James McCool commited on
Commit
02183a0
·
1 Parent(s): 3dc7dac

Added backlog option to display, collection limit of 10k on seed frame

Browse files
Files changed (1) hide show
  1. app.py +16 -14
app.py CHANGED
@@ -63,7 +63,6 @@ def load_overall_stats():
63
  worksheet = sh.worksheet('DK_Build_Up')
64
  raw_display = pd.DataFrame(worksheet.get_all_records())
65
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
66
- raw_display.replace("", 'Welp', inplace=True)
67
  raw_display = raw_display.loc[raw_display['Salary'] > 0]
68
  raw_display = raw_display.loc[raw_display['Median'] > 0]
69
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
@@ -72,7 +71,6 @@ def load_overall_stats():
72
  worksheet = sh.worksheet('FD_Build_Up')
73
  raw_display = pd.DataFrame(worksheet.get_all_records())
74
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
75
- raw_display.replace("", 'Welp', inplace=True)
76
  raw_display = raw_display.loc[raw_display['Median'] > 0]
77
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
78
  fd_raw = raw_display.sort_values(by='Median', ascending=False)
@@ -80,7 +78,6 @@ def load_overall_stats():
80
  worksheet = sh.worksheet('Secondary_DK_Build')
81
  raw_display = pd.DataFrame(worksheet.get_all_records())
82
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
83
- raw_display.replace("", 'Welp', inplace=True)
84
  raw_display = raw_display.loc[raw_display['Median'] > 0]
85
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
86
  dk_raw_sec = raw_display.sort_values(by='Median', ascending=False)
@@ -88,31 +85,33 @@ def load_overall_stats():
88
  worksheet = sh.worksheet('Secondary_FD_Build')
89
  raw_display = pd.DataFrame(worksheet.get_all_records())
90
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
91
- raw_display.replace("", 'Welp', inplace=True)
92
  raw_display = raw_display.loc[raw_display['Median'] > 0]
93
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
94
  fd_raw_sec = raw_display.sort_values(by='Median', ascending=False)
95
 
96
  worksheet = sh.worksheet('Player_Level_ROO')
97
  raw_display = pd.DataFrame(worksheet.get_all_records())
98
- raw_display.replace("", 'Welp', inplace=True)
99
  raw_display = raw_display.loc[raw_display['Median'] > 0]
100
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
101
  roo_raw = raw_display.sort_values(by='Median', ascending=False)
102
 
103
  timestamp = raw_display['timestamp'].values[0]
104
 
105
- return dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp
 
 
 
 
106
 
107
  @st.cache_data(ttl = 300)
108
  def init_DK_lineups():
109
 
110
  collection = db["DK_NBA_seed_frame"]
111
- cursor = collection.find()
112
 
113
  raw_display = pd.DataFrame(list(cursor))
114
  raw_display = raw_display[['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
115
- DK_seed = raw_display.head(10000).to_numpy()
116
 
117
  return DK_seed
118
 
@@ -120,11 +119,11 @@ def init_DK_lineups():
120
  def init_FD_lineups():
121
 
122
  collection = db["FD_NBA_seed_frame"]
123
- cursor = collection.find()
124
 
125
  raw_display = pd.DataFrame(list(cursor))
126
  raw_display = raw_display[['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
127
- FD_seed = raw_display.head(10000).to_numpy()
128
 
129
  return FD_seed
130
 
@@ -136,7 +135,7 @@ def convert_df(array):
136
  array = pd.DataFrame(array, columns=column_names)
137
  return array.to_csv().encode('utf-8')
138
 
139
- dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
140
  dk_lineups = init_DK_lineups()
141
  fd_lineups = init_FD_lineups()
142
  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
@@ -151,7 +150,7 @@ with tab1:
151
  st.info(t_stamp)
152
  if st.button("Load/Reset Data", key='reset1'):
153
  st.cache_data.clear()
154
- dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
155
  dk_lineups = init_DK_lineups()
156
  fd_lineups = init_FD_lineups()
157
  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
@@ -162,11 +161,14 @@ with tab1:
162
  site_baselines = roo_raw[roo_raw['site'] == 'Draftkings']
163
  elif site_var2 == 'Fanduel':
164
  site_baselines = roo_raw[roo_raw['site'] == 'Fanduel']
165
- slate_split = st.radio("Are you viewing the main slate or the secondary slate?", ('Main Slate', 'Secondary'), key='slate_split')
166
  if slate_split == 'Main Slate':
167
  raw_baselines = site_baselines[site_baselines['slate'] == 'Main Slate']
168
  elif slate_split == 'Secondary':
169
  raw_baselines = site_baselines[site_baselines['slate'] == 'Secondary Slate']
 
 
 
170
  split_var2 = st.radio("Are you running the full slate or certain games?", ('Full Slate Run', 'Specific Games'), key='split_var2')
171
  if split_var2 == 'Specific Games':
172
  team_var2 = st.multiselect('Which teams would you like to include in the ROO?', options = raw_baselines['Team'].unique(), key='team_var2')
@@ -206,7 +208,7 @@ with tab2:
206
  with col1:
207
  if st.button("Load/Reset Data", key='reset2'):
208
  st.cache_data.clear()
209
- dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
210
  dk_lineups = init_DK_lineups()
211
  fd_lineups = init_FD_lineups()
212
  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
 
