"] 
+    cursor = collection.find()
+
+    raw_display = pd.DataFrame(list(cursor))
+    raw_display = raw_display[['Player', 'Minutes', 'Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Cei', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
+                               'Own', 'Small_Own', 'Large_Own', 'Cash_Own', 'CPT_Own', 'LevX', 'ValX', 'site', 'version', 'slate', 'timestamp']]
     raw_display = raw_display.loc[raw_display['Median'] > 0]
     raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
     roo_raw = raw_display.sort_values(by='Median', ascending=False)
 
     timestamp = raw_display['timestamp'].values[0]
 
-    worksheet = sh.worksheet('ROO_Backlog')
-    raw_display = pd.DataFrame(worksheet.get_all_records())
+    collection = db["Range_Of_Outcomes_Backlog"] 
+    cursor = collection.find()
+
+    raw_display = pd.DataFrame(list(cursor))
+    raw_display = raw_display[['Player', 'Minutes', 'Proj', 'Position', 'Team', 'Opp', 'Salary', 'Floor', 'Median', 'Cei', 'Top_finish', 'Top_5_finish', 'Top_10_finish', '20+%', '4x%', '5x%', '6x%', 'GPP%',
+                               'Own', 'Small_Own', 'Large_Own', 'Cash_Own', 'CPT_Own', 'LevX', 'ValX', 'site', 'version', 'slate', 'timestamp', 'Date']]
     roo_backlog = raw_display.sort_values(by='Date', ascending=False)
     roo_backlog = roo_backlog[roo_backlog['slate'] == 'Main Slate']