I have a dataframe like this:
df <- setNames(data.frame(matrix(c(rep(1,8),c(1,2,3,1,2,3,4,1),
rep("useless",3),"label1",
rep("useless",3),"label2",
floor(runif(8,100,400))),8,4)),
c("subject","trial","block","data"))
subject trial block data
1 1 1 useless 144
2 1 2 useless 380
3 1 3 useless 118
4 1 1 label1 323
5 1 2 useless 250
6 1 3 useless 292
7 1 4 useless 375
8 1 1 label2 358
I would like to make all of the "useless" rows into the "label" rows that come after them.
Output:
subject trial block data
1 1 1 label1 144
2 1 2 label1 380
3 1 3 label1 118
4 1 1 label1 323
5 1 2 label2 250
6 1 3 label2 292
7 1 4 label2 375
8 1 1 label2 358
I was thinking along these lines, but don't know how to do it:
df %>%
mutate(block = ifelse(block == "useless", "make it the end label", block))
I know there must be a very simple solution, but I'm not seeing it. I would prefer an answer from the tidyverse, but will accept anything that works.
Replace useless value with NA, then do a backward fill:
library(tidyverse)
df %>%
mutate(block = ifelse(grepl('label', block), as.character(block), NA)) %>%
fill(block, .direction = 'up')
# subject trial block data
#1 1 1 label1 108
#2 1 2 label1 391
#3 1 3 label1 201
#4 1 1 label1 239
#5 1 2 label2 332
#6 1 3 label2 239
#7 1 4 label2 363
#8 1 1 label2 267
Or use na_if, if you have only one useless value:
library(tidyverse)
df %>%
mutate(block = na_if(block, 'useless')) %>%
fill(block, .direction = 'up')
# subject trial block data
#1 1 1 label1 108
#2 1 2 label1 391
#3 1 3 label1 201
#4 1 1 label1 239
#5 1 2 label2 332
#6 1 3 label2 239
#7 1 4 label2 363
#8 1 1 label2 267