我有一个data.table dt。此data.table首先按列date（我的分组变量）排序，然后按列age排序：
library(data.table)
setkeyv(dt, c("date", "age")) # Sorts table first by column "date" then by "age"
> dt
date age name
1: 2000-01-01 3 Andrew
2: 2000-01-01 4 Ben
3: 2000-01-01 5 Charlie
4: 2000-01-02 6 Adam
5: 2000-01-02 7 Bob
6: 2000-01-02 8 Campbell
我的问题是：我想知道是否可以为每个唯一日期提取前两行？或者更一般地说：
如何提取每组中的前n行？
在此示例中，dt.f中的结果为：
> dt.f = ???????? # function of dt to extract the first 2 rows per unique date
> dt.f
date age name
1: 2000-01-01 3 Andrew
2: 2000-01-01 4 Ben
3: 2000-01-02 6 Adam
4: 2000-01-02 7 Bob
P.S。以下是创建上述data.table的代码：
install.packages("data.table")
library(data.table)
date <- c("2000-01-01","2000-01-01","2000-01-01",
"2000-01-02","2000-01-02","2000-01-02")
age <- c(3,4,5,6,7,8)
name <- c("Andrew","Ben","Charlie","Adam","Bob","Campbell")
dt <- data.table(date, age, name)
setkeyv(dt,c("date","age")) # Sorts table first by column "date" then by "age"
答案 0 :(得分：43)
是的，只需使用.SD并根据需要对其进行索引。
DT[, .SD[1:2], by=date]
date age name
1: 2000-01-01 3 Andrew
2: 2000-01-01 4 Ben
3: 2000-01-02 6 Adam
4: 2000-01-02 7 Bob
@ eddi的建议现场点亮：
使用此代替，速度：
DT[DT[, .I[1:2], by = date]$V1]
# using a slightly larger data set
> microbenchmark(SDstyle=DT[, .SD[1:2], by=date], IStyle=DT[DT[, .I[1:2], by = date]$V1], times=200L)
Unit: milliseconds
expr min lq median uq max neval
SDstyle 13.567070 16.224797 22.170302 24.239881 88.26719 200
IStyle 1.675185 2.018773 2.168818 2.269292 11.31072 200
答案 1 :(得分：1)
可能不是最快的方法，但是如果您不使用键控变量并且需要更多灵活性，它会提供一些灵活性。通过更改选择的Row.ID，可以根据需要调整第一个对象的数量。
dt[, .( age
, name
, Row.ID = rank(age)
)
, by = list(date)][Row.ID %in% (1:2), .(date
, age
, name
)]
答案 2 :(得分：0)
这是一个扩展的解决方案。目标是用 1 行代码从 data.table 中的过滤数据中删除第一行（或其他行）。
我试着用例子来解释：
mpg2 <- data.table(mpg)
mpg2
# manufacturer model displ year cyl trans drv cty hwy fl class
# 1: audi a4 1.8 1999 4 auto(l5) f 18 29 p compact
# 2: audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
# 3: audi a4 2.0 2008 4 manual(m6) f 20 31 p compact
# 4: audi a4 2.0 2008 4 auto(av) f 21 30 p compact
# 5: audi a4 2.8 1999 6 auto(l5) f 16 26 p compact
# ---
# 230: volkswagen passat 2.0 2008 4 auto(s6) f 19 28 p midsize
# 231: volkswagen passat 2.0 2008 4 manual(m6) f 21 29 p midsize
# 232: volkswagen passat 2.8 1999 6 auto(l5) f 16 26 p midsize
# 233: volkswagen passat 2.8 1999 6 manual(m5) f 18 26 p midsize
# 234: volkswagen passat 3.6 2008 6 auto(s6) f 17 26 p midsize
# I wanna first filter the table with year is 1999 and that it is an manual
mpg2[year == "1999" & grepl("manual", trans)]
