R 如何获取具有正值的最后一行号
一种简明的方法是R 如何获取具有正值的最后一行号,r,dplyr,R,Dplyr,一种简明的方法是 library(tidyverse) df <- tibble(a = c(1, 2, 3, 0, 5, 0, 7, 0, 0, 0)) %>% print() 让我们做一个较长的df$a并比较所有方法: df[1:which.max(cumsum(df$a)),] head(df,1-which.max(rev(df$a)>0)) df[rev(cumsum(rev(df$a>0)))>0,] df 0)),], df[1:which.max
library(tidyverse)
df <- tibble(a = c(1, 2, 3, 0, 5, 0, 7, 0, 0, 0)) %>% print()
让我们做一个较长的df$a
并比较所有方法:
df[1:which.max(cumsum(df$a)),]
head(df,1-which.max(rev(df$a)>0))
df[rev(cumsum(rev(df$a>0)))>0,]
df 0)),],
df[1:which.max(总和(df$a)),],
水头(df,1-最大值(修订版(df$a)>0)),
df[rev(积数)(rev(df$a>0)))>0,],
df[1:tail(符号(df$a)==1),1),],
次=10000
)
#单位:微秒
#expr最小lq平均uq最大neval cld
#df[1:max(其中(df$a>0)),]52.817 58.5800 102.80519 62.2160 71.5910 17108.65 10000 a
#df[1:which.max(总和(df$a)),]36.190 40.7620 65.68274 43.0785 49.7835 18827.08 10000 a
#水头(df,1-哪个最大值(修订版(df$a)>0))214.812 230.7590 355.37321 249.1085 297.4340 18158.22 10000摄氏度
#df[rev(累积值(rev(df$a>0)))>0,]106.391114.6345192.44990124.4690141.565014473.121000B
#df[1:tail(符号(df$a)==1),1),]106.152 116.8985 207.69863 125.6520 150.3425 195384.36 10000 b
尾部(符号(df$a)==1),1)
df[1:max(which(df$a>0)),]
# A tibble: 7 x 1
# a
# <dbl>
# 1 1
# 2 2
# 3 3
# 4 0
# 5 5
# 6 0
# 7 7
df[1:which.max(cumsum(df$a)),]
head(df,1-which.max(rev(df$a)>0))
df[rev(cumsum(rev(df$a>0)))>0,]
df <- data.frame(a = rbinom(5000, 2, 0.2) - 1)
microbenchmark(
df[1:max(which(df$a>0)),],
df[1:which.max(cumsum(df$a)),],
head(df,1-which.max(rev(df$a)>0)),
df[rev(cumsum(rev(df$a>0)))>0,],
df[1:tail(which(sign(df$a) == 1), 1),],
times = 10000
)
# Unit: microseconds
# expr min lq mean median uq max neval cld
# df[1:max(which(df$a > 0)), ] 52.817 58.5800 102.80519 62.2160 71.5910 17108.65 10000 a
# df[1:which.max(cumsum(df$a)), ] 36.190 40.7620 65.68274 43.0785 49.7835 18827.08 10000 a
# head(df, 1 - which.max(rev(df$a) > 0)) 214.812 230.7590 355.37321 249.1085 297.4340 18158.22 10000 c
# df[rev(cumsum(rev(df$a > 0))) > 0, ] 106.391 114.6345 192.44990 124.4690 141.5650 14473.12 10000 b
# df[1:tail(which(sign(df$a) == 1), 1), ] 106.152 116.8985 207.69863 125.6520 150.3425 195384.36 10000 b