Splitting one column into two columns using data wrangling with R - r

Question

I would really appreciate your help in using R for data wrangling. I have a data where I want to split one column (variable) into two whenever applicable as conditioned by other variables. For example, as per the sample below, the data represents reactions time measures (RT1 and RT2) of some words (item) that appear in different times of reading (block). I want to see if RT1 and RT2 values in block 3, 4, and 5 are correlated with RT1 and RT2 values of the same item at block 1. The target items that appeared in block 1 and re-appeared in subsequent blocks are coded as 'EI' in the column 'condition', whereas items coded as 'E' or 'I' appeared only once.
dput(d1)
structure(list(RECORDING_SESSION_LABEL = c(26, 26, 26, 26, 26,
26, 26, 26), RT1 = c(5171, 3857, 3447, 314, 460, 731, 957, 1253
), RT2 = c(357, 328, 122, 39, 86, 132, 173, 215), item = c("foreign",
"detailed", "large", "foreign", "foreign", "large", "large",
"disputable"), block = c(1, 1, 1, 3, 4, 3, 4, 3), condition = c("EI",
"E", "EI", "EI", "EI", "EI", "EI", "I")), row.names = c(NA, -8L
), class = c("tbl_df", "tbl", "data.frame"))
Where a sample of the data would look like this:
> d1
# A tibble: 8 x 6
RECORDING_SESSION_LABEL RT1 RT2 item block condition
<dbl> <dbl> <dbl> <chr> <dbl> <chr>
1 26 5171 357 foreign 1 EI
2 26 3857 328 detailed 1 E
3 26 3447 122 large 1 EI
4 26 314 39 foreign 3 EI
5 26 460 86 foreign 4 EI
6 26 731 132 large 3 EI
7 26 957 173 large 4 EI
8 26 1253 215 disputable 3 I
In order to present in a format that R would understand, the target data frame I want to achieve would be similar to the one below (where the highlighted columns should be added). Rows in blanks at these columns represent items which do not appear repetitively (condition is not coded as 'EI') ; therefore, they are irrelevant and should be coded as 'NA'.
dput(d2)
structure(list(RECORDING_SESSION_LABEL = c(26, 26, 26, 26, 26,
26, 26, 26), `RT 1` = c(5171, 3857, 3447, 314, 460, 731, 957,
1253), RT2 = c(357, 328, 122, 39, 86, 132, 173, 215), item = c("foreign",
"detailed", "large", "foreign", "foreign", "large", "large",
"disputable"), block = c(1, 1, 1, 3, 4, 3, 4, 3), condition = c("EI",
"E", "EI", "EI", "EI", "EI", "EI", "I"), `RT 1_at_block1` = c(NA,
NA, NA, 5171, 5171, 3447, 3447, NA), RT2_at_block1 = c(NA, NA,
NA, 357, 357, 122, 122, NA)), row.names = c(NA, -8L), class = c("tbl_df",
"tbl", "data.frame"))
And a sample of the data format targeted would look like this:
> d2
# A tibble: 8 x 8
RECORDING_SESSI~ `RT 1` RT2 item block condition `RT 1_at_block1`
<dbl> <dbl> <dbl> <chr> <dbl> <chr> <dbl>
1 26 5171 357 fore~ 1 EI NA
2 26 3857 328 deta~ 1 E NA
3 26 3447 122 large 1 EI NA
4 26 314 39 fore~ 3 EI 5171
5 26 460 86 fore~ 4 EI 5171
6 26 731 132 large 3 EI 3447
7 26 957 173 large 4 EI 3447
8 26 1253 215 disp~ 3 I NA
# ... with 1 more variable: RT2_at_block1 <dbl>
> head(d2)
# A tibble: 6 x 8
RECORDING_SESSION_LABEL `RT 1` RT2 item block condition `RT 1_at_block1` RT2_at_block1
<dbl> <dbl> <dbl> <chr> <dbl> <chr> <dbl> <dbl>
1 26 5171 357 foreign 1 EI NA NA
2 26 3857 328 detailed 1 E NA NA
3 26 3447 122 large 1 EI NA NA
4 26 314 39 foreign 3 EI 5171 357
5 26 460 86 foreign 4 EI 5171 357
6 26 731 132 large 3 EI 3447 122
Thanks in advance for any help.

Answer 1

A possible solution using dplyr:
d1 <- structure(list(RECORDING_SESSION_LABEL = c(26, 26, 26, 26, 26, 26, 26, 26),
RT1 = c(5171, 3857, 3447, 314, 460, 731, 957, 1253),
RT2 = c(357, 328, 122, 39, 86, 132, 173, 215),
item = c("foreign", "detailed", "large", "foreign", "foreign", "large", "large", "disputable"),
block = c(1, 1, 1, 3, 4, 3, 4, 3), condition = c("EI", "E", "EI", "EI", "EI", "EI", "EI", "I")),
row.names = c(NA, -8L), class = c("tbl_df", "tbl", "data.frame"))
library(dplyr)
d2 <- d1 %>%
left_join(d1 %>% filter(block == 1) %>% select(RECORDING_SESSION_LABEL, item, RT1_at_block1 = RT1)) %>%
left_join(d1 %>% filter(block == 1) %>% select(RECORDING_SESSION_LABEL, item, RT2_at_block1 = RT2))
After that, d2 looks like this:
RECORDING_SESSION_LABEL RT1 RT2 item block condition RT1_at_block1 RT2_at_block1
<dbl> <dbl> <dbl> <chr> <dbl> <chr> <dbl> <dbl>
1 26 5171 357 foreign 1 EI 5171 357
2 26 3857 328 detailed 1 E 3857 328
3 26 3447 122 large 1 EI 3447 122
4 26 314 39 foreign 3 EI 5171 357
5 26 460 86 foreign 4 EI 5171 357
6 26 731 132 large 3 EI 3447 122
Edit: Adding a mutate if you want to set the values for block 1 to NA:
d2 <- d1 %>%
left_join(d1 %>% filter(block == 1) %>% select(RECORDING_SESSION_LABEL, item, RT1_at_block1 = RT1)) %>%
left_join(d1 %>% filter(block == 1) %>% select(RECORDING_SESSION_LABEL, item, RT2_at_block1 = RT2)) %>%
mutate(RT1_at_block1 = ifelse(block == 1, NA, RT1_at_block1),
RT2_at_block1 = ifelse(block == 1, NA, RT2_at_block1))