如何将观测值与r中的结束日期合并

Question

我有一个数据库，每6个月测试一次牛群中的动物(动物的数量会随着时间的推移而变化)。问题是，牛群中的所有动物不是在同一天进行测试，而是在2个月的时间内进行测试。

我想知道我可以创建一个新的列，它合并了所有这些结束日期(按群分组)，这样我就可以计算出一个羊群被测试的次数。

这是一个例子，一群已经测试了8次，但在不同的日期。每一个点代表一个动物：

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以下是数据的一个示例：

df <- data.frame(
        animal = c("Animal1", "Animal2", "Animal3", "Animal4", "Animal5", "Animal6", "Animal1", "Animal2", "Animal3", "Animal4", "Animal5", "Animal6", "Animal7", "Animal8", "Animal9", "Animal10", "Animal11", "Animal12", "Animal7", "Animal8", "Animal9", "Animal10", "Animal11", "Animal12"),
        herd = c("Herd1","Herd1","Herd1", "Herd1","Herd1","Herd1", "Herd1","Herd1","Herd1", "Herd1","Herd1","Herd1","Herd2","Herd2", "Herd2","Herd2","Herd2","Herd2", "Herd2","Herd2", "Herd2","Herd2","Herd2","Herd2"),
        date = c("2017-01-01", "2017-01-01", "2017-01-17","2017-02-04", "2017-02-04", "2017-02-05", "2017-06-01" , "2017-06-03", "2017-07-01", "2017-06-21", "2017-06-01", "2017-06-15", "2017-02-01", "2017-02-01", "2017-02-15", "2017-02-21", "2017-03-05", "2017-03-01", "2017-07-01", "2017-07-01", "2017-07-15", "2017-07-21", "2017-08-05", "2017-08-01"))

因此，预期的结果将是：

     animal  herd       date  testing
1   Animal1 Herd1 2017-01-01  1
2   Animal2 Herd1 2017-01-01  1
3   Animal3 Herd1 2017-01-17  1
4   Animal4 Herd1 2017-02-04  1
5   Animal5 Herd1 2017-02-04  1
6   Animal6 Herd1 2017-02-05  1
7   Animal1 Herd1 2017-06-01  2
8   Animal2 Herd1 2017-06-03  2
9   Animal3 Herd1 2017-07-01  2
10  Animal4 Herd1 2017-06-21  2
11  Animal5 Herd1 2017-06-01  2
12  Animal6 Herd1 2017-06-15  2
13  Animal7 Herd2 2017-02-01  1
14  Animal8 Herd2 2017-02-01  1
15  Animal9 Herd2 2017-02-15  1
16 Animal10 Herd2 2017-02-21  1
17 Animal11 Herd2 2017-03-05  1
18 Animal12 Herd2 2017-03-01  1
19  Animal7 Herd2 2017-07-01  2
20  Animal8 Herd2 2017-07-01  2
21  Animal9 Herd2 2017-07-15  2
22 Animal10 Herd2 2017-07-21  2
23 Animal11 Herd2 2017-08-05  2
24 Animal12 Herd2 2017-08-01  2

我想应用这样的方法，但是考虑到彼此关闭的日期是相同的测试。

df %>% 
  group_by(herd) %>% 
  mutate(testing = dense_rank(date))

谢谢!

Answer 1

您可以每5个月使用一次group_by并应用dense_rank。因为你最小的两个日期之间的差距来自同一动物是5个月，单位必须是5个月。

library(dplyr)
library(lubridate)
df %>% 
  group_by(testing = dense_rank(floor_date(ymd(date), unit = "5 months")))