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b36d1b3
1
Parent(s):
37d6b8f
Update app.py
Browse files
app.py
CHANGED
@@ -53,7 +53,29 @@ with st.sidebar:
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selected_conta = st.selectbox('Seleciona Conta', df['Conta'].unique())
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# Filter the DataFrame based on selected values
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filtered_df = df[(df['Instituição'] == selected_instituicao) & (df['Conta'] == selected_conta)]
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#col1, col2, col3 = st.columns(3) # This divides the page into three equal parts
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selected_conta = st.selectbox('Seleciona Conta', df['Conta'].unique())
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# Filter the DataFrame based on selected values
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#filtered_df = df[(df['Instituição'] == selected_instituicao) & (df['Conta'] == selected_conta)]
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# Initial filtering based on selected 'Instituição'
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instituicao_df = df[df['Instituição'] == selected_instituicao]
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# Container for adjusted DataFrame rows
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adjusted_rows = []
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# Iterate through each unique 'Conta' within the selected 'Instituição'
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for conta in instituicao_df['Conta'].unique():
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conta_df = instituicao_df[instituicao_df['Conta'] == conta]
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# Check if 'Linear Regression' is available for this 'Conta'
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if 'Linear Regression' in conta_df['Modelo'].values:
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# If yes, filter to only 'Linear Regression' results for this 'Conta'
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lr_rows = conta_df[conta_df['Modelo'] == 'Linear Regression']
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adjusted_rows.append(lr_rows)
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else:
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# If not, include all models' results for this 'Conta'
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adjusted_rows.append(conta_df)
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# Combine all adjusted rows back into a single DataFrame
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filtered_df = pd.concat(adjusted_rows)
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#col1, col2, col3 = st.columns(3) # This divides the page into three equal parts
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