# manufacturer model displ year cyl trans drv cty hwy fl class
# 1: audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
# 2: audi a4 2.8 1999 6 manual(m5) f 18 26 p compact
# 3: audi a4 quattro 1.8 1999 4 manual(m5) 4 18 26 p compact
# 4: audi a4 quattro 2.8 1999 6 manual(m5) 4 17 25 p compact
# 5: chevrolet corvette 5.7 1999 8 manual(m6) r 16 26 p 2seater
# 6: dodge dakota pickup 4wd 3.9 1999 6 manual(m5) 4 14 17 r pickup
# 7: dodge dakota pickup 4wd 5.2 1999 8 manual(m5) 4 11 17 r pickup
# 8: dodge ram 1500 pickup 4wd 5.2 1999 8 manual(m5) 4 11 16 r pickup
# 9: ford explorer 4wd 4.0 1999 6 manual(m5) 4 15 19 r suv
# 10: ford f150 pickup 4wd 4.2 1999 6 manual(m5) 4 14 17 r pickup
# 11: ford f150 pickup 4wd 4.6 1999 8 manual(m5) 4 13 16 r pickup
# 12: ford mustang 3.8 1999 6 manual(m5) r 18 26 r subcompact
# 13: ford mustang 4.6 1999 8 manual(m5) r 15 22 r subcompact
# 14: honda civic 1.6 1999 4 manual(m5) f 28 33 r subcompact
# 15: honda civic 1.6 1999 4 manual(m5) f 25 32 r subcompact
# 16: honda civic 1.6 1999 4 manual(m5) f 23 29 p subcompact
# 17: hyundai sonata 2.4 1999 4 manual(m5) f 18 27 r midsize
# 18: hyundai sonata 2.5 1999 6 manual(m5) f 18 26 r midsize
# 19: hyundai tiburon 2.0 1999 4 manual(m5) f 19 29 r subcompact
# 20: nissan altima 2.4 1999 4 manual(m5) f 21 29 r compact
# 21: nissan maxima 3.0 1999 6 manual(m5) f 19 25 r midsize
# 22: nissan pathfinder 4wd 3.3 1999 6 manual(m5) 4 15 17 r suv
# 23: subaru forester awd 2.5 1999 4 manual(m5) 4 18 25 r suv
# 24: subaru impreza awd 2.2 1999 4 manual(m5) 4 19 26 r subcompact
# 25: subaru impreza awd 2.5 1999 4 manual(m5) 4 19 26 r subcompact
# 26: toyota 4runner 4wd 2.7 1999 4 manual(m5) 4 15 20 r suv
# 27: toyota 4runner 4wd 3.4 1999 6 manual(m5) 4 15 17 r suv
# 28: toyota camry 2.2 1999 4 manual(m5) f 21 29 r midsize
# 29: toyota camry 3.0 1999 6 manual(m5) f 18 26 r midsize
# 30: toyota camry solara 2.2 1999 4 manual(m5) f 21 29 r compact
# 31: toyota camry solara 3.0 1999 6 manual(m5) f 18 26 r compact
# 32: toyota corolla 1.8 1999 4 manual(m5) f 26 35 r compact
# 33: toyota toyota tacoma 4wd 2.7 1999 4 manual(m5) 4 15 20 r pickup
# 34: toyota toyota tacoma 4wd 3.4 1999 6 manual(m5) 4 15 17 r pickup
# 35: volkswagen gti 2.0 1999 4 manual(m5) f 21 29 r compact
# 36: volkswagen gti 2.8 1999 6 manual(m5) f 17 24 r compact
# 37: volkswagen jetta 1.9 1999 4 manual(m5) f 33 44 d compact
# 38: volkswagen jetta 2.0 1999 4 manual(m5) f 21 29 r compact
# 39: volkswagen jetta 2.8 1999 6 manual(m5) f 17 24 r compact
# 40: volkswagen new beetle 1.9 1999 4 manual(m5) f 35 44 d subcompact
# 41: volkswagen new beetle 2.0 1999 4 manual(m5) f 21 29 r subcompact
# 42: volkswagen passat 1.8 1999 4 manual(m5) f 21 29 p midsize
# 43: volkswagen passat 2.8 1999 6 manual(m5) f 18 26 p midsize
# manufacturer model displ year cyl trans drv cty hwy fl class
# maybe I wanna order it
mpg2[year == "1999" & grepl("manual", trans)][order(model, -displ)]
