数据指标波动假设检验统计

eda/recommended_indexs/hypothesis_test.py

@@ -305,11 +305,33 @@ def get_var_data(x,y,z,t1):
 def collect_data(data):
     tt = [float(data[i][0])*100 for i in range(len(data))]
     return tt
-print("【1】新用户CT-CVR数据波动5日内方差检验结果：")
-test_data=get_var_data("diary_meigou_oldUser","diary_exp_oldUser","diary_meigou_crv",five_days)
-tt=collect_data(test_data)
-lin=np.var(tt)
-print(lin)
+
+var_ctcvr_old_data=get_var_data("diary_meigou_oldUser","diary_exp_oldUser","diary_meigou_crv",five_days)
+var_ctcvr_old_D=collect_data(var_ctcvr_old_data)
+var_ctcvr_old=np.var(var_ctcvr_old_D)
+print("【1】老用户CT-CVR数据波动5日内方差检验结果：{}".format(var_ctcvr_old))
+
+var_ctcvr_new_data=get_var_data("diary_meigou_newUser","diary_exp_newUser","diary_meigou_crv",five_days)
+var_ctcvr_new_D=collect_data(var_ctcvr_new_data)
+var_ctcvr_new=np.var(var_ctcvr_new_D)
+print("【2】新用户CT-CVR数据波动5日内方差检验结果：{}".format(var_ctcvr_new))
+
+var_cvr_old_data=get_var_data("diary_meigou_oldUser","diary_clk_oldUser","diary_meigou_crv",five_days)
+var_cvr_old_D=collect_data(var_cvr_old_data)
+var_cvr_old=np.var(var_cvr_old_D)
+print("【3】老用户CVR数据波动5日内方差检验结果：{}".format(var_cvr_old))
+#
+var_cvr_new_data=get_var_data("diary_meigou_newUser","diary_clk_newUser","diary_meigou_crv",five_days)
+var_cvr_new_D=collect_data(var_cvr_new_data)
+var_cvr_new=np.var(var_cvr_new_D)
+print("【4】新用户CVR数据波动5日内方差检验结果：{}".format(var_cvr_new))
+
+# var_ctr_new_data=get_var_data("diary_meigou_newUser","diary_clk_newUser","diary_meigou_crv",five_days)
+# var_cvr_new_D=collect_data(var_cvr_new_data)
+# var_cvr_new=np.var(var_cvr_new_D)
+# print("【4】新用户CVR数据波动5日内方差检验结果：{}".format(var_cvr_new))
+
+
 
 # print(chi_ctr_precise_recently)
 # print(chi_ctr_precise_yesterday)