数据低于
dialled Ringing state duration NA NA NA 0 NA NA NA 0 NA NA NA 0 NA NA NA 0 123 NA NA 0 123 NA NA 0 123 NA NA 0 123 NA NA 60 NA NA active 0 NA NA active 0 NA NA inactive 0 NA NA inactive 0 123 NA inactive 0 123 NA inactive 0 123 NA inactive 0 NA NA inactive 0 NA NA inactive 0 NA NA inactive 0 222 NA inactive 0 222 NA inactive 0 222 NA inactive 37 NA NA active 0 NA NA active 0 NA NA inactive 0 123 NA inactive 0 123 NA inactive 0 123 NA active 60 NA NA active 0 NA NA active 0 NA NA active 0 NA NA active 0 123 NA inactive 0 123 NA inactive 0 123 NA inactive 0 answer i am looking for is dialled Ringing state duration 123 NA NA 0 123 NA NA 60 123 NA inactive 0 123 NA inactive 0 222 NA inactive 0 222 NA inactive 37 123 NA inactive 0 123 NA inactive 60 123 NA inactive 0 123 NA inactive 0
另外如果你可以帮助我获得紧接的下一行，在每个小组的最后一行之后和Rbind他们
答案 0 :(得分：1)
在data.table v1.9.5中，有一个新功能rleid()可帮助完成此任务相当简单。您可以按照these instructions：
require(data.table)
setDT(df)[, if (!is.na(dialled[1L])) .SD[c(1L, .N)],
by=.(dialled, rleid(dialled))]
# dialled rleid Ringing state duration
# 1: 123 2 NA NA 0
# 2: 123 2 NA NA 60
# 3: 123 4 NA inactive 0
# 4: 123 4 NA inactive 0
# 5: 222 6 NA inactive 0
# 6: 222 6 NA inactive 37
# 7: 123 8 NA inactive 0
# 8: 123 8 NA active 60
# 9: 123 10 NA inactive 0
# 10: 123 10 NA inactive 0
.SD包含by =中指定的组的数据子集。
答案 1 :(得分：0)
你可以创建一个分组变量＆＃34; grp＆＃34; （类似于here）。子集＆＃34; df＆＃34;的行。那不是＆＃39; 0＆＃39;对于＆＃34; grp＆＃34;，使用slice获取每个＆＃34; grp＆＃34;，ungroup的第一行和最后一行，并删除grp变量。< / p>
rl <- rle(!is.na(df$dialled))
grp <- inverse.rle(within.list(rl,
values[values] <- cumsum(values)[values]))
df$grp <- grp
library(dplyr)
df %>%
filter(grp!=0) %>%
group_by(grp) %>%
slice(c(1, n()))%>%
ungroup() %>%
select(-grp)
# dialled Ringing state duration
#1 123 NA NA 0
#2 123 NA NA 60
#3 123 NA inactive 0
#4 123 NA inactive 0
#5 222 NA inactive 0
#6 222 NA inactive 37
#7 123 NA inactive 0
#8 123 NA active 60
#9 123 NA inactive 0
#10 123 NA inactive 0
或者base R选项是获取子集数据集的第一行和最后一行的行索引＆＃34; df1＆＃34;基于＆＃34; grp＆＃34;然后用它来提取行。
df1 <- df[grp!=0,]
df2 <- df1[unlist(tapply(1:nrow(df1), grp[grp!=0],
FUN=function(x) c(head(x,1), tail(x,1)))),]
评论中并不清楚。也许这有帮助
df2 %>%
group_by(grp) %>%
filter(any(duration>0)) %>%
slice(1)
# dialled Ringing state duration grp
#1 123 NA NA 0 1
#2 222 NA inactive 0 3
#3 123 NA inactive 0 4
df <- structure(list(dialled = c(NA, NA, NA, NA, 123L, 123L, 123L,
123L, NA, NA, NA, NA, 123L, 123L, 123L, NA, NA, NA, 222L, 222L,
222L, NA, NA, NA, 123L, 123L, 123L, NA, NA, NA, NA, 123L, 123L,
123L), Ringing = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA), state = c(NA, NA, NA, NA, NA, NA,
NA, NA, "active", "active", "inactive", "inactive", "inactive",
"inactive", "inactive", "inactive", "inactive", "inactive", "inactive",
"inactive", "inactive", "active", "active", "inactive", "inactive",
"inactive", "active", "active", "active", "active", "active",
"inactive", "inactive", "inactive"), duration = c(0L, 0L, 0L,
0L, 0L, 0L, 0L, 60L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 37L, 0L, 0L, 0L, 0L, 0L, 60L, 0L, 0L, 0L, 0L, 0L, 0L,
0L)), .Names = c("dialled", "Ringing", "state", "duration"),
class = "data.frame", row.names = c(NA, -34L))