我感兴趣的是go 识别同时具有时间固定值和时变值的敏感数据集.我想(a)根据社会保险号对所有 case 进行分组，(b)为这些 case 分配一个唯一的ID，然后(c)删除社会保险号.
下面是一个示例数据集:
personal_id gender temperature
111-11-1111 M 99.6
999-999-999 F 98.2
111-11-1111 M 97.8
999-999-999 F 98.3
888-88-8888 F 99.0
111-11-1111 M 98.9
任何解决方案都将不胜感激.
dplyr有一个group_indices函数，用于创建唯一的组ID
library(dplyr)
data <- data.frame(personal_id = c("111-111-111", "999-999-999", "222-222-222", "111-111-111"),
gender = c("M", "F", "M", "M"),
temperature = c(99.6, 98.2, 97.8, 95.5))
data$group_id <- data %>% group_indices(personal_id)
data <- data %>% select(-personal_id)
data
gender temperature group_id
1 M 99.6 1
2 F 98.2 3
3 M 97.8 2
4 M 95.5 1
或在同一管道内(https://github.com/tidyverse/dplyr/issues/2160):
data %>%
mutate(group_id = group_indices(., personal_id))