James McCool
commited on
Commit
·
772166a
1
Parent(s):
77d71e0
Update duplicate calculation logic in app.py
Browse files- Modified the grouping for duplicate entries from 'sorted' to 'actual_fpts' to enhance accuracy in counting duplicates based on actual fantasy points.
- Ensured consistent application of this change across relevant sections of the code.
app.py
CHANGED
@@ -429,7 +429,7 @@ if selected_tab == 'Data Load':
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working_df['sorted'] = working_df[st.session_state['player_columns']].apply(
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lambda row: ','.join(sorted(row.values)), axis=1
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)
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-
working_df['dupes'] = working_df.groupby('
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# Vectorized unique calculations
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working_df['uniques'] = working_df.groupby('BaseName')['dupes'].transform(
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@@ -527,7 +527,7 @@ if selected_tab == 'Data Load':
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working_df['sorted'] = working_df[st.session_state['player_columns']].apply(
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lambda row: ','.join(sorted(row.values)), axis=1
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)
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-
working_df['dupes'] = working_df.groupby('
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# Vectorized unique calculations
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working_df['uniques'] = working_df.groupby('BaseName')['dupes'].transform(
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working_df['sorted'] = working_df[st.session_state['player_columns']].apply(
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lambda row: ','.join(sorted(row.values)), axis=1
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)
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+
working_df['dupes'] = working_df.groupby('actual_fpts').transform('size')
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# Vectorized unique calculations
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working_df['uniques'] = working_df.groupby('BaseName')['dupes'].transform(
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working_df['sorted'] = working_df[st.session_state['player_columns']].apply(
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lambda row: ','.join(sorted(row.values)), axis=1
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)
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+
working_df['dupes'] = working_df.groupby('actual_fpts').transform('size')
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# Vectorized unique calculations
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working_df['uniques'] = working_df.groupby('BaseName')['dupes'].transform(
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