如何使用基于本地日期设置的RGA包从Google Analytics帐户获取每周数据
尝试使用下面的示例代码从Google Analytics帐户获取数据。我希望结果按周分组;因此,添加了ga:week作为最后一个维度如何使用基于本地日期设置的RGA包从Google Analytics帐户获取每周数据,r,google-analytics,R,Google Analytics,尝试使用下面的示例代码从Google Analytics帐户获取数据。我希望结果按周分组;因此,添加了ga:week作为最后一个维度 ga_data <- get_ga(id, start.date = "2017-02-27", end.date = "2017-03-05", metrics = "ga:bounceRate, ga:sessions, dimensions = "ga:Medium, ga:wee
ga_data <- get_ga(id, start.date = "2017-02-27", end.date = "2017-03-05",
metrics = "ga:bounceRate, ga:sessions,
dimensions = "ga:Medium, ga:week",
segment = "gaid::xxxxxxxxxxxxxx",
include.empty.rows = "TRUE")
使用ga:isoYearIsoWeek代替ga:week作为维度解决了问题。现在,当我删除ga:date时,它将是从周一开始的每周基础
对于那些有类似问题的人,以下链接可能会有所帮助:
将ga:date添加到维度。@artemkletsov,谢谢回复。我刚刚对有关您评论的问题进行了一些编辑。您设置了ga:isoYearIsoWeek,但对于日期范围,该范围仍然是美国星期日标准星期日第一天,星期六最后一天,这是否真的正确,还是我们应该根据ga:isoYearIsoWeek准备日期范围?
> ga_data <- get_ga(id, start.date = "2017-02-26", end.date = "2017-03-06",
+ metrics = "ga:bounceRate, ga:sessions",
+ dimensions = "ga:Medium, ga:week, ga:date",
+ segment = "gaid::xxxxxxxxxxxxxx",
+ include.empty.rows = "TRUE")
> library(lubridate)
> ga_data$weekDay <- wday(ga_data$date, label = T)
> ga_data$weekDesired <- format(ga_data$date, "%W")
> head(ga_data,16)
Medium week date bounceRate sessions weekDay weekDesired
<chr> <chr> <dttm> <dbl> <int> <ord> <chr>
1 (none) 09 2017-02-26 66.66667 3 Sun 08
2 (none) 09 2017-02-27 50.00000 6 Mon 09
3 (none) 09 2017-02-28 80.00000 5 Tues 09
4 (none) 09 2017-03-01 20.00000 5 Wed 09
5 (none) 09 2017-03-02 57.14286 14 Thurs 09
6 (none) 09 2017-03-03 75.00000 8 Fri 09
7 (none) 09 2017-03-04 100.00000 4 Sat 09
8 (none) 10 2017-03-05 100.00000 4 Sun 09
9 (none) 10 2017-03-06 38.46154 13 Mon 10
10 banner 09 2017-02-26 22.22222 9 Sun 08
11 banner 09 2017-02-27 36.84211 19 Mon 09
12 banner 09 2017-02-28 58.33333 12 Tues 09
13 banner 09 2017-03-01 53.33333 15 Wed 09
14 banner 09 2017-03-02 50.00000 12 Thurs 09
15 banner 09 2017-03-03 54.54545 11 Fri 09
16 banner 09 2017-03-04 25.00000 12 Sat 09
> ga_data <- get_ga(id, start.date = "2017-02-26", end.date = "2017-03-06",
+ metrics = "ga:bounceRate, ga:sessions",
+ dimensions = "ga:Medium, ga:isoYearIsoWeek, ga:date",
+ segment = "gaid::4SZBNy34Taypmuk_Mczdow",
+ include.empty.rows = "TRUE")
> ga_data$weekDay <- wday(ga_data$date, label = T)
> ga_data$weekDesired <- format(ga_data$date, "%W")
> head(ga_data,20)
Medium **isoYearIsoWeek** date bounceRate sessions weekDay **weekDesired**
<chr> <chr> <dttm> <dbl> <int> <ord> <chr>
1 (none) 201708 2017-02-26 66.66667 3 Sun 08
2 (none) 201709 2017-02-27 50.00000 6 Mon 09
3 (none) 201709 2017-02-28 80.00000 5 Tues 09
4 (none) 201709 2017-03-01 20.00000 5 Wed 09
5 (none) 201709 2017-03-02 57.14286 14 Thurs 09
6 (none) 201709 2017-03-03 75.00000 8 Fri 09
7 (none) 201709 2017-03-04 100.00000 4 Sat 09
8 (none) 201709 2017-03-05 100.00000 4 Sun 09
9 (none) 201710 2017-03-06 38.46154 13 Mon 10
10 banner 201708 2017-02-26 22.22222 9 Sun 08
11 banner 201709 2017-02-27 36.84211 19 Mon 09
12 banner 201709 2017-02-28 58.33333 12 Tues 09
13 banner 201709 2017-03-01 53.33333 15 Wed 09
14 banner 201709 2017-03-02 50.00000 12 Thurs 09
15 banner 201709 2017-03-03 54.54545 11 Fri 09
16 banner 201709 2017-03-04 25.00000 12 Sat 09
17 banner 201709 2017-03-05 27.27273 11 Sun 09
18 banner 201710 2017-03-06 44.44444 18 Mon 10
19 cpc 201708 2017-02-26 52.15239 4646 Sun 08
20 cpc 201709 2017-02-27 52.73286 4885 Mon 09