Update app.py

app.py

@@ -164,42 +164,6 @@ if not filtered_df.empty:
     # Append these rows to the table data
     table_data = pd.concat([table_data, saude_row, educacao_row], ignore_index=True)
 
-    # Convert 'Data_Completa' to datetime format to ensure correct processing
-    temp_data['Data_Completa'] = pd.to_datetime(temp_data['Data_Completa'])
-
-    # Assuming 'Data_Completa' is sorted, if not, you should sort it.
-    # temp_data = temp_data.sort_values(by='Data_Completa', ascending=False)
-
-    # Initialize an empty list to store data including the 'Último ano' sums
-    data_with_last_year = []
-
-    # Iterate over each unique 'Instituição' and 'Conta' combination in 'df'
-    for instituicao in df['Instituição'].unique():
-        for conta in df[df['Instituição'] == instituicao]['Conta'].unique():
-            # Filter temp_data for the current 'Instituição' and 'Conta'
-            filtered_temp = temp_data[(temp_data['Instituição'] == instituicao) & (temp_data['Conta'] == conta)]
-
-            # Get the last 12 periods of 'Data_Completa'
-            last_12_periods = filtered_temp.nlargest(12, 'Data_Completa')
-
-            # Calculate the sum of 'Valor' for these periods
-            last_year_sum = last_12_periods['Valor'].sum()
-
-            # Append this information to the data list
-            data_with_last_year.append({
-                'Conta': conta,
-                'Último ano': last_year_sum
-            })
-
-    # Convert the list to a DataFrame
-    last_year_data = pd.DataFrame(data_with_last_year)
-
-    # Merge this DataFrame with your existing table data to add the 'Último ano' column
-    # Assuming 'table_data' is your existing DataFrame that you want to add the column to
-    # You might need to adjust column names or merge keys based on your actual data structure
-    table_data = table_data.merge(last_year_data, on=['Conta'])
-
-
     # Display the table
     st.table(table_data)