总计总计在Google Data Studio中是错误的 [英] Grand Total is wrong in Google Data Studio

问题描述

我在Google Data Studio中有一个表，其中包含以下数据:

I have a table in Google Data Studio with the following data:

Date    Users
1-Mar-18    616
2-Mar-18    632
3-Mar-18    550
4-Mar-18    567
5-Mar-18    688
6-Mar-18    1,844
7-Mar-18    788
8-Mar-18    2,153
9-Mar-18    1,469
10-Mar-18   554
11-Mar-18   448
12-Mar-18   861
13-Mar-18   1,578
14-Mar-18   823
15-Mar-18   628
16-Mar-18   556
17-Mar-18   292
18-Mar-18   311
19-Mar-18   635
20-Mar-18   1,966
21-Mar-18   1,111
22-Mar-18   748
23-Mar-18   610
24-Mar-18   366
25-Mar-18   359
26-Mar-18   720
27-Mar-18   2,103
28-Mar-18   879
29-Mar-18   664
30-Mar-18   562
31-Mar-18   272

如果将用户"总数加起来，总共将得出26353.但是，如果您在表格的数据"选项卡上选中显示摘要行"框，则用户的总计"列为20,997.

If you sum the "Users" you will come up with 26353 as a total. However, if you check the "Show summary row" box on the "Data" tab for the table, the "Grand Total" for users is listed as 20,997.

此外，如果我在同一日期段内创建一个以用户"作为指标的记分卡，则用户总数为20997.但是，如果我将日期范围缩短为可涵盖任何一天，则该天的用户将获得与表中相同的值(例如，日期范围为3月1日至3月1日的用户的记分卡将显示616位用户).

Furthermore, if I create a scorecard with "Users" as the metric over the same date period, I get 20,997 as the total number of Users. However, if I reduce the date period to cover any single day, I will get the same value value for users for that day as I see in the table (e.g. A scorecard on Users with a date range from March 1 to March 1 will show 616 Users).

我不确定这种差异来自何处，也不确定要信任哪个数字.

I am not sure where this difference is coming from, and I'm not sure which number to trust.

推荐答案

这是因为您的细分维度(日期). Google Analytics(分析)会尽力消除使用者的重复资料.因此，如果您查看整个月，它将告诉您您有20,997个用户.但是，如果您在组合中添加特定日期，并且其中一些用户多次回来，那么您的数字一定会更高.这些用户中的每个用户只计一次总数，但是按天划分时，他们可能会被列出多次.

This is because of your breakdown dimension (date). Google Analytics does its best to deduplicate users. So, if you're looking at the whole month, it will tell you that you had 20,997 users. But if you add a specific day to the mix and some of those users came back multiple times, then you'll necessarily have a higher number. Each of those users is only counted once for the aggregate number, but when split out by day, they may be listed several times.

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