Update app.py

app.py

@@ -117,14 +117,11 @@ if not filtered_df.empty:
         # Initialize a variable to store the sum for the current 'Conta'
         conta_sum = 0.0
 
-        # Optionally, handle multiple 'Modelos' by aggregating them
-        # For simplicity, here we're just taking the first 'Modelo' found for the 'Conta'
+        # Take the first 'Modelo' for simplicity
         modelo = conta_df['Modelo'].iloc[0]
 
         # Iterate over each row in the filtered DataFrame for the current 'Conta'
         for _, row in conta_df.iterrows():
-            # Extract the numeric value and add it to the conta_sum
-            # Assuming 'Forecasts' is already processed correctly above
             lines = row['Forecasts'].split('\n')
             for line in lines[:-1]:  # Skip the summary line
                 if line.strip():
@@ -138,7 +135,7 @@ if not filtered_df.empty:
         # Format the sum as a monetary value
         monetary_value = f'R$ {conta_sum:,.2f}'
 
-        # Append the 'Conta', 'Modelo', and sum to the data list
+        # Append the data to the list
         data.append({'Conta': conta, 'Modelo': modelo, 'Valor Monetário': monetary_value})
 
     # Convert the list to a DataFrame
@@ -147,12 +144,19 @@ if not filtered_df.empty:
     # Calculate the grand total sum of all 'Conta' values
     total_sum = sum(float(row['Valor Monetário'].replace('R$ ', '').replace(',', '')) for row in data)
 
-    # Create a DataFrame for the "Total" row, without a 'Modelo' value
+    # Append the "Total" row
     total_row = pd.DataFrame({'Conta': ['TOTAL'], 'Modelo': [''], 'Valor Monetário': [f'R$ {total_sum:,.2f}']})
-
-    # Concatenate the "Total" row with the existing table data
     table_data = pd.concat([table_data, total_row], ignore_index=True)
 
+    # Calculate and append the rows for "Saúde (12% da RLIT)" and "Educação (25% da RLIT)"
+    saude_value = total_sum * 0.15
+    educacao_value = total_sum * 0.25
+    saude_row = pd.DataFrame({'Conta': ['Saúde (15% da RLIT)'], 'Modelo': [''], 'Valor Monetário': [f'R$ {saude_value:,.2f}']})
+    educacao_row = pd.DataFrame({'Conta': ['Educação (25% da RLIT)'], 'Modelo': [''], 'Valor Monetário': [f'R$ {educacao_value:,.2f}']})
+
+    # Append these rows to the table data
+    table_data = pd.concat([table_data, saude_row, educacao_row], ignore_index=True)
+
     # Display the table
     st.table(table_data)