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I have the following data frame:

enter image description here

I have multiple participants listed in subj_id (you can see only 2 here). I want to change all Pre items in the trial column to Pre1, Pre2, Pre3, Pre4.

How can I do this?

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    what of Test? Do you also want to change it to Test1 Test2 ...? Also note that one cannot replicate your work since you provided an image rather than plain text data Commented Aug 27, 2021 at 16:49
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    For context, images of code or data breaks screen readers (there are visually-impaired users who also need help) and breaks search-engine optimization; see meta.stackoverflow.com/a/285557 (and xkcd.com/2116). Please read from stackoverflow.com/q/5963269, minimal reproducible example, and stackoverflow.com/tags/r/info for some great suggestions on how to make the question more reproducible, starting with sample data (dput(x)) and code you've attempted. Thanks! Commented Aug 27, 2021 at 16:58
  • @r2evans thanks so much! I wasn't aware of this. I'll certainly check out these websites. Commented Aug 27, 2021 at 17:08

1 Answer 1

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base R

dat <- data.frame( subj_id = c(rep(1L, 7), rep(2L, 7)), trial = c(rep("Pre", 4), rep("Test", 3), rep("Pre", 4), rep("Test", 3)), judgment = 1:14 ) dat # subj_id trial judgment # 1 1 Pre 1 # 2 1 Pre 2 # 3 1 Pre 3 # 4 1 Pre 4 # 5 1 Test 5 # 6 1 Test 6 # 7 1 Test 7 # 8 2 Pre 8 # 9 2 Pre 9 # 10 2 Pre 10 # 11 2 Pre 11 # 12 2 Test 12 # 13 2 Test 13 # 14 2 Test 14 ave(seq_len(nrow(dat)), dat[,c("subj_id", "trial")], FUN = seq_along) # [1] 1 2 3 4 1 2 3 1 2 3 4 1 2 3 dat$trial <- paste0(dat$trial, ave(seq_len(nrow(dat)), dat[,c("subj_id", "trial")], FUN = seq_along)) dat # subj_id trial judgment # 1 1 Pre1 1 # 2 1 Pre2 2 # 3 1 Pre3 3 # 4 1 Pre4 4 # 5 1 Test1 5 # 6 1 Test2 6 # 7 1 Test3 7 # 8 2 Pre1 8 # 9 2 Pre2 9 # 10 2 Pre3 10 # 11 2 Pre4 11 # 12 2 Test1 12 # 13 2 Test2 13 # 14 2 Test3 14

If you only need "Pre" numbered, then alter that code above to be

dat$trial <- ifelse(dat$trial == "Pre", paste0(dat$trial, ave(seq_len(nrow(dat)), dat[,c("subj_id", "trial")], FUN = seq_along)), dat$trial) dat # subj_id trial judgment # 1 1 Pre1 1 # 2 1 Pre2 2 # 3 1 Pre3 3 # 4 1 Pre4 4 # 5 1 Test 5 # 6 1 Test 6 # 7 1 Test 7 # 8 2 Pre1 8 # 9 2 Pre2 9 # 10 2 Pre3 10 # 11 2 Pre4 11 # 12 2 Test 12 # 13 2 Test 13 # 14 2 Test 14

dplyr

library(dplyr) dat %>% group_by(subj_id, trial) %>% mutate(trial = paste0(trial, row_number())) %>% ungroup() # # A tibble: 14 x 3 # subj_id trial judgment # <int> <chr> <int> # 1 1 Pre1 1 # 2 1 Pre2 2 # 3 1 Pre3 3 # 4 1 Pre4 4 # 5 1 Test1 5 # 6 1 Test2 6 # 7 1 Test3 7 # 8 2 Pre1 8 # 9 2 Pre2 9 # 10 2 Pre3 10 # 11 2 Pre4 11 # 12 2 Test1 12 # 13 2 Test2 13 # 14 2 Test3 14

Similarly, if only "Pre", then

dat %>% group_by(subj_id, trial) %>% mutate(trial = if_else(trial == "Pre", paste0(trial, row_number()), trial)) %>% ungroup()
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3 Comments

Thank you so much! This is great. I just have two follow-up questions. (1) How can I only select only PRE trials (so not changing Test trials)? (2) is there a way to do this without depending on the subj_id?
See my edit. I had assumed that that was not a factor since you never answered @Onyambu's comment. (This is one reason why the "reproducible question" links tend to suggest including expected output.)
This is great help! Thanks! I'm now reading about the reproducible questions. Thank you so much for guiding me so much!

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