我试图根据日期和初始事件确定重复ID。下面是一个示例数据集
+----+------------+-------------------------+
| ID | Date | Investigation or Intake |
+----+------------+-------------------------+
| 1 | 1/1/2019 | Investigation |
| 2 | 1/2/2019 | Investigation |
| 3 | 1/3/2019 | Investigation |
| 4 | 1/4/2019 | Investigation |
| 1 | 1/2/2019 | Intake |
| 2 | 12/31/2018 | Intake |
| 3 | 1/5/2019 | Intake |
+----+------------+-------------------------+我想要编写R代码来检查从1到4的ID(有调查的ID),并查看它们是否有后续的摄入量(在比调查日期更晚的时间内发生的摄入量)。因此,预期的输出如下:
+----+------------+-------------------------+------------+
| ID | Date | Investigation or Intake | New Column |
+----+------------+-------------------------+------------+
| 1 | 1/1/2019 | Investigation | Sub Intake |
| 2 | 1/2/2019 | Investigation | None |
| 3 | 1/3/2019 | Investigation | Sub Intake |
| 4 | 1/4/2019 | Investigation | None |
| 1 | 1/2/2019 | Intake | |
| 2 | 12/31/2018 | Intake | |
| 3 | 1/5/2019 | Intake | |
+----+------------+-------------------------+------------+解决这个问题的代码是什么样子的?我猜这将是某种循环功能?
谢谢!
发布于 2019-04-03 02:48:21
您可以使用dplyr包并使用一些ifelse语句根据需要创建一个新列。与其使用循环,不如使用lead函数检查组中的下一个条目。这个解决方案假设,在每个组中,您将有一个“调查”,然后是0或更多的“摄入量”条目,然后列出。
library(dplyr)
df <- data.frame(ID = c(1, 2, 3, 4, 1, 2, 3),
Date = as.Date(c("2019-01-01", "2019-01-02", "2019-1-03", "2019-01-04", "2019-01-02", "2018-12-31", "2019-1-5")),
Investigation_or_Intake = c("Investigation", "Investigation", "Investigation", "Investigation", "Intake", "Intake", "Intake"),
stringsAsFactors = FALSE)
df %>%
group_by(ID) %>% # Make groups according to ID column
mutate(newcol = ifelse(lead(Date) > Date, "Sub Intake", "None"), # Check next entry in the group to see if Date is after current
newcol = ifelse(Investigation_or_Intake == "Investigation" & is.na(newcol), "None", newcol)) # Change "Investigation" entries with no Intake to "None" 这给了我们
ID Date Investigation_or_Intake newcol
<dbl> <date> <chr> <chr>
1 1 2019-01-01 Investigation Sub Intake
2 2 2019-01-02 Investigation None
3 3 2019-01-03 Investigation Sub Intake
4 4 2019-01-04 Investigation None
5 1 2019-01-02 Intake NA
6 2 2018-12-31 Intake NA
7 3 2019-01-05 Intake NA https://stackoverflow.com/questions/55482609
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