James McCool
commited on
Commit
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c744629
1
Parent(s):
c9fd1e3
Add stack comparison feature in app.py and create_stack_comparison.py
Browse files- Introduced a new function, create_stack_comparison, to facilitate the comparison of stack exposures based on user selections.
- Updated app.py to include a form for selecting stacks to compare, enhancing user interaction and data analysis capabilities.
- Improved player exposure comparison by adding position filtering logic and ensuring accurate data representation in the displayed DataFrame.
- app.py +40 -14
- global_func/create_player_comparison.py +1 -1
- global_func/create_stack_comparison.py +22 -0
app.py
CHANGED
@@ -64,6 +64,7 @@ from global_func.create_stack_size_exposures import create_stack_size_exposures
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from global_func.create_general_exposures import create_general_exposures
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from global_func.grab_contest_data import grab_contest_data
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from global_func.create_player_comparison import create_player_comparison
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def is_valid_input(file):
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if isinstance(file, pd.DataFrame):
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@@ -438,6 +439,16 @@ with tab2:
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comp_player_select = comp_player_select
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if comp_player_var == 'Yes':
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player_exp_comp = create_player_comparison(st.session_state['display_contest_info'], st.session_state['player_columns'], comp_player_select)
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st.dataframe(player_exp_comp.style.background_gradient(cmap='RdYlGn', axis=0).format(formatter='{:.2%}', subset=player_exp_comp.select_dtypes(include=['number']).columns), hide_index=True)
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else:
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if st.session_state['entry_parse_var'] == 'All':
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@@ -476,21 +487,36 @@ with tab2:
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format(formatter='{:.2%}', subset=st.session_state['player_frame'].iloc[:, 2:].select_dtypes(include=['number']).columns),
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hide_index=True)
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with tab2:
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else:
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-
st.session_state['
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with tab3:
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if st.session_state['entry_parse_var'] == 'All':
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from global_func.create_general_exposures import create_general_exposures
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from global_func.grab_contest_data import grab_contest_data
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from global_func.create_player_comparison import create_player_comparison
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from global_func.create_stack_comparison import create_stack_comparison
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def is_valid_input(file):
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if isinstance(file, pd.DataFrame):
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comp_player_select = comp_player_select
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if comp_player_var == 'Yes':
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player_exp_comp = create_player_comparison(st.session_state['display_contest_info'], st.session_state['player_columns'], comp_player_select)
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hold_frame = player_exp_comp.copy()
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if sport_select == 'GOLF':
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hold_frame['Pos'] = 'G'
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else:
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hold_frame['Pos'] = hold_frame['Player'].map(st.session_state['map_dict']['pos_map'])
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player_exp_comp.insert(1, 'Pos', hold_frame['Pos'])
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player_exp_comp = player_exp_comp.dropna(subset=['Pos'])
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if pos_select:
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position_mask = player_exp_comp['Pos'].apply(lambda x: any(pos in x for pos in pos_select))
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player_exp_comp = player_exp_comp[position_mask]
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st.dataframe(player_exp_comp.style.background_gradient(cmap='RdYlGn', axis=0).format(formatter='{:.2%}', subset=player_exp_comp.select_dtypes(include=['number']).columns), hide_index=True)
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else:
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if st.session_state['entry_parse_var'] == 'All':
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format(formatter='{:.2%}', subset=st.session_state['player_frame'].iloc[:, 2:].select_dtypes(include=['number']).columns),
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hide_index=True)
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with tab2:
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with st.form(key='stack_exp_comp_form'):
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col1, col2 = st.columns(2)
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with col1:
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comp_stack_var = st.selectbox("Would you like to compare with anyone?", ['No', 'Yes'], key='comp_stack_var')
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with col2:
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comp_stack_select = st.multiselect("Select stacks to compare with:", st.session_state['display_contest_info']['BaseName'].sort_values().unique(), key='comp_stack_select')
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submitted = st.form_submit_button("Submit")
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if submitted:
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if comp_stack_var == 'No':
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comp_stack_select = None
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else:
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comp_stack_select = comp_stack_select
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if comp_stack_var == 'Yes':
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stack_exp_comp = create_stack_comparison(st.session_state['display_contest_info'], comp_stack_select)
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st.dataframe(stack_exp_comp.style.background_gradient(cmap='RdYlGn', axis=0).format(formatter='{:.2%}', subset=stack_exp_comp.select_dtypes(include=['number']).columns), hide_index=True)
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else:
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if st.session_state['entry_parse_var'] == 'All':
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st.session_state['stack_frame'] = create_stack_exposures(st.session_state['display_contest_info'])
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st.dataframe(st.session_state['stack_frame'].
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sort_values(by='Exposure Overall', ascending=False).
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style.background_gradient(cmap='RdYlGn').
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format(formatter='{:.2%}', subset=st.session_state['stack_frame'].iloc[:, 1:].select_dtypes(include=['number']).columns),
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hide_index=True)
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else:
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st.session_state['stack_frame'] = create_stack_exposures(st.session_state['display_contest_info'], st.session_state['entry_names'])
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st.dataframe(st.session_state['stack_frame'].
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sort_values(by='Exposure Overall', ascending=False).
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style.background_gradient(cmap='RdYlGn').
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format(formatter='{:.2%}', subset=st.session_state['stack_frame'].iloc[:, 1:].select_dtypes(include=['number']).columns),
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hide_index=True)
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with tab3:
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if st.session_state['entry_parse_var'] == 'All':
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global_func/create_player_comparison.py
CHANGED
@@ -19,4 +19,4 @@ def create_player_comparison(df: pd.DataFrame, player_columns: list, entrants: l
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set_frame = set_frame.rename(columns={'Percent': f'Exposure {each_user}'})
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player_frame = pd.merge(player_frame, set_frame, on='Player', how='outer')
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return player_frame
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set_frame = set_frame.rename(columns={'Percent': f'Exposure {each_user}'})
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player_frame = pd.merge(player_frame, set_frame, on='Player', how='outer')
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return player_frame.sort_values(by='Exposure Overall', ascending=False)
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global_func/create_stack_comparison.py
ADDED
@@ -0,0 +1,22 @@
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import pandas as pd
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def create_stack_comparison(df: pd.DataFrame, entrants: list):
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overall_players = pd.Series(list(df['stack'])).value_counts()
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contest_len = len(df)
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set_frame = overall_players.to_frame().reset_index().rename(columns={'index': 'Player', 'count': 'Count'})
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set_frame['Percent'] = set_frame['Count'] / contest_len
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set_frame = set_frame[['Player', 'Percent']]
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set_frame = set_frame.rename(columns={'Percent': f'Exposure Overall'})
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player_frame = set_frame
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for each_user in entrants:
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overall_players = pd.Series(list(df[df['BaseName'] == each_user]['stack'])).value_counts()
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set_frame = overall_players.to_frame().reset_index().rename(columns={'index': 'Player', 'count': 'Count'})
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set_frame['Percent'] = set_frame['Count'] / len(df[df['BaseName'] == each_user])
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set_frame = set_frame[['Player', 'Percent']]
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set_frame = set_frame.rename(columns={'Percent': f'Exposure {each_user}'})
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player_frame = pd.merge(player_frame, set_frame, on='Player', how='outer')
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return player_frame.sort_values(by='Exposure Overall', ascending=False)
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