数据指标波动假设检验统计

eda/recommended_indexs/hypothesis_test.py

@@ -26,7 +26,7 @@ def get_somedate():
 	:rtype : str
 	"""
 	today = datetime.date.today()
-	someday = today - datetime.timedelta(days=11)
+	someday = today - datetime.timedelta(days=10)
 	someday = someday.strftime("%Y-%m-%d")
 	return someday
 ten_days=get_somedate()
@@ -43,17 +43,18 @@ def DATA_recently(x,y,z,q,t):
 # #获取固定时间的10天的数据
 def DATA_fixed(x,y,z,q):
     sql_cid = "select {0}/{1} as {2} from {3} \
-    where stat_date >= " "  and stat_date<" " group by stat_date".format(x,y,z,q)
+    where stat_date >='2018-11-20'  and stat_date<='2018-11-29' group by stat_date".format(x,y,z,q)
     CVR_DATA_fixed = con_sql(sql_cid)
     return CVR_DATA_fixed
 #
 # #新用户cvr
 x_crv_new_temp=DATA_recently("diary_meigou_newUser","diary_clk_newUser","CVR_new","diary_meigou_crv",ten_days)
 x_crv_new=[x_crv_new_temp[i] for i in range(len(x_crv_new_temp))]
-print(type(x_crv_new))
-print(x_crv_new)
-# y_crv_new=DATA_fixed("diary_meigou_newUser","diary_clk_newUser","CVR_new","diary_meigou_crv")
-#
+# print(type(x_crv_new))
+# print(x_crv_new)
+y_crv_new_temp=DATA_fixed("diary_meigou_newUser","diary_clk_newUser","CVR_new","diary_meigou_crv")
+y_crv_new=[y_crv_new_temp[i] for i in range(len(y_crv_new_temp))]
+print(y_crv_new)
 # #老用户cvr
 # x_crv_old=DATA_recently("diary_meigou_oldUser","diary_clk_oldUser","CVR_old","diary_meigou_crv")
 # y_crv_old=DATA_fixed("diary_meigou_oldUser","diary_clk_oldUser","CVR_old","diary_meigou_crv")