James McCool commited on
Commit
56ac316
·
1 Parent(s): 978080b

Refactor app.py and load_contest_file.py for improved data handling

Browse files

- Removed unnecessary debug output in app.py to streamline the user interface.
- Updated load_contest_file.py to drop the 'Lineup' and 'Remove' columns after processing, enhancing data organization in the cleaned dataframe.
- These changes contribute to ongoing efforts to refine data handling and improve user experience within the application.

Files changed (2) hide show
  1. app.py +0 -5
  2. global_func/load_contest_file.py +1 -0
app.py CHANGED
@@ -98,11 +98,6 @@ with tab1:
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  st.session_state['salary_dict'] = dict(zip(st.session_state['salary_df']['Player'], st.session_state['salary_df']['Salary']))
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  st.session_state['team_dict'] = dict(zip(st.session_state['team_df']['Player'], st.session_state['team_df']['Team']))
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  st.session_state['pos_dict'] = dict(zip(st.session_state['pos_df']['Player'], st.session_state['pos_df']['Pos']))
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- st.write(st.session_state['ownership_dict'])
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- st.write(st.session_state['actual_dict'])
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- st.write(st.session_state['salary_dict'])
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- st.write(st.session_state['team_dict'])
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- st.write(st.session_state['pos_dict'])
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  with tab2:
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  excluded_cols = ['BaseName', 'EntryCount']
 
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  st.session_state['salary_dict'] = dict(zip(st.session_state['salary_df']['Player'], st.session_state['salary_df']['Salary']))
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  st.session_state['team_dict'] = dict(zip(st.session_state['team_df']['Player'], st.session_state['team_df']['Team']))
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  st.session_state['pos_dict'] = dict(zip(st.session_state['pos_df']['Player'], st.session_state['pos_df']['Pos']))
 
 
 
 
 
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  with tab2:
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  excluded_cols = ['BaseName', 'EntryCount']
global_func/load_contest_file.py CHANGED
@@ -43,6 +43,7 @@ def load_contest_file(upload, sport):
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  cleaned_df = df[['BaseName', 'EntryCount', 'Lineup']]
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  cleaned_df['Lineup'] = cleaned_df['Lineup'].replace(pos_list, value=',', regex=True)
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  cleaned_df[['Remove', '1B', '2B', '3B', 'C', 'OF1', 'OF2', 'OF3', 'P1', 'P2', 'SS']] = cleaned_df['Lineup'].str.split(',', expand=True)
 
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  # Get unique entry names
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  entry_list = list(set(df['BaseName']))
 
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  cleaned_df = df[['BaseName', 'EntryCount', 'Lineup']]
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  cleaned_df['Lineup'] = cleaned_df['Lineup'].replace(pos_list, value=',', regex=True)
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  cleaned_df[['Remove', '1B', '2B', '3B', 'C', 'OF1', 'OF2', 'OF3', 'P1', 'P2', 'SS']] = cleaned_df['Lineup'].str.split(',', expand=True)
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+ cleaned_df = cleaned_df.drop(columns=['Lineup', 'Remove'])
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  # Get unique entry names
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  entry_list = list(set(df['BaseName']))