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Update app.py
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app.py
CHANGED
@@ -52,7 +52,7 @@ def init_baselines():
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matchups = raw_display[['Team', 'Opp', 'FL1$', 'FL2$', 'FL3$', 'Team Total', 'Game Pace', 'SF', 'o_SA', 'SF_m', 'HDCF',
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'o_HDCA', 'HDCF_m']]
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data_cols = matchups.columns.drop(['Team', 'Opp'])
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matchups[data_cols] = matchups[data_cols].apply(pd.to_numeric, errors='coerce')
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worksheet = sh.worksheet('Marketshares')
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raw_display = pd.DataFrame(worksheet.get_values())
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@@ -63,7 +63,7 @@ def init_baselines():
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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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return matchups, overall_ms
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@@ -82,7 +82,7 @@ with col1:
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with col2:
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if split_var1 == 'Slate Matchups':
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display_table = matchups
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st.dataframe(display_table
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st.download_button(
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label="Export Matchups",
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data=convert_df_to_csv(display_table),
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@@ -91,7 +91,7 @@ with col2:
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)
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elif split_var1 == 'Line Marketshares':
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display_table = overall_ms
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st.dataframe(display_table
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st.download_button(
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label="Export Marketshares",
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data=convert_df_to_csv(display_table),
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matchups = raw_display[['Team', 'Opp', 'FL1$', 'FL2$', 'FL3$', 'Team Total', 'Game Pace', 'SF', 'o_SA', 'SF_m', 'HDCF',
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'o_HDCA', 'HDCF_m']]
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data_cols = matchups.columns.drop(['Team', 'Opp'])
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+
# matchups[data_cols] = matchups[data_cols].apply(pd.to_numeric, errors='coerce')
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worksheet = sh.worksheet('Marketshares')
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raw_display = pd.DataFrame(worksheet.get_values())
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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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return matchups, overall_ms
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with col2:
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if split_var1 == 'Slate Matchups':
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display_table = matchups
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st.dataframe(display_table, use_container_width = True)
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st.download_button(
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label="Export Matchups",
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data=convert_df_to_csv(display_table),
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)
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elif split_var1 == 'Line Marketshares':
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display_table = overall_ms
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st.dataframe(display_table, use_container_width = True)
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st.download_button(
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label="Export Marketshares",
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data=convert_df_to_csv(display_table),
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