diff --git a/api/api_v1/endpoints/query.py b/api/api_v1/endpoints/query.py
index ad95f8e..2521912 100644
--- a/api/api_v1/endpoints/query.py
+++ b/api/api_v1/endpoints/query.py
@@ -369,17 +369,19 @@ async def scatter_model(
                 resp['label'].append(f'[{quota_interval_arr[i]},{v})')
                 bins.append(v)
 
+        summary_data = None
+        # todo 整体的，需要补充分组的
         for key, tmp_df in df.groupby('date'):
             bins_s = pd.cut(tmp_df['values'], bins=bins,
                             right=False).value_counts()
             bins_s.sort_index(inplace=True)
             total = int(bins_s.sum())
             resp['list'][key.strftime('%Y-%m-%d')] = {'n': bins_s.to_list(), 'total': total,
-                                              'p': round(bins_s * 100 / total, 2).to_list()}
+                                                      'p': round(bins_s * 100 / total, 2).to_list()}
         return schemas.Msg(code=0, msg='ok', data=resp)
 
     if interval_type == 'def' and analysis == 'number_of_days':
-        resp = {}
+        resp = {'list': {}}
         for key, tmp_df in df.groupby('date'):
             total = int(tmp_df['values'].sum())
             resp['list'][key.strftime('%Y-%m-%d')] = {'n': total, 'total': total, 'p': 100}
diff --git a/models/behavior_analysis.py b/models/behavior_analysis.py
index 1bab487..cda4260 100644
--- a/models/behavior_analysis.py
+++ b/models/behavior_analysis.py
@@ -299,12 +299,15 @@ ORDER BY level
             event_name_col == event_name
 
         ]
+        values_col = func.count().label('values')
+        if analysis in ['number_of_days', 'number_of_hours']:
+            values_col = func.count(func.distinct(e_account_id_col)).label('values')
 
         if analysis in ['times', 'number_of_days', 'number_of_hours']:
 
-            qry = sa.select(event_date_col, func.count().label('values')) \
+            qry = sa.select(event_date_col, values_col) \
                 .where(and_(*where)) \
-                .group_by(event_date_col, e_account_id_col)
+                .group_by(event_date_col, *self.groupby, e_account_id_col)
 
             sql = str(qry.compile(compile_kwargs={"literal_binds": True}))
             print(sql)
@@ -319,7 +322,7 @@ ORDER BY level
 
             qry = sa.select(event_date_col, settings.CK_FUNC[analysis](event_attr_col).label('values')) \
                 .where(and_(*where)) \
-                .group_by(event_date_col, e_account_id_col)
+                .group_by(event_date_col, *self.groupby, e_account_id_col)
             sql = str(qry.compile(compile_kwargs={"literal_binds": True}))
             print(sql)
             return {