# manufacturer model displ year cyl trans drv cty hwy fl class
# 1: toyota 4runner 4wd 3.4 1999 6 manual(m5) 4 15 17 r suv
# 2: toyota 4runner 4wd 2.7 1999 4 manual(m5) 4 15 20 r suv
# 3: audi a4 2.8 1999 6 manual(m5) f 18 26 p compact
# 4: audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
# 5: audi a4 quattro 2.8 1999 6 manual(m5) 4 17 25 p compact
# 6: audi a4 quattro 1.8 1999 4 manual(m5) 4 18 26 p compact
# 7: nissan altima 2.4 1999 4 manual(m5) f 21 29 r compact
# 8: toyota camry 3.0 1999 6 manual(m5) f 18 26 r midsize
# 9: toyota camry 2.2 1999 4 manual(m5) f 21 29 r midsize
# 10: toyota camry solara 3.0 1999 6 manual(m5) f 18 26 r compact
# 11: toyota camry solara 2.2 1999 4 manual(m5) f 21 29 r compact
# 12: honda civic 1.6 1999 4 manual(m5) f 28 33 r subcompact
# 13: honda civic 1.6 1999 4 manual(m5) f 25 32 r subcompact
# 14: honda civic 1.6 1999 4 manual(m5) f 23 29 p subcompact
# 15: toyota corolla 1.8 1999 4 manual(m5) f 26 35 r compact
# 16: chevrolet corvette 5.7 1999 8 manual(m6) r 16 26 p 2seater
# 17: dodge dakota pickup 4wd 5.2 1999 8 manual(m5) 4 11 17 r pickup
# 18: dodge dakota pickup 4wd 3.9 1999 6 manual(m5) 4 14 17 r pickup
# 19: ford explorer 4wd 4.0 1999 6 manual(m5) 4 15 19 r suv
# 20: ford f150 pickup 4wd 4.6 1999 8 manual(m5) 4 13 16 r pickup
# 21: ford f150 pickup 4wd 4.2 1999 6 manual(m5) 4 14 17 r pickup
# 22: subaru forester awd 2.5 1999 4 manual(m5) 4 18 25 r suv
# 23: volkswagen gti 2.8 1999 6 manual(m5) f 17 24 r compact
# 24: volkswagen gti 2.0 1999 4 manual(m5) f 21 29 r compact
# 25: subaru impreza awd 2.5 1999 4 manual(m5) 4 19 26 r subcompact
# 26: subaru impreza awd 2.2 1999 4 manual(m5) 4 19 26 r subcompact
# 27: volkswagen jetta 2.8 1999 6 manual(m5) f 17 24 r compact
# 28: volkswagen jetta 2.0 1999 4 manual(m5) f 21 29 r compact
# 29: volkswagen jetta 1.9 1999 4 manual(m5) f 33 44 d compact
# 30: nissan maxima 3.0 1999 6 manual(m5) f 19 25 r midsize
# 31: ford mustang 4.6 1999 8 manual(m5) r 15 22 r subcompact
# 32: ford mustang 3.8 1999 6 manual(m5) r 18 26 r subcompact
# 33: volkswagen new beetle 2.0 1999 4 manual(m5) f 21 29 r subcompact
# 34: volkswagen new beetle 1.9 1999 4 manual(m5) f 35 44 d subcompact
# 35: volkswagen passat 2.8 1999 6 manual(m5) f 18 26 p midsize
# 36: volkswagen passat 1.8 1999 4 manual(m5) f 21 29 p midsize
# 37: nissan pathfinder 4wd 3.3 1999 6 manual(m5) 4 15 17 r suv
# 38: dodge ram 1500 pickup 4wd 5.2 1999 8 manual(m5) 4 11 16 r pickup
# 39: hyundai sonata 2.5 1999 6 manual(m5) f 18 26 r midsize
# 40: hyundai sonata 2.4 1999 4 manual(m5) f 18 27 r midsize
# 41: hyundai tiburon 2.0 1999 4 manual(m5) f 19 29 r