adjusted file with gemini

src/components/data_table.py

@@ -4,7 +4,7 @@ from datetime import datetime
 import os
 import dash_bootstrap_components as dbc
 
-from ..data.loader import DataSchema
+from ..data.loader_gz import MTBFSchema
 from . import ids
 
 def render(app: Dash, data: pd.DataFrame) -> html.Div:
@@ -13,33 +13,48 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
         [
             Input(ids.YEAR_DROPDOWN, "value"),
             Input(ids.WEEK_DROPDOWN, "value"),
-            Input(ids.CATEGORY_DROPDOWN, "value"),
+            Input(ids.HITS_SELECTOR, "value"),
+            Input(ids.SINGLE_HITTER_FILTER, "value"),
         ],
     )
     def update_data_table(
-        years: list[str], weeks: list[str], categories: list[str]
+        years: list[str], weeks: list[str], hits_type: str, single_hitter_filter: list[str]
     ) -> html.Div:
         filtered_data = data.query(
-            "year in @years and week in @weeks and category in @categories"
+            "year in @years and week in @weeks"
         )
-
         if filtered_data.shape[0] == 0:
             return html.Div("No data selected.")
 
-        pt = filtered_data.pivot_table(
-            values=DataSchema.AMOUNT,
-            index=[DataSchema.CATEGORY],
-            aggfunc="sum",
-            fill_value=0,
-            dropna=False,
-        ).reset_index().sort_values(DataSchema.AMOUNT, ascending=False)
+        if hits_type == "p-hits":
+            hits_col = MTBFSchema.P_HITS
+        else:
+            hits_col = MTBFSchema.U_HITS
 
-        columns = [{"name": i.capitalize(), "id": i} for i in pt.columns]
+        # Count 'Y' values
+        hits_data = filtered_data[filtered_data[hits_col] == 'Y']
+        
+        table_data = hits_data.groupby(MTBFSchema.AIR).agg(
+            count=(hits_col, 'size'),
+            air_issue_description=(MTBFSchema.AIR_ISSUE_DESCRIPTION, lambda x: ', '.join(x.unique())),
+            close_notes=(MTBFSchema.CLOSE_NOTES, lambda x: ', '.join(x.unique()))
+        ).reset_index()
+
+        if 'remove_single' in single_hitter_filter:
+            table_data = table_data[table_data['count'] > 1]
+        else:
+            table_data = table_data[table_data['count'] == 1]
+            
+        table_data = table_data.sort_values('count', ascending=False)
+        
+        # Reorder columns
+        table_data = table_data[[MTBFSchema.AIR, 'air_issue_description', 'close_notes', 'count']]
 
         return dash_table.DataTable(
-            id=ids.CATEGORY_TABLE,
-            data=pt.to_dict("records"),
-            columns=columns,
+            id=ids.CATEGORY_TABLE, # Using this ID for feedback callbacks
+            data=table_data.to_dict("records"),
+            columns=[{"name": i, "id": i} for i in table_data.columns],
+            page_size=10,
             row_selectable='single',
             selected_rows=[]
         )
@@ -54,7 +69,7 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
         State(ids.CATEGORY_TABLE, "data"),
         State(ids.FEEDBACK_INPUT, "value"),
     )
-    def handle_feedback_modal(selected_rows, save_clicks, close_clicks, is_open, data, comment):
+    def handle_feedback_modal(selected_rows, save_clicks, close_clicks, is_open, table_data, comment):
         ctx = callback_context
         if not ctx.triggered:
             return False, ""
@@ -65,12 +80,12 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
             return True, ""
 
         if triggered_id == ids.SAVE_FEEDBACK_BUTTON_POPUP and selected_rows:
-            selected_row_data = data[selected_rows[0]]
-            category = selected_row_data[DataSchema.CATEGORY]
+            selected_row_data = table_data[selected_rows[0]]
+            air_value = selected_row_data[MTBFSchema.AIR]
             timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
             if not comment:
                 comment = ""
-            feedback_data = f'{timestamp},{category},"{comment}"\n'
+            feedback_data = f'{timestamp},dashboard_table,"AIR: {air_value} - {comment}"\n'
             file_path = "data/feedback.csv"
             try:
                 is_new_file = not os.path.exists(file_path) or os.path.getsize(file_path) == 0
@@ -78,7 +93,7 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
                     if is_new_file:
                         f.write("timestamp,category,comment\n")
                     f.write(feedback_data)
-                message = f"Feedback for category '{category}' has been saved successfully at {timestamp}."
+                message = f"Feedback for AIR '{air_value}' has been saved successfully at {timestamp}."
                 return False, message
             except Exception as e:
                 return True, "An error occurred while saving feedback."
@@ -94,17 +109,17 @@ def render(app: Dash, data: pd.DataFrame) -> html.Div:
         State(ids.CATEGORY_TABLE, "data"),
         prevent_initial_call=True
     )
-    def update_feedback_category_label(selected_rows, data):
+    def update_feedback_air_label(selected_rows, data):
         if selected_rows:
-            category = data[selected_rows[0]][DataSchema.CATEGORY]
-            return f"Category: {category}"
-        return "Category: "
+            air_value = data[selected_rows[0]][MTBFSchema.AIR]
+            return f"AIR: {air_value}"
+        return "AIR: "
 
     modal = dbc.Modal(
         [
             dbc.ModalHeader(dbc.ModalTitle("Submit Feedback")),
             dbc.ModalBody([
-                html.H6("Category: ", id="feedback-category-label"),
+                html.H6("AIR: ", id="feedback-category-label"),
                 dcc.Input(id=ids.FEEDBACK_INPUT, type='text', placeholder='Enter feedback...', style={'width': '100%'}),
             ]),
             dbc.ModalFooter([