Update app.py

app.py

@@ -6,6 +6,8 @@ import numpy as np
 
 df = pd.read_csv('last_results_5.csv')
 
+temp_data = pd.read_csv('temp_data(2).csv')
+
 image1 = 'images/rs_pmpa.PNG'
 
 title_html = """
@@ -162,14 +164,41 @@ 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)
 
-    # Calculate the sum of the last 12 periods for each "Conta" of each "Instituição"
-    last_12_periods_sums = df.groupby(['Instituição', 'Conta']) \
-        .apply(lambda x: x.sort_values(by='Period', ascending=False).head(12)['Value'].sum()) \
-        .reset_index(name='Último ano')
+    # 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({
+                'Instituição': instituicao,
+                'Conta': conta,
+                'Último ano': last_year_sum
+            })
+
+    # Convert the list to a DataFrame
+    last_year_data = pd.DataFrame(data_with_last_year)
 
-    # Merge this sum back into your table_data DataFrame
-    # This assumes table_data already exists and contains columns for 'Instituição' and 'Conta'
-    table_data = pd.merge(table_data, last_12_periods_sums, on=['Instituição', 'Conta'], how='left')
+    # 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=['Instituição', 'Conta'], how='left')
 
 
     # Display the table