subcompact
# 42: toyota toyota tacoma 4wd 3.4 1999 6 manual(m5) 4 15 17 r pickup
# 43: toyota toyota tacoma 4wd 2.7 1999 4 manual(m5) 4 15 20 r pickup
# manufacturer model displ year cyl trans drv cty hwy fl class
# My wish would be to extract the model from 1999 with the highest displ (I could use max, but I will extract the first row)
mpg2[year == "1999" & grepl("manual", trans)][order(model, -displ), .SD[1], model]
# model manufacturer displ year cyl trans drv cty hwy fl class
# 1: 4runner 4wd toyota 3.4 1999 6 manual(m5) 4 15 17 r suv
# 2: a4 audi 2.8 1999 6 manual(m5) f 18 26 p compact
# 3: a4 quattro audi 2.8 1999 6 manual(m5) 4 17 25 p compact
# 4: altima nissan 2.4 1999 4 manual(m5) f 21 29 r compact
# 5: camry toyota 3.0 1999 6 manual(m5) f 18 26 r midsize
# 6: camry solara toyota 3.0 1999 6 manual(m5) f 18 26 r compact
# 7: civic honda 1.6 1999 4 manual(m5) f 28 33 r subcompact
# 8: corolla toyota 1.8 1999 4 manual(m5) f 26 35 r compact
# 9: corvette chevrolet 5.7 1999 8 manual(m6) r 16 26 p 2seater
# 10: dakota pickup 4wd dodge 5.2 1999 8 manual(m5) 4 11 17 r pickup
# 11: explorer 4wd ford 4.0 1999 6 manual(m5) 4 15 19 r suv
# 12: f150 pickup 4wd ford 4.6 1999 8 manual(m5) 4 13 16 r pickup
# 13: forester awd subaru 2.5 1999 4 manual(m5) 4 18 25 r suv
# 14: gti volkswagen 2.8 1999 6 manual(m5) f 17 24 r compact
# 15: impreza awd subaru 2.5 1999 4 manual(m5) 4 19 26 r subcompact
# 16: jetta volkswagen 2.8 1999 6 manual(m5) f 17 24 r compact
# 17: maxima nissan 3.0 1999 6 manual(m5) f 19 25 r midsize
# 18: mustang ford 4.6 1999 8 manual(m5) r 15 22 r subcompact
# 19: new beetle volkswagen 2.0 1999 4 manual(m5) f 21 29 r subcompact
# 20: passat volkswagen 2.8 1999 6 manual(m5) f 18 26 p midsize
# 21: pathfinder 4wd nissan 3.3 1999 6 manual(m5) 4 15 17 r suv
# 22: ram 1500 pickup 4wd dodge 5.2 1999 8 manual(m5) 4 11 16 r pickup
# 23: sonata hyundai 2.5 1999 6 manual(m5) f 18 26 r midsize
# 24: tiburon hyundai 2.0 1999 4 manual(m5) f 19 29 r subcompact
# 25: toyota tacoma 4wd toyota 3.4 1999 6 manual(m5) 4 15 17 r pickup
# model manufacturer displ year cyl trans drv cty hwy fl class
# my goal now is actually from the orginal table to remove those rows, we will you then .I which will return the frow ID from those ones. However it should be a bit differently written. All of this in 1 line of code:
# mpg2[year == "1999" & grepl("manual", trans)] is same as mpg2[mpg2[, .I[year == "1999" & grepl("manual", trans)]]]
# mpg2[year == "1999" & grepl("manual", trans)] is same as mpg2[mpg2[, .I[year == "1999" & grepl("manual", trans)], model]$V1]
# goal is to first get row ID (V1) of filtered data and keep our important variable for future steps
mpg2[, .I[year == "1999" & grepl("manual", trans)], .(model, displ)]
