Update app.py

app.py

@@ -77,11 +77,22 @@ else:
                 coordinates = raw_answer.get('coordinates', [])
                 cells = raw_answer.get('cells', [])
                 
-                if aggregator == 'SUM':
-                    # Convert cell values to numbers and sum them
-                    values = [float(cell) for cell in cells if cell.replace('.', '').isdigit()]
-                    total_sum = sum(values)
-                    base_sentence = f"The sum for '{question}' is {total_sum}."
+                # Handle aggregation based on user question or TAPAS output
+                if 'average' in question.lower() or aggregator == 'AVG':
+                    avg_value = df_numeric.mean().mean()  # Calculate average of the entire DataFrame
+                    base_sentence = f"The average for '{question}' is {avg_value:.2f}."
+                elif 'sum' in question.lower() or aggregator == 'SUM':
+                    total_sum = df_numeric.sum().sum()  # Calculate sum of all numeric values
+                    base_sentence = f"The sum for '{question}' is {total_sum:.2f}."
+                elif 'max' in question.lower() or aggregator == 'MAX':
+                    max_value = df_numeric.max().max()  # Calculate max value across DataFrame
+                    base_sentence = f"The maximum value for '{question}' is {max_value:.2f}."
+                elif 'min' in question.lower() or aggregator == 'MIN':
+                    min_value = df_numeric.min().min()  # Calculate min value across DataFrame
+                    base_sentence = f"The minimum value for '{question}' is {min_value:.2f}."
+                elif 'count' in question.lower() or aggregator == 'COUNT':
+                    row_count = df_numeric.count().sum()  # Count of all non-null values
+                    base_sentence = f"The total count of non-null values for '{question}' is {row_count}."
                 else:
                     # Construct a base sentence for other aggregators or no aggregation
                     base_sentence = f"The answer from TAPAS for '{question}' is {answer}."