-1
names <- names(mtcars)
str(mtcars[names[1]]) # shows the str for mpg data frame

I would like to select everything EXCEPT names[1] which in this example is mpg.

Tried:

str(mtcars[!names[1]])
Error in !names[1] : invalid argument type

Also tried

str(mtcars[-names[1]])
Error in -names[1] : invalid argument to unary operator

How can I select mtcars minus names[1] feature using square braces syntax?

Doug Fir
  • 19,971
  • 47
  • 169
  • 299
  • 2
    Possible duplicate of [Selecting columns in R data frame based on those \*not\* in a vector](https://stackoverflow.com/questions/12208090/selecting-columns-in-r-data-frame-based-on-those-not-in-a-vector) – astrofunkswag Nov 09 '18 at 00:53

2 Answers2

1
str(mtcars[!names %in% names[1]])

'data.frame':   32 obs. of  10 variables:
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...
astrofunkswag
  • 2,608
  • 12
  • 25
1

If you want to use numerical indexing for selection, you can just use a - in front of that to do the reverse.

str(mtcars[names[1]]) # shows the str for mpg data frame
'data.frame':   32 obs. of  1 variable:
 $ mpg: num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...

str(mtcars[names[-1]])
'data.frame':   32 obs. of  10 variables:
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...
dshkol
  • 1,208
  • 7
  • 23