数据指标波动假设检验统计

eda/recommended_indexs/hypothesis_test.py

@@ -176,10 +176,15 @@ def chi_DATA_recently(x,y,z,q,t1,t2):
     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)
     CVR_DATA_recently = con_sql(sql_cid)
     return CVR_DATA_recently
+def chi_DATA_yesterday(x,y,z,t1):
+    sql_cid = "select {0}+{1},{2} from {3} where stat_date='{5}'  ".format(x,y,z,t1)
+    CVR_DATA_recently = con_sql(sql_cid)
+    return CVR_DATA_yesterday
 
-testtest=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)
-print(testtest[1])
-print(type(testtest))
+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")
+print(chi_ctr_precise_recently)
+print(chi_ctr_precise_yesterday)
 
 # chi_cvr_new=
 # chi_cvr_old=