为R中的每个级别选择前80个观测值

Question

我有一个如下所示的数据集:

structure(list(A = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25"), class = "factor"), T = c(0.04, 0.08, 0.12, 0.16, 0.2, 
0.24), X = c(464.4, 464.4, 464.4, 464.4, 464.4, 464.4), Y = c(418.5, 
418.5, 418.5, 418.5, 418.5, 418.5), V = c(0, 0, 0, 0, 0, 0), 
    GD = c(0, 0, 0, 0, 0, 0), ND = c(NA, 0, 0, 0, 0, 0), ND2 = c(NA, 
    0, 0, 0, 0, 0), TID = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("t1", 
    "t10", "t11", "t12", "t13", "t14", "t15", "t16", "t17", "t18", 
    "t19", "t2", "t20", "t21", "t22", "t23", "t24", "t25", "t3", 
    "t4", "t5", "t6", "t7", "t8", "t9"), class = "factor")), .Names = c("A", 
"T", "X", "Y", "V", "GD", "ND", "ND2", "TID"), row.names = c(NA, 
6L), class = "data.frame")

我想为每个TID选择所有变量的前80个观测值.到目前为止,我只能使用代码使用第一个TID执行此操作:

sub.data1<-NM[1:80, ]

我怎么能为我所有其他TID做到这一点？

谢谢!

Answer 1

我会做:

lapply(split(dat, dat$TID), head, 80)

它返回一个包含80(或更少)行的data.frames列表.相反,如果您想将所有内容都放在一个data.frame中:

do.call(rbind, lapply(split(dat, dat$TID), head, 80))

Answer 2

使用功能ddply()的plyr,你可以通过TID拆分数据,然后选择福斯特80 head(),然后再次把所有在一个数据帧,

library(plyr)
ddply(NM, .(TID), head, n = 80)