R Dplyr变异，计算每一行的标准差 [英] R Dplyr mutate, calculating standard deviation for each row

问题描述

我正在尝试计算数据框中某些列的均值和标准差，并将这些值返回到数据框中的新列。我可以用它来表示平均值：

I am trying to calculate the mean and standard deviation from certain columns in a data frame, and return those values to new columns in the data frame. I can get this to work for mean:

library(dplyr)
mtcars = mutate(mtcars, mean=(hp+drat+wt)/3)

但是，当我尝试对标准偏差执行相同操作时，我有一个问题，因为我无法像我那样轻易地对等式进行硬编码。因此，我尝试使用如下函数：

However, when I try to do the same for standard deviation, I have an issue, because I cannot hardcode the equation like I did for mean very easily. So, I try to use a function, as follows:

mtcars = mutate(mtcars, mean=(hp+drat+wt)/3, stdev = sd(hp,drat,wt))

导致错误错误在sd（hp，drat，wt）中：未使用的参数（wt）。如何纠正我的语法？谢谢。

Resulting in the error "Error in sd(hp, drat, wt) : unused argument (wt)". How can I correct my syntax? Thank you.

推荐答案

您可以尝试

library(dplyr)
library(matrixStats)
nm1 <- c('hp', 'drat', 'wt')
res1 <- mtcars %>% 
           mutate(Mean= rowMeans(.[nm1]), stdev=rowSds(as.matrix(.[nm1])))

head(res1,3)
#   mpg cyl disp  hp drat    wt  qsec vs am gear carb     Mean    stdev
#1 21.0   6  160 110 3.90 2.620 16.46  0  1    4    4 38.84000 61.62969
#2 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4 38.92500 61.55489
#3 22.8   4  108  93 3.85 2.320 18.61  1  1    4    1 33.05667 51.91809

或使用 do

res2 <- mtcars %>% 
             rowwise() %>%
             do(data.frame(., Mean=mean(unlist(.[nm1])),
                         stdev=sd(unlist(.[nm1]))))

head(res2,3)
#   mpg cyl disp  hp drat    wt  qsec vs am gear carb     Mean    stdev
#1 21.0   6  160 110 3.90 2.620 16.46  0  1    4    4 38.84000 61.62969
#2 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4 38.92500 61.55489
#3 22.8   4  108  93 3.85 2.320 18.61  1  1    4    1 33.05667 51.91809

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