diff --git a/api/api_v1/endpoints/query.py b/api/api_v1/endpoints/query.py
index c1970a7..5c040a7 100644
--- a/api/api_v1/endpoints/query.py
+++ b/api/api_v1/endpoints/query.py
@@ -438,7 +438,33 @@ async def event_model(
         item['sum'] = np.array(item['sum'])[sort_key].tolist()
         item['avg'] = np.array(item['avg'])[sort_key].tolist()
     res = [item for idx, item in enumerate(res) if idx not in is_hide]
-
+    #  对单个为int的分组进行排序
+    if analysis.event_view.get('groupBy','') !=[] and analysis.event_view.get('groupBy','') != '':
+        if analysis.event_view.get('groupBy','')[0]['data_type'] == 'int' and len(analysis.event_view.get('groupBy','')) == 1 and len(res[0]['groups']) > 1:
+            short_list = sorted([ast.literal_eval(i)[0] for i in res[0]['groups']])
+            idx_list = []
+            for date in res[0]['groups']:
+                for id, i in enumerate(short_list):
+                    if date == f'[{i}]':
+                        idx_list.append(id)
+                        break
+            for i in ['groups', 'values', 'sum', 'avg']:
+                ad = [0 for nu in range(len(idx_list))]
+                for idx, ii in enumerate(idx_list):
+                    ad[ii] = res[0][i][idx]
+                res[0][i] = ad
+    #  计算每一天的总和
+    # if res[0]['event_name'] == '充值排行':
+    #     zong=[]
+    #     lens=len(res[0]['date_range'])
+    #     for nu in range(lens):
+    #         aa=0
+    #         for value in res[0]['values']:
+    #             aa+=value[nu]
+    #         zong.append(aa)
+    #     res[0]['zong']=zong
+    # else:
+    #     res[0]['zong'] = []
     return schemas.Msg(code=0, msg='ok', data=res)
 
 
@@ -1887,6 +1913,11 @@ async def scatter_model(
                 ac = ast.literal_eval(i)
                 ab = [str(ii) for ii in ac]
                 groupby_data.append(ab)
+                # if not isinstance(ac,int):
+                #     ab = [str(ii) for ii in ac]
+                #     groupby_data.append(ab)
+                # else:
+                #     groupby_data.append(ac)
             resp['groupby_data'] = groupby_data
             return schemas.Msg(code=0, msg='ok', data=resp)
         else: