r - 如何对 data.frame 进行子集化？

Question

我有一个这样的数据集

a <- data.frame(var1 = c("patientA", "patientA", "patientA", "patientB", "patientB", "patientB", "patientB"),
                var2 = as.Date(c("2015-01-02","2015-01-04","2015-02-02","2015-02-06","2015-01-02","2015-01-07","2015-04-02")),
                var3 = c(F, T, F, F, F, T, F)               
                )
sequ <- rle(as.character(a$var1))
a$sequ <- sequence(sequ$lengths)

生产

> a
      var1       var2  var3 sequ
1 patientA 2015-01-02 FALSE    1
2 patientA 2015-01-04  TRUE    2
3 patientA 2015-02-02 FALSE    3
4 patientB 2015-02-06 FALSE    1
5 patientB 2015-01-02 FALSE    2
6 patientB 2015-01-07  TRUE    3
7 patientB 2015-04-02 FALSE    4

如何子集/过滤此数据集，以便获得 var3 == TRUE 和 var2 日期值大于 var3 == TRUE 的行中的所有行(患者，var1？我试过

subset(a, (var3 == TRUE) & (var2 > var3))

但这不会产生正确的结果集。正确的是

#       var1       var2  var3 sequ
# 1 patientA 2015-01-04  TRUE    2
# 2 patientA 2015-02-02 FALSE    3
# 3 patientB 2015-02-06 FALSE    1
# 4 patientB 2015-01-07  TRUE    3
# 5 patientB 2015-04-02 FALSE    4

Answer 1

你可以试试 data.table .在这里，我们将“data.frame”转换为“data.table”(setDT(a))，按“var1”分组，我们得到大于或等于相应“var2”元素的“var2”元素的逻辑索引'var3' 为 TRUE 并对数据集进行子集 .SD .

library(data.table)
setDT(a)[,.SD[var2 >= var2[var3]], var1]
#       var1       var2  var3 sequ
#1: patientA 2015-01-04  TRUE    2
#2: patientA 2015-02-02 FALSE    3
#3: patientB 2015-02-06 FALSE    1
#4: patientB 2015-01-07  TRUE    3
#5: patientB 2015-04-02 FALSE    4

使用 base R 的选项(假设数据按'var1'排序)

a[with(a, var2>=rep(var2[var3], table(var1))),]
#      var1       var2  var3 sequ
#2 patientA 2015-01-04  TRUE    2
#3 patientA 2015-02-02 FALSE    3
#4 patientB 2015-02-06 FALSE    1
#6 patientB 2015-01-07  TRUE    3
#7 patientB 2015-04-02 FALSE    4