数据指标波动假设检验统计

eda/recommended_indexs/hypothesis_test.py

@@ -79,23 +79,23 @@ x_ctr_new=[float(str(Decimal(x_ctr_new_temp[i][0]).quantize(Decimal('0.0000'))))
 y_ctr_new_temp=DATA_fixed("clk_count_newUser_all","imp_count_newUser_all","ctr_new","bug_Recommendation_strategy_newUser")
 y_ctr_new=[float(str(Decimal(y_ctr_new_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(y_ctr_new_temp))]
 # #
-# # #老用户ctr(page_view)
-# x_ctr_old_temp=DATA_recently("clk_count_oldUser_all","imp_count_oldUser_all","ctr_old","bug_Recommendation_strategy_temp",ten_days)
-# x_ctr_old=[float(str(Decimal(x_ctr_old_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(x_ctr_old_temp))]
-# y_ctr_old_temp=DATA_fixed("clk_count_oldUser_all","imp_count_oldUser_all","ctr_old","bug_Recommendation_strategy_temp")
-# y_ctr_old=[float(str(Decimal(y_ctr_old_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(y_ctr_old_temp))]
-# #
-# # #新用户ctr(on_click_diary_card)
-# x_ctr_new_o_temp=DATA_recently("clk_count_newUser_all_a","imp_count_newUser_all","ctr_new","on_click_diary_card",ten_days)
-# x_ctr_new_o=[float(str(Decimal(x_ctr_new_o_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(x_ctr_new_o_temp))]
-# y_ctr_new_o_temp=DATA_fixed("clk_count_newUser_all_a","imp_count_newUser_all","ctr_new","on_click_diary_card")
-# y_ctr_new_o=[float(str(Decimal(y_ctr_new_o_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(y_ctr_new_o_temp))]
-# #
-# # #老用户ctr(on_click_diary_card)
-# x_ctr_old_o_temp=DATA_recently("clk_count_oldUser_all_a","imp_count_oldUser_all","ctr_old","on_click_diary_card",ten_days)
-# x_ctr_old_o=[float(str(Decimal(x_ctr_old_o_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(x_ctr_old_o_temp))]
-# y_ctr_old_o_temp=DATA_fixed("clk_count_oldUser_all_a","imp_count_oldUser_all","ctr_old","on_click_diary_card")
-# y_ctr_old_o=[float(str(Decimal(y_ctr_old_o_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(y_ctr_old_o_temp))]
+# #老用户ctr(page_view)
+x_ctr_old_temp=DATA_recently("clk_count_oldUser_all","imp_count_oldUser_all","ctr_old","bug_Recommendation_strategy_temp",ten_days)
+x_ctr_old=[float(str(Decimal(x_ctr_old_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(x_ctr_old_temp))]
+y_ctr_old_temp=DATA_fixed("clk_count_oldUser_all","imp_count_oldUser_all","ctr_old","bug_Recommendation_strategy_temp")
+y_ctr_old=[float(str(Decimal(y_ctr_old_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(y_ctr_old_temp))]
+#
+# #新用户ctr(on_click_diary_card)
+x_ctr_new_o_temp=DATA_recently("clk_count_newUser_all_a","imp_count_newUser_all","ctr_new","on_click_diary_card",ten_days)
+x_ctr_new_o=[float(str(Decimal(x_ctr_new_o_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(x_ctr_new_o_temp))]
+y_ctr_new_o_temp=DATA_fixed("clk_count_newUser_all_a","imp_count_newUser_all","ctr_new","on_click_diary_card")
+y_ctr_new_o=[float(str(Decimal(y_ctr_new_o_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(y_ctr_new_o_temp))]
+#
+# #老用户ctr(on_click_diary_card)
+x_ctr_old_o_temp=DATA_recently("clk_count_oldUser_all_a","imp_count_oldUser_all","ctr_old","on_click_diary_card",ten_days)
+x_ctr_old_o=[float(str(Decimal(x_ctr_old_o_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(x_ctr_old_o_temp))]
+y_ctr_old_o_temp=DATA_fixed("clk_count_oldUser_all_a","imp_count_oldUser_all","ctr_old","on_click_diary_card")
+y_ctr_old_o=[float(str(Decimal(y_ctr_old_o_temp[i][0]).quantize(Decimal('0.0000')))) for i in range(len(y_ctr_old_o_temp))]
 # #
 #
 #
@@ -136,16 +136,15 @@ ctcrv_new_ttest=t_test(x_ctcrv_new,y_ctcrv_new)
 ctcrv_old_ttest=t_test(x_ctcrv_old,y_ctcrv_old)
 #
 #
-# #新用户ctr假设检验
+#新用户ctr假设检验
 ctr_new_ttest=t_test(x_ctr_new,y_ctr_new)
 #老用户ctr假设检验
-# ctr_old_ttest=t_test(x_ctr_old,y_ctr_old)
-#
-# ##新用户ctr(on_click_diary_card)假设检验
-# ctr_new_o_ttest=t_test(x_ctr_new_o,y_ctr_new_o)
-# #老用户ctr(on_click_diary_card)假设检验
-# ctr_old_o_ttest=t_test(x_ctr_old_o,y_ctr_old_o)
-# #
+ctr_old_ttest=t_test(x_ctr_old,y_ctr_old)
+
+#新用户ctr(on_click_diary_card)假设检验
+ctr_new_o_ttest=t_test(x_ctr_new_o,y_ctr_new_o)
+#老用户ctr(on_click_diary_card)假设检验
+ctr_old_o_ttest=t_test(x_ctr_old_o,y_ctr_old_o)
 #
 # ###############推荐策略不变的情况下数据假设检验##############
 #