数据指标波动假设检验统计

eda/recommended_indexs/hypothesis_test.py

@@ -173,7 +173,7 @@ five_days=get_fivedate()
 #获取最近5天的数据
 def chi_DATA_recently(x,y,z,q,t1,t2):
     sql_cid = "select AVG({0}+{1}),AVG({2}) from {3} \
-    where stat_date >= '{4}' and stat_date < '{5}' union all select {0}+{1},{2} from {3} where stat_date='{5}'  ".format(x,y,z,q,t1,t2)
+    where stat_date >= '{4}' and stat_date < '{5}' ".format(x,y,z,q,t1,t2)
     CVR_DATA_recently = con_sql(sql_cid)
     return CVR_DATA_recently
 def chi_DATA_yesterday(x,y,z,q,t1):
@@ -182,7 +182,7 @@ def chi_DATA_yesterday(x,y,z,q,t1):
     return CVR_DATA_yesterday
 
 chi_ctr_precise_recently=chi_DATA_recently("clk_count_oldUser_all_a","clk_count_oldUser_all_b","imp_count_oldUser_all_precise","on_click_diary_card",five_days,yesterday)
-chi_ctr_precise_yesterday=chi_DATA_yesterday("clk_count_oldUser_all_a","clk_count_oldUser_all_b","imp_count_oldUser_all_precise","on_click_diary_card","yesterday")
+chi_ctr_precise_yesterday=chi_DATA_yesterday("clk_count_oldUser_all_a","clk_count_oldUser_all_b","imp_count_oldUser_all_precise","on_click_diary_card",yesterday)
 print(chi_ctr_precise_recently)
 print(chi_ctr_precise_yesterday)