Is there a simpler version of renaming columns with alternating patterns? Or tidyverse methods?

Question

My Data

So I have a data frame that I am working with below:

structure(list(V1 = c(3L, 3L, 3L, 2L, 4L, 1L), V2 = c(1L, 1L, 
1L, 1L, 1L, 1L), V3 = c(2L, 2L, 2L, 1L, 3L, 2L), V4 = c(2L, 2L, 
3L, 1L, 1L, 1L), V5 = c(3L, 3L, 4L, 1L, 3L, 3L), V6 = c(3L, 3L, 
4L, 3L, 3L, 3L), V7 = c(2L, 2L, 1L, 1L, 3L, 3L), V8 = c(3L, 3L, 
4L, 4L, 3L, 3L), V9 = c(3L, 3L, 3L, 2L, 3L, 3L), V10 = c(2L, 
2L, 1L, 1L, 1L, 1L)), row.names = c(NA, 6L), class = "data.frame")

It looks like this:

 V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
1  3  1  2  2  3  3  2  3  3   2
2  3  1  2  2  3  3  2  3  3   2
3  3  1  2  3  4  4  1  4  3   1
4  2  1  1  1  1  3  1  4  2   1
5  4  1  3  1  3  3  3  3  3   1
6  1  1  2  1  3  3  3  3  3   1

Solution So Far

The best code I have come up with for renaming the variables quickly is this:

new_names <- outer("cope",
                   1:10, 
                   paste, 
                   sep="_")
names(data1) <- new_names
data1

Which gives me this data frame:

  cope_1 cope_2 cope_3 cope_4 cope_5 cope_6 cope_7 cope_8 cope_9 cope_10
1      3      1      2      2      3      3      2      3      3       2
2      3      1      2      2      3      3      2      3      3       2
3      3      1      2      3      4      4      1      4      3       1
4      2      1      1      1      1      3      1      4      2       1
5      4      1      3      1      3      3      3      3      3       1
6      1      1      2      1      3      3      3      3      3       1

Question

While this serves my purpose well enough, it has made me consider two questions for the future. First, is there a way to simplify the code down in order to make it one line? I was thinking something that worked within dplyr if possible because that is what I am most accustomed to working with.

Second, I foresee issues on the horizon if there are, say, 30 variables, with some having repeating patterns and some being unique. What is the most economical use of time when renaming variables like these? I know rep is one option, but I am only aware of how it can repeat but not separate values into multiple patterns. I'm thinking along the lines of something like this, which would be easier to write with some kind of pattern and stops:

names <- c("v1","v2","v3","c1","c2","c3","u","p","z1","z2")

For example:

names <- c("v1","v2","v3","c1","c2","c3","u","p","z1","z2")
colnames(data1) <- names
data1

  v1 v2 v3 c1 c2 c3 u p z1 z2
1   3  1  2  2  3  3 2 3  3  2
2   3  1  2  2  3  3 2 3  3  2
3   3  1  2  3  4  4 1 4  3  1
4   2  1  1  1  1  3 1 4  2  1
5   4  1  3  1  3  3 3 3  3  1
6   1  1  2  1  3  3 3 3  3  1
7   3  1  3  1  3  2 2 2  3  2
8   3  2  1  2  3  2 3 3  2  1
9   3  2  4  1  2  4 2 3  4  1
10  4  2  4  2  3  4 3 3  4  1

This is time-consuming if you spell it out manually:

names <- c("cope_1", "cope_2","cope_3","sad_1","sad_2","sad_3","u","p","zip_1","zip_2")
colnames(data1) <- names
data1

Which does get you what you want, yet slowly:

  cope_1 cope_2 cope_3 sad_1 sad_2 sad_3 u p zip_1 zip_2
1      3      1      2     2     3     3 2 3     3     2
2      3      1      2     2     3     3 2 3     3     2
3      3      1      2     3     4     4 1 4     3     1
4      2      1      1     1     1     3 1 4     2     1
5      4      1      3     1     3     3 3 3     3     1
6      1      1      2     1     3     3 3 3     3     1

And something like outer doesnt seem to fit here:

outer("cope",
      1:3,
      paste,
      sep="_",
      "sad",
      1:3,
      paste,
      sep="_",
      "u",
      "p")

So if there is a better way of naming chunks of variables like this, that would be great to know.

