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Update app.py
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app.py
CHANGED
@@ -37,7 +37,8 @@ gcservice_account = init_conn()
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NHL_data = 'https://docs.google.com/spreadsheets/d/1NmKa-b-2D3w7rRxwMPSchh31GKfJ1XcDI2GU8rXWnHI/edit#gid=811139250'
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percentages_format = {'Shots': '{:.2%}', 'HDCF': '{:.2%}', 'Goals': '{:.2%}', 'Assists': '{:.2%}', 'Blocks': '{:.2%}',
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'L14_Shots': '{:.2%}', 'L14_HDCF': '{:.2%}', 'L14_Goals': '{:.2%}', 'L14_Assists': '{:.2%}',
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@st.cache_resource(ttl = 599)
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def init_baselines():
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@@ -76,10 +77,6 @@ def init_baselines():
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# raw_display = raw_display[raw_display['Line'] != ""]
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overall_ms = raw_display[['Line', 'SK1', 'SK2', 'SK3', 'Cost', 'Team Total', 'Shots', 'HDCF', 'Goals', 'Assists', 'Blocks',
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'L14_Shots', 'L14_HDCF', 'L14_Goals', 'L14_Assists', 'L14_Blocks']]
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data_cols = overall_ms.columns.drop(['Line', 'SK1', 'SK2', 'SK3'])
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overall_ms[data_cols] = overall_ms[data_cols].apply(pd.to_numeric, errors='coerce')
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overall_ms = overall_ms.sort_values(by='Shots', ascending=False)
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for team in team_list:
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table_parsed = overall_ms[overall_ms['Line'].str.contains('|'.join(team))]
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table_parsed['Max Goal%'] = table_parsed['Goals'].max()
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@@ -87,7 +84,10 @@ def init_baselines():
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parse_hold = pd.concat([parse_hold, table_parsed])
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overall_ms = parse_hold
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return matchups, overall_ms, team_frame, team_list, team_dict
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def convert_df_to_csv(df):
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NHL_data = 'https://docs.google.com/spreadsheets/d/1NmKa-b-2D3w7rRxwMPSchh31GKfJ1XcDI2GU8rXWnHI/edit#gid=811139250'
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percentages_format = {'Shots': '{:.2%}', 'HDCF': '{:.2%}', 'Goals': '{:.2%}', 'Assists': '{:.2%}', 'Blocks': '{:.2%}',
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'L14_Shots': '{:.2%}', 'L14_HDCF': '{:.2%}', 'L14_Goals': '{:.2%}', 'L14_Assists': '{:.2%}',
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'L14_Blocks': '{:.2%}', 'Max Goal%': '{:.2%}'}
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@st.cache_resource(ttl = 599)
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def init_baselines():
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# raw_display = raw_display[raw_display['Line'] != ""]
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overall_ms = raw_display[['Line', 'SK1', 'SK2', 'SK3', 'Cost', 'Team Total', 'Shots', 'HDCF', 'Goals', 'Assists', 'Blocks',
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'L14_Shots', 'L14_HDCF', 'L14_Goals', 'L14_Assists', 'L14_Blocks']]
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for team in team_list:
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table_parsed = overall_ms[overall_ms['Line'].str.contains('|'.join(team))]
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table_parsed['Max Goal%'] = table_parsed['Goals'].max()
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parse_hold = pd.concat([parse_hold, table_parsed])
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overall_ms = parse_hold
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data_cols = overall_ms.columns.drop(['Line', 'SK1', 'SK2', 'SK3'])
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overall_ms[data_cols] = overall_ms[data_cols].apply(pd.to_numeric, errors='coerce')
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overall_ms = overall_ms.sort_values(by='Shots', ascending=False)
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return matchups, overall_ms, team_frame, team_list, team_dict
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def convert_df_to_csv(df):
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