Multichem commited on
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1fb647a
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1 Parent(s): d1195b4

Update app.py

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Files changed (1) hide show
  1. app.py +27 -3
app.py CHANGED
@@ -51,6 +51,7 @@ def init_conn():
51
  gcservice_account, client, db, DK_seed, FD_seed, MLB_Data = init_conn()
52
 
53
  percentages_format = {'Exposure': '{:.2%}'}
 
54
  dk_columns = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count']
55
  fd_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count']
56
 
@@ -358,19 +359,42 @@ with tab2:
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  st.session_state.player_freq['Freq'] = st.session_state.player_freq['Freq'].astype(int)
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  st.session_state.player_freq['Position'] = st.session_state.player_freq['Player'].map(maps_dict['Pos_map'])
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  st.session_state.player_freq['Salary'] = st.session_state.player_freq['Player'].map(maps_dict['Salary_map'])
361
- st.session_state.player_freq['Proj Own'] = st.session_state.player_freq['Player'].map(maps_dict['Small_Own_map']) / 100
362
  st.session_state.player_freq['Exposure'] = st.session_state.player_freq['Freq']/(1000)
363
  st.session_state.player_freq['Edge'] = st.session_state.player_freq['Exposure'] - st.session_state.player_freq['Proj Own']
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  st.session_state.player_freq['Team'] = st.session_state.player_freq['Player'].map(maps_dict['Team_map'])
 
 
 
 
 
 
 
 
 
 
 
 
 
 
365
 
366
  with st.container():
367
- tab1, tab2, tab3, tab4, tab5, tab6, tab7 = st.tabs(['Overall Exposures', 'QB Exposures', 'RB Exposures', 'WR Exposures', 'TE Exposures', 'FLEX Exposures', 'DST Exposures'])
368
  with tab1:
369
  if 'player_freq' in st.session_state:
370
- st.dataframe(st.session_state.player_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
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  st.download_button(
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  label="Export Exposures",
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  data=st.session_state.player_freq.to_csv().encode('utf-8'),
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  file_name='player_freq_export.csv',
375
  mime='text/csv',
 
 
 
 
 
 
 
 
 
376
  )
 
51
  gcservice_account, client, db, DK_seed, FD_seed, MLB_Data = init_conn()
52
 
53
  percentages_format = {'Exposure': '{:.2%}'}
54
+ freq_format = {'Exposure': '{:.2%}', 'Proj Own': '{:.2%}'}
55
  dk_columns = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count']
56
  fd_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count']
57
 
 
359
  st.session_state.player_freq['Freq'] = st.session_state.player_freq['Freq'].astype(int)
360
  st.session_state.player_freq['Position'] = st.session_state.player_freq['Player'].map(maps_dict['Pos_map'])
361
  st.session_state.player_freq['Salary'] = st.session_state.player_freq['Player'].map(maps_dict['Salary_map'])
362
+ st.session_state.player_freq['Proj Own'] = st.session_state.player_freq['Player'].map(maps_dict['Own_map']) / 100
363
  st.session_state.player_freq['Exposure'] = st.session_state.player_freq['Freq']/(1000)
364
  st.session_state.player_freq['Edge'] = st.session_state.player_freq['Exposure'] - st.session_state.player_freq['Proj Own']
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  st.session_state.player_freq['Team'] = st.session_state.player_freq['Player'].map(maps_dict['Team_map'])
366
+
367
+ if sim_site_var1 == 'Draftkings':
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+ st.session_state.sp_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:2].values, return_counts=True)),
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+ columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
370
+ elif sim_site_var1 == 'Draftkings':
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+ st.session_state.sp_freq = pd.DataFrame(np.column_stack(np.unique(st.session_state.Sim_Winner_Display.iloc[:,0:1].values, return_counts=True)),
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+ columns=['Player','Freq']).sort_values('Freq', ascending=False).reset_index(drop=True)
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+ st.session_state.sp_freq['Freq'] = st.session_state.sp_freq['Freq'].astype(int)
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+ st.session_state.sp_freq['Position'] = st.session_state.sp_freq['Player'].map(maps_dict['Pos_map'])
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+ st.session_state.sp_freq['Salary'] = st.session_state.sp_freq['Player'].map(maps_dict['Salary_map'])
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+ st.session_state.sp_freq['Proj Own'] = st.session_state.sp_freq['Player'].map(maps_dict['Own_map']) / 100
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+ st.session_state.sp_freq['Exposure'] = st.session_state.sp_freq['Freq']/(1000)
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+ st.session_state.sp_freq['Edge'] = st.session_state.sp_freq['Exposure'] - st.session_state.sp_freq['Proj Own']
379
+ st.session_state.sp_freq['Team'] = st.session_state.sp_freq['Player'].map(maps_dict['Team_map'])
380
 
381
  with st.container():
382
+ tab1, tab2, tab3, tab4 = st.tabs(['Overall Exposures', 'SP Exposures', 'Team Exposures', 'Stack Size Exposures'])
383
  with tab1:
384
  if 'player_freq' in st.session_state:
385
+ st.dataframe(st.session_state.player_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
386
  st.download_button(
387
  label="Export Exposures",
388
  data=st.session_state.player_freq.to_csv().encode('utf-8'),
389
  file_name='player_freq_export.csv',
390
  mime='text/csv',
391
+ )
392
+ with tab2:
393
+ if 'sp_freq' in st.session_state:
394
+ st.dataframe(st.session_state.sp_freq.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(freq_format, precision=2), use_container_width = True)
395
+ st.download_button(
396
+ label="Export Exposures",
397
+ data=st.session_state.sp_freq.to_csv().encode('utf-8'),
398
+ file_name='player_freq_export.csv',
399
+ mime='text/csv',
400
  )