You'll need to provide more details regarding your second question - `tidyselect` semantics offer a variety of ways to select specific columns that can be used in renaming but it would be better to provide a concrete example, e.g. this is what I have and this is what I want. — Ritchie Sacramento, Feb 06 '22 at 00:09
This is why I have the vector of names listed at the bottom as an example. I will edit my question again to specify what I mean further. — Shawn Hemelstrand, Feb 06 '22 at 00:11
If there's a systematic pattern to how you want to convert old names to new ones you may be able to define a function for that and pass it into `dplyr::rename_with()` as @Ronak Shah demonstrated below. — Dan Adams, Feb 06 '22 at 01:00

score 3 · Answer 1 · answered Feb 06 '22 at 00:02

3

One solution could be this:

library(dplyr)

df %>%
  setNames(paste0("cope_", seq_len(ncol(df))))

  cope_1 cope_2 cope_3 cope_4 cope_5 cope_6 cope_7 cope_8 cope_9 cope_10
1      3      1      2      2      3      3      2      3      3       2
2      3      1      2      2      3      3      2      3      3       2
3      3      1      2      3      4      4      1      4      3       1
4      2      1      1      1      1      3      1      4      2       1
5      4      1      3      1      3      3      3      3      3       1
6      1      1      2      1      3      3      3      3      3       1

answered Feb 06 '22 at 00:02

Anoushiravan R

21,622
3
18
41

1

I just figured out the problem. I changed one part to data1 and forgot to change the end of the code to data1 -_- well that solves that problem haha – Shawn Hemelstrand Feb 06 '22 at 00:28
Ok take your time, if you have any other question just let us know. – Anoushiravan R Feb 06 '22 at 00:29
1

If you have a solution for the other part of the question that would be great. This is already a good answer, but it would be great to hear what solution there is for the rest if you can! – Shawn Hemelstrand Feb 06 '22 at 00:38
1

The second part is just replacing unique column letters with unique names? – Anoushiravan R Feb 06 '22 at 00:44
The idea is naming the columns based off multiple patterns (a1:a10, b1:b10) while also naming individual columns that dont have patterns (c, d, e). I realize that is probably complicated but its something I feel I will encounter in the wild down the road. – Shawn Hemelstrand Feb 06 '22 at 00:45
2

@ShawnHemelstrand I feel like my answer addresses that concern, unless I've misunderstood... – Mikael Jagan Feb 06 '22 at 00:54
1

It does! Thanks for chiming in. – Shawn Hemelstrand Feb 06 '22 at 00:59

score 3 · Answer 2 · answered Feb 06 '22 at 00:35

You may use rename_with in dplyr -

library(dplyr)

df %>% rename_with(~paste0('cope_', seq_along(.)))

#  cope_1 cope_2 cope_3 cope_4 cope_5 cope_6 cope_7 cope_8 cope_9 cope_10
#1      3      1      2      2      3      3      2      3      3       2
#2      3      1      2      2      3      3      2      3      3       2
#3      3      1      2      3      4      4      1      4      3       1
#4      2      1      1      1      1      3      1      4      2       1
#5      4      1      3      1      3      3      3      3      3       1
#6      1      1      2      1      3      3      3      3      3       1

Mikael Jagan · Accepted Answer · 2022-02-06T00:41:08.813

If you have a vector x with the names and a vector r with the number of replications, then you could do:

x <- c("v", "c", "u", "p", "z")
r <- c(3L, 3L, 1L, 1L, 3L)

f <- function(n) if (n > 1L) seq_len(n) else character(n)
paste0(rep(x, r), unlist(lapply(r, f)))
## [1] "v1" "v2" "v3" "c1" "c2" "c3" "u"  "p"  "z1" "z2" "z3"

If you are fine with "u1" and "p1", then you can simplify a bit:

paste0(rep(x, r), unlist(lapply(r, seq_len)))
## [1] "v1" "v2" "v3" "c1" "c2" "c3" "u1" "p1" "z1" "z2" "z3"

There is also base R's make.unique. It is more literate, but it awkwardly only numbers duplicates, so it doesn't quite give you what you want:

make.unique(rep(x, r), sep = "")
## [1] "v"  "v1" "v2" "c"  "c1" "c2" "u"  "p"  "z"  "z1" "z2"

Is there a simpler version of renaming columns with alternating patterns? Or tidyverse methods?

My Data

Solution So Far

Question

3 Answers3