在编程中使用dplyr mutate() [英] use dplyr mutate() in programming

问题描述

我正在尝试使用mutate将列名分配给变量.

I am trying to assign a column name to a variable using mutate.

df <-data.frame(x = sample(1:100, 50), y = rnorm(50))

new <- function(name){
     df%>%mutate(name = ifelse(x <50, "small", "big"))
}

我跑步时

new(name = "newVar")

它不起作用.我知道mutate_()可以帮助您，但我正在努力将其与ifelse一起使用.

it doesn't work. I know mutate_() could help but I'm struggling in using it together with ifelse.

任何帮助将不胜感激.

推荐答案

使用dplyr 0.7.1及其在NSE中的改进，您必须UQ自变量mutate，然后在分配时使用:= .这里有很多有关dplyr和NSE编程的信息: https://cran.r-project.org/web/packages/dplyr/vignettes/programming.html

Using dplyr 0.7.1 and its advances in NSE, you have to UQ the argument to mutate and then use := when assigning. There is lots of info on programming with dplyr and NSE here: https://cran.r-project.org/web/packages/dplyr/vignettes/programming.html

为了避免混淆，我将函数参数的名称更改为myvar.如果您还有更多要重新编码的类别，也可以使用dplyr中的case_when代替ifelse.

I've changed the name of the function argument to myvar to avoid confusion. You could also use case_when from dplyr instead of ifelse if you have more categories to recode.

df <- data.frame(x = sample(1:100, 50), y = rnorm(50))

new <- function(myvar){
    df %>% mutate(UQ(myvar) := ifelse(x < 50, "small", "big"))
}

new(myvar = "newVar")

这将返回

     x        y newVar
1   37  1.82669  small
2   63 -0.04333    big
3   46  0.20748  small
4   93  0.94169    big
5   83 -0.15678    big
6   14 -1.43567  small
7   61  0.35173    big
8   26 -0.71826  small
9   21  1.09237  small
10  90  1.99185    big
11  60 -1.01408    big
12  70  0.87534    big
13  55  0.85325    big
14  38  1.70972  small
15   6  0.74836  small
16  23 -0.08528  small
17  27  2.02613  small
18  76 -0.45648    big
19  97  1.20124    big
20  99 -0.34930    big
21  74  1.77341    big
22  72 -0.32862    big
23  64 -0.07994    big
24  53 -0.40116    big
25  16 -0.70226  small
26   8  0.78965  small
27  34  0.01871  small
28  24  1.95154  small
29  82 -0.70616    big
30  77 -0.40387    big
31  43 -0.88383  small
32  88 -0.21862    big
33  45  0.53409  small
34  29 -2.29234  small
35  54  1.00730    big
36  22 -0.62636  small
37 100  0.75193    big
38  52 -0.41389    big
39  36  0.19817  small
40  89 -0.49224    big
41  81 -1.51998    big
42  18  0.57047  small
43  78 -0.44445    big
44  49 -0.08845  small
45  20  0.14014  small
46  32  0.48094  small
47   1 -0.12224  small
48  66  0.48769    big
49  11 -0.49005  small
50  87 -0.25517    big

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