当前数据框看起来像这样：
Scenario Month A B C
1 1 -0.593186301 1.045550808 -0.593816304
1 2 0.178626141 2.043084432 0.111370583
1 3 1.205779717 -0.324083723 -1.397716949
2 1 0.933615199 0.052647056 -0.656486153
2 2 1.647291688 -1.065793671 0.799040546
2 3 1.613663101 -1.955567231 -1.817457972
3 1 -0.621991775 1.634069402 -1.404981646
3 2 -1.899326887 -0.836322394 -1.826351541
3 3 0.164235141 -1.160701812 1.238246459
我想在Month = 1的行的顶部添加行，如下所示。我知道dplyr具有add_rows函数，但是我想根据条件添加行。任何帮助深表感谢。
Scenario Month A B C
0
1 1 -0.593186301 1.045550808 -0.593816304
1 2 0.178626141 2.043084432 0.111370583
1 3 1.205779717 -0.324083723 -1.397716949
0
2 1 0.933615199 0.052647056 -0.656486153
2 2 1.647291688 -1.065793671 0.799040546
2 3 1.613663101 -1.955567231 -1.817457972
0
3 1 -0.621991775 1.634069402 -1.404981646
3 2 -1.899326887 -0.836322394 -1.826351541
3 3 0.164235141 -1.160701812 1.238246459
答案 0 :(得分：4)
使用tidyverse的解决方案。
library(tidyverse)
dat2 <- dat %>%
split(f = .$Scenario) %>%
map_dfr(~bind_rows(tibble(Scenario = 0), .x))
dat2
# # A tibble: 12 x 5
# Scenario Month A B C
# <dbl> <int> <dbl> <dbl> <dbl>
# 1 0 NA NA NA NA
# 2 1 1 -0.593 1.05 -0.594
# 3 1 2 0.179 2.04 0.111
# 4 1 3 1.21 -0.324 -1.40
# 5 0 NA NA NA NA
# 6 2 1 0.934 0.0526 -0.656
# 7 2 2 1.65 -1.07 0.799
# 8 2 3 1.61 -1.96 -1.82
# 9 0 NA NA NA NA
# 10 3 1 -0.622 1.63 -1.40
# 11 3 2 -1.90 -0.836 -1.83
# 12 3 3 0.164 -1.16 1.24
数据
dat <- read.table(text = "Scenario Month A B C
1 1 -0.593186301 1.045550808 -0.593816304
1 2 0.178626141 2.043084432 0.111370583
1 3 1.205779717 -0.324083723 -1.397716949
2 1 0.933615199 0.052647056 -0.656486153
2 2 1.647291688 -1.065793671 0.799040546
2 3 1.613663101 -1.955567231 -1.817457972
3 1 -0.621991775 1.634069402 -1.404981646
3 2 -1.899326887 -0.836322394 -1.826351541
3 3 0.164235141 -1.160701812 1.238246459 ",
header = TRUE)
答案 1 :(得分：3)
以某种方式，add_row对其.before参数不采用多个值。
一种方法是split到Month = 1所在的数据帧，然后使用add_row上方的Month = 1为每个数据帧添加一行。
library(tidyverse)
map_df(split(df, cumsum(df$Month == 1)),
~ add_row(., Scenario = 0, .before = which(.$Month == 1)))
# Scenario Month A B C
#1 0 NA NA NA NA
#2 1 1 -0.5931863 1.04555081 -0.5938163
#3 1 2 0.1786261 2.04308443 0.1113706
#4 1 3 1.2057797 -0.32408372 -1.3977169
#5 0 NA NA NA NA
#6 2 1 0.9336152 0.05264706 -0.6564862
#7 2 2 1.6472917 -1.06579367 0.7990405
#8 2 3 1.6136631 -1.95556723 -1.8174580
#9 0 NA NA NA NA
#10 3 1 -0.6219918 1.63406940 -1.4049816
#11 3 2 -1.8993269 -0.83632239 -1.8263515
#12 3 3 0.1642351 -1.16070181 1.2382465
答案 2 :(得分：2)
这是data.table
library(data.table)
setDT(df1)[, .SD[c(.N+1, seq_len(.N))], Scenario][
!duplicated(Scenario), Scenario := 0][]
# Scenario Month A B C
# 1: 0 NA NA NA NA
# 2: 1 1 -0.5931863 1.04555081 -0.5938163
# 3: 1 2 0.1786261 2.04308443 0.1113706
# 4: 1 3 1.2057797 -0.32408372 -1.3977169
# 5: 0 NA NA NA NA
# 6: 2 1 0.9336152 0.05264706 -0.6564862
# 7: 2 2 1.6472917 -1.06579367 0.7990405
# 8: 2 3 1.6136631 -1.95556723 -1.8174580
# 9: 0 NA NA NA NA
#10: 3 1 -0.6219918 1.63406940 -1.4049816
#11: 3 2 -1.8993269 -0.83632239 -1.8263515
#12: 3 3 0.1642351 -1.16070181 1.2382465
或者如评论中提到的@ chinsoon12
setDT(df1)[, rbindlist(.(.(Scenario=0L), c(.(Scenario=rep(Scenario, .N)),
.SD)), use.names=TRUE, fill=TRUE), by=.(Scenario)][, -1L]
df1 <- structure(list(Scenario = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L
), Month = c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), A = c(-0.593186301,
0.178626141, 1.205779717, 0.933615199, 1.647291688, 1.613663101,
-0.621991775, -1.899326887, 0.164235141), B = c(1.045550808,
2.043084432, -0.324083723, 0.052647056, -1.065793671, -1.955567231,
1.634069402, -0.836322394, -1.160701812), C = c(-0.593816304,
0.111370583, -1.397716949, -0.656486153, 0.799040546, -1.817457972,
-1.404981646, -1.826351541, 1.238246459)), class = "data.frame",
row.names = c(NA,
-9L))
答案 3 :(得分：0)
这是使用基数R的简单方法（无循环）-
df1 <- df[rep(1:nrow(df), (df$Month == 1)+1), ]
df1[duplicated(df1, fromLast = T), ] <- NA
df1$Scenario[is.na(df1$Scenario)] <- 0
df1
Scenario Month A B C
1 0 NA NA NA NA
1.1 1 1 -0.5931863 1.04555081 -0.5938163
2 1 2 0.1786261 2.04308443 0.1113706
3 1 3 1.2057797 -0.32408372 -1.3977169
4 0 NA NA NA NA
4.1 2 1 0.9336152 0.05264706 -0.6564862
5 2 2 1.6472917 -1.06579367 0.7990405
6 2 3 1.6136631 -1.95556723 -1.8174580
7 0 NA NA NA NA
7.1 3 1 -0.6219918 1.63406940 -1.4049816
8 3 2 -1.8993269 -0.83632239 -1.8263515
9 3 3 0.1642351 -1.16070181 1.2382465
数据-
df <- structure(list(Scenario = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L
), Month = c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), A = c(-0.593186301,
0.178626141, 1.205779717, 0.933615199, 1.647291688, 1.613663101,
-0.621991775, -1.899326887, 0.164235141), B = c(1.045550808,
2.043084432, -0.324083723, 0.052647056, -1.065793671, -1.955567231,
1.634069402, -0.836322394, -1.160701812), C = c(-0.593816304,
0.111370583, -1.397716949, -0.656486153, 0.799040546, -1.817457972,
-1.404981646, -1.826351541, 1.238246459)), class = "data.frame", row.names = c(NA,
-9L))