Moved dataframe to above the multiselect

app.py

@@ -23,17 +23,12 @@ class MultiURLData:
             with open(filename) as f:
                 data = json.load(f)
                 df = pd.DataFrame(data['results']).T
-
                 df = df.rename(columns={'acc': model_name})
-
                 df.index = df.index.str.replace('hendrycksTest-', '')
-
                 df.index = df.index.str.replace('harness\\|', '')
-
                 dataframes.append(df[[model_name]])
 
         data = pd.concat(dataframes, axis=1)
-
         data = data.transpose()
         data['Model Name'] = data.index
         cols = data.columns.tolist()
@@ -42,26 +37,56 @@ class MultiURLData:
 
         return data
 
+    def get_top_performing_models(self, column_name, top_n):
+        sorted_data = self.data.sort_values(by=column_name, ascending=False)
+        return sorted_data['Model Name'].head(top_n).tolist()
+
     def get_data(self, selected_models):
         filtered_data = self.data[self.data['Model Name'].isin(selected_models)]
         return filtered_data
+    
 
 data_provider = MultiURLData()
 
-# Create checkboxes for each column
-selected_columns = st.multiselect(
-    'Select Columns',
-    data_provider.data.columns.tolist(),
-    default=data_provider.data.columns.tolist()
-)
-
-selected_models = st.multiselect(
-    'Select Models',
-    data_provider.data['Model Name'].tolist(),
-    default=data_provider.data['Model Name'].tolist()
-)
-
-
-# Get the filtered data and display it in a table
-filtered_data = data_provider.get_data(selected_models)
-st.dataframe(filtered_data)
+# Get top 20 performing models
+top_models = data_provider.get_top_performing_models('harness|arc:challenge|25', 20)
+
+# Initialize selected models and columns
+selected_models = top_models
+selected_columns = data_provider.data.columns.tolist()
+
+# Create placeholders for the dataframe and multiselects
+df_placeholder = st.empty()
+models_multiselect = st.empty()
+columns_multiselect = st.empty()
+
+# Function to display dataframe
+def display_dataframe(models, columns):
+    filtered_data = data_provider.get_data(models)
+    filtered_data = filtered_data[columns]
+    df_placeholder.dataframe(filtered_data)
+
+# Function to display multiselects
+def display_multiselects():
+    models = models_multiselect.multiselect(
+        'Select Models',
+        data_provider.data['Model Name'].tolist(),
+        default=selected_models
+    )
+    columns = columns_multiselect.multiselect(
+        'Select Columns',
+        data_provider.data.columns.tolist(),
+        default=selected_columns
+    )
+    return models, columns
+
+# Display dataframe initially
+display_dataframe(selected_models, selected_columns)
+
+# Display multiselects initially
+selected_models, selected_columns = display_multiselects()
+
+# If the user clicks the "Update" button, update the selected models and columns
+# and redisplay the dataframe
+if st.button('Update'):
+    display_dataframe(selected_models, selected_columns)