James McCool commited on
Commit
f32fab3
·
1 Parent(s): be18b60

dropped dupes on QB and non-qb stats based on player/position

Browse files
Files changed (1) hide show
  1. app.py +2 -1
app.py CHANGED
@@ -138,7 +138,9 @@ with tab2:
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  st.cache_data.clear()
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  game_model, overall_stats, timestamp, prop_frame, prop_trends, pick_frame = init_baselines()
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  qb_stats = overall_stats[overall_stats['Position'] == 'QB']
 
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  non_qb_stats = overall_stats[overall_stats['Position'] != 'QB']
 
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  team_dict = dict(zip(prop_frame['Player'], prop_frame['Team']))
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  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
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  split_var1 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var1')
@@ -147,7 +149,6 @@ with tab2:
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  elif split_var1 == 'All':
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  team_var1 = qb_stats.Team.values.tolist()
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  qb_stats = qb_stats[qb_stats['Team'].isin(team_var1)]
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- qb_stats = qb_stats.drop_duplicates(subset='Player')
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  qb_stats_disp = qb_stats.set_index('Player')
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  qb_stats_disp = qb_stats_disp.sort_values(by='PPR', ascending=False)
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  st.dataframe(qb_stats_disp.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height = 1000, use_container_width = True)
 
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  st.cache_data.clear()
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  game_model, overall_stats, timestamp, prop_frame, prop_trends, pick_frame = init_baselines()
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  qb_stats = overall_stats[overall_stats['Position'] == 'QB']
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+ qb_stats = qb_stats.drop_duplicates(subset=['Player', 'Position'])
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  non_qb_stats = overall_stats[overall_stats['Position'] != 'QB']
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+ non_qb_stats = non_qb_stats.drop_duplicates(subset=['Player', 'Position'])
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  team_dict = dict(zip(prop_frame['Player'], prop_frame['Team']))
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  t_stamp = f"Last Update: " + str(timestamp) + f" CST"
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  split_var1 = st.radio("Would you like to view all teams or specific ones?", ('All', 'Specific Teams'), key='split_var1')
 
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  elif split_var1 == 'All':
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  team_var1 = qb_stats.Team.values.tolist()
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  qb_stats = qb_stats[qb_stats['Team'].isin(team_var1)]
 
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  qb_stats_disp = qb_stats.set_index('Player')
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  qb_stats_disp = qb_stats_disp.sort_values(by='PPR', ascending=False)
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  st.dataframe(qb_stats_disp.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height = 1000, use_container_width = True)