# model displ V1
# 1: a4 1.8 2
# 2: a4 2.8 6
# 3: a4 quattro 1.8 8
# 4: a4 quattro 2.8 13
# 5: corvette 5.7 24
# 6: dakota pickup 4wd 3.9 52
# 7: dakota pickup 4wd 5.2 56
# 8: ram 1500 pickup 4wd 5.2 72
# 9: explorer 4wd 4.0 79
# 10: f150 pickup 4wd 4.2 85
# 11: f150 pickup 4wd 4.6 86
# 12: mustang 3.8 91
# 13: mustang 4.6 96
# 14: civic 1.6 100
# 15: civic 1.6 102
# 16: civic 1.6 103
# 17: sonata 2.4 110
# 18: sonata 2.5 114
# 19: tiburon 2.0 117
# 20: altima 2.4 142
# 21: maxima 3.0 149
# 22: pathfinder 4wd 3.3 152
# 23: forester awd 2.5 160
# 24: impreza awd 2.2 167
# 25: impreza awd 2.5 168
# 26: 4runner 4wd 2.7 174
# 27: 4runner 4wd 3.4 177
# 28: camry 2.2 180
# 29: camry 3.0 185
# 30: camry solara 2.2 188
# 31: camry solara 3.0 192
# 32: corolla 1.8 196
# 33: toyota tacoma 4wd 2.7 201
# 34: toyota tacoma 4wd 3.4 204
# 35: gti 2.0 208
# 36: gti 2.8 212
# 37: jetta 1.9 213
# 38: jetta 2.0 214
# 39: jetta 2.8 221
# 40: new beetle 1.9 222
# 41: new beetle 2.0 224
# 42: passat 1.8 228
# 43: passat 2.8 233
# model displ V1
# then order and get the first row
mpg2[, .I[year == "1999" & grepl("manual", trans)], .(model, displ)][order(model, -displ), .SD[1], model]
# model displ V1
# 1: 4runner 4wd 3.4 177
# 2: a4 2.8 6
# 3: a4 quattro 2.8 13
# 4: altima 2.4 142
# 5: camry 3.0 185
# 6: camry solara 3.0 192
# 7: civic 1.6 100
# 8: corolla 1.8 196
# 9: corvette 5.7 24
# 10: dakota pickup 4wd 5.2 56
# 11: explorer 4wd 4.0 79
# 12: f150 pickup 4wd 4.6 86
# 13: forester awd 2.5 160
# 14: gti 2.8 212
# 15: impreza awd 2.5 168
# 16: jetta 2.8 221
# 17: maxima 3.0 149
# 18: mustang 4.6 96
# 19: new beetle 2.0 224
# 20: passat 2.8 233
# 21: pathfinder 4wd 3.3 152
# 22: ram 1500 pickup 4wd 5.2 72
# 23: sonata 2.5 114
# 24: tiburon 2.0 117
# 25: toyota tacoma 4wd 3.4 204
# model displ V1
# V1 is the row ID from original table, we have then just to remove it from it
mpg2[!mpg2[, .I[year == "1999" & grepl("manual", trans)], .(model, displ)][order(model, -displ), .SD[1], model]$V1]
# manufacturer model displ year cyl trans drv cty hwy fl class
# 1: audi a4 1.8 1999 4 auto(l5) f 18 29 p compact
# 2: audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
# 3: audi a4 2.0 2008 4 manual(m6) f 20 31 p compact
# 4: audi a4 2.0 2008 4 auto(av) f 21 30 p compact
# 5: audi a4 2.8 1999 6 auto(l5) f 16 26 p compact
# ---
# 205: volkswagen passat 1.8 1999 4 auto(l5) f 18 29 p midsize
# 206: volkswagen passat 2.0 2008 4 auto(s6) f 19 28 p midsize
# 207: volkswagen passat 2.0 2008 4 manual(m6) f 21 29 p midsize
# 208: volkswagen passat 2.8 1999 6 auto(l5) f 16 26 p midsize
# 209: volkswagen passat 3.6 2008 6 auto(s6) f 17 26 p midsize