63
  worksheet = sh.worksheet('DK_Build_Up')
64
  raw_display = pd.DataFrame(worksheet.get_all_records())
65
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
 
66
  raw_display = raw_display.loc[raw_display['Salary'] > 0]
67
  raw_display = raw_display.loc[raw_display['Median'] > 0]
68
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
 
71
  worksheet = sh.worksheet('FD_Build_Up')
72
  raw_display = pd.DataFrame(worksheet.get_all_records())
73
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
 
74
  raw_display = raw_display.loc[raw_display['Median'] > 0]
75
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
76
  fd_raw = raw_display.sort_values(by='Median', ascending=False)
 
78
  worksheet = sh.worksheet('Secondary_DK_Build')
79
  raw_display = pd.DataFrame(worksheet.get_all_records())
80
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
 
81
  raw_display = raw_display.loc[raw_display['Median'] > 0]
82
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
83
  dk_raw_sec = raw_display.sort_values(by='Median', ascending=False)
 
85
  worksheet = sh.worksheet('Secondary_FD_Build')
86
  raw_display = pd.DataFrame(worksheet.get_all_records())
87
  raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True)
 
88
  raw_display = raw_display.loc[raw_display['Median'] > 0]
89
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
90
  fd_raw_sec = raw_display.sort_values(by='Median', ascending=False)
91
 
92
  worksheet = sh.worksheet('Player_Level_ROO')
93
  raw_display = pd.DataFrame(worksheet.get_all_records())
 
94
  raw_display = raw_display.loc[raw_display['Median'] > 0]
95
  raw_display = raw_display.apply(pd.to_numeric, errors='ignore')
96
  roo_raw = raw_display.sort_values(by='Median', ascending=False)
97
 
98
  timestamp = raw_display['timestamp'].values[0]
99
 
100
+ worksheet = sh.worksheet('ROO_backlog')
101
+ raw_display = pd.DataFrame(worksheet.get_all_records())
102
+ roo_backlog = raw_display.sort_values(by='Median', ascending=False)
103
+
104
+ return dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp, roo_backlog
105
 
106
  @st.cache_data(ttl = 300)
107
  def init_DK_lineups():
108
 
109
  collection = db["DK_NBA_seed_frame"]
110
+ cursor = collection.find().limit(10000)
111
 
112
  raw_display = pd.DataFrame(list(cursor))
113
  raw_display = raw_display[['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
114
+ DK_seed = raw_display.to_numpy()
115
 
116
  return DK_seed
117
 
 
119
  def init_FD_lineups():
120
 
121
  collection = db["FD_NBA_seed_frame"]
122
+ cursor = collection.find().limit(10000)
123
 
124
  raw_display = pd.DataFrame(list(cursor))
125
  raw_display = raw_display[['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
126
+ FD_seed = raw_display.to_numpy()
127
 
128
  return FD_seed
129
 
 
135
  array = pd.DataFrame(array, columns=column_names)
136
  return array.to_csv().encode('utf-8')
137
 
138
+ dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp, roo_backlog = load_overall_stats()
139
  dk_lineups = init_DK_lineups()
140
  fd_lineups = init_FD_lineups()
141
  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
 
150
  st.info(t_stamp)
151
  if st.button("Load/Reset Data", key='reset1'):
152
  st.cache_data.clear()
153
+ dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp, roo_backlog = load_overall_stats()
154
  dk_lineups = init_DK_lineups()
155
  fd_lineups = init_FD_lineups()
156
  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
 
161
  site_baselines = roo_raw[roo_raw['site'] == 'Draftkings']
162
  elif site_var2 == 'Fanduel':
163
  site_baselines = roo_raw[roo_raw['site'] == 'Fanduel']
164
+ slate_split = st.radio("Are you viewing the main slate or the secondary slate?", ('Main Slate', 'Secondary', 'Backlog'), key='slate_split')
165
  if slate_split == 'Main Slate':
166
  raw_baselines = site_baselines[site_baselines['slate'] == 'Main Slate']
167
  elif slate_split == 'Secondary':
168
  raw_baselines = site_baselines[site_baselines['slate'] == 'Secondary Slate']
169
+ elif slate_split == 'Backlog':
170
+ raw_baselines = roo_backlog
171
+ raw_baselines = raw_baselines[site_baselines['site'] == site_var2]
172
  split_var2 = st.radio("Are you running the full slate or certain games?", ('Full Slate Run', 'Specific Games'), key='split_var2')
173
  if split_var2 == 'Specific Games':
174
  team_var2 = st.multiselect('Which teams would you like to include in the ROO?', options = raw_baselines['Team'].unique(), key='team_var2')
 
208
  with col1:
209
  if st.button("Load/Reset Data", key='reset2'):
210
  st.cache_data.clear()
211
+ dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp, roo_backlog = load_overall_stats()
212
  dk_lineups = init_DK_lineups()
213
  fd_lineups = init_FD_lineups()
214
  t_stamp = f"Last Update: " + str(timestamp) + f" CST"