dplyr：根据变量字符串选择的多个列来更改新列

Question

Given this data:

df=data.frame(
  x1=c(2,0,0,NA,0,1,1,NA,0,1),
  x2=c(3,2,NA,5,3,2,NA,NA,4,5),
  x3=c(0,1,0,1,3,0,NA,NA,0,1),
  x4=c(1,0,NA,3,0,0,NA,0,0,1),
  x5=c(1,1,NA,1,3,4,NA,3,3,1))

I want to create an extra column min for the rowwise minimal value of selected columns using dplyr. That's easy using the column names:

df <- df %>% rowwise() %>% mutate(min = min(x2,x5))

But I have a large df with varying column names so I need to match them from some string of values mycols . Now other threads tell me to use select helper functions, but I must be missing something. Here's matches :

mycols <- c("x2","x5")
df <- df %>% rowwise() %>%
  mutate(min = min(select(matches(mycols))))
Error: is.string(match) is not TRUE

And one_of :

mycols <- c("x2","x5")
 df <- df %>%
 rowwise() %>%
 mutate(min = min(select(one_of(mycols))))
Error: no applicable method for 'select' applied to an object of class "c('integer', 'numeric')"
In addition: Warning message:
In one_of(c("x2", "x5")) : Unknown variables: `x2`, `x5`

What am I overlooking? Should select_ work? It doesn't in the following:

df <- df %>%
   rowwise() %>%
   mutate(min = min(select_(mycols)))
Error: no applicable method for 'select_' applied to an object of class "character"

And likewise:

df <- df %>%
  rowwise() %>%
  mutate(min = min(select_(matches(mycols))))
Error: is.string(match) is not TRUE

Answer 1

Here's another solution a bit technical with the help of purrr package from the tidyverse designed for functional programming.

Fist, matches helpers from dplyr takes a regex string as argument not a vector. It is a good way for you to find a regex that matches all your columns. (in the code under you can use the dplyr select helper that you wish)

Then, purrr functions works great with dplyr when you understand the underlying scheme of functionnal programming.

Solution to your problem :

df=data.frame(
  x1=c(2,0,0,NA,0,1,1,NA,0,1),
  x2=c(3,2,NA,5,3,2,NA,NA,4,5),
  x3=c(0,1,0,1,3,0,NA,NA,0,1),
  x4=c(1,0,NA,3,0,0,NA,0,0,1),
  x5=c(1,1,NA,1,3,4,NA,3,3,1))


# regex to get only x2 and x5 column
mycols <- "x[25]"

library(dplyr)

df %>%
  mutate(min_x2_x5 =
           # select columns that you want in df
           select(., matches(mycols)) %>% 
           # use pmap on this subset to get a vector of min from each row.
           # dataframe is a list so pmap works on each element of the list that is to say each row
           purrr::pmap_dbl(min)
         )
#>    x1 x2 x3 x4 x5 min_x2_x5
#> 1   2  3  0  1  1         1
#> 2   0  2  1  0  1         1
#> 3   0 NA  0 NA NA        NA
#> 4  NA  5  1  3  1         1
#> 5   0  3  3  0  3         3
#> 6   1  2  0  0  4         2
#> 7   1 NA NA NA NA        NA
#> 8  NA NA NA  0  3        NA
#> 9   0  4  0  0  3         3
#> 10  1  5  1  1  1         1

I won't explain further about purrr here but it works fine in your case

Answer 2

This was a bit trickier. In case of SE evaluation you'd need to pass the operation as string.

mycols <- '(x2,x5)'
f <- paste0('min',mycols)
df %>% rowwise() %>% mutate_(min = f)
df
# A tibble: 10 × 6
#      x1    x2    x3    x4    x5   min
#   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#1      2     3     0     1     1     1
#2      0     2     1     0     1     1
#3      0    NA     0    NA    NA    NA
#4     NA     5     1     3     1     1
#5      0     3     3     0     3     3
#6      1     2     0     0     4     2
#7      1    NA    NA    NA    NA    NA
#8     NA    NA    NA     0     3    NA
#9      0     4     0     0     3     3
#10     1     5     1     1     1     1