I need your kind tidying data frame. A sample of data is provided below:
> dput(data_1)
structure(list(subject = c("E1", "E1", "E1", "E1", "E1", "E1",
"E1", "E1"), block = c(3, 3, 4, 4, 5, 5, 6, 6), condition = c("EI",
"I", "EI", "I", "EI", "I", "EI", "I"), prev_total_RT = c("963",
"NA", "963", "NA", "963", "NA", "963", "NA"), total_RT = c(271,
1042, 409, 406, 544, 490, 645, 465), Item_number = c(17, 46,
17, 46, 17, 46, 17, 46)), row.names = c(NA, -8L), class = c("tbl_df",
"tbl", "data.frame"))
> data_1
# A tibble: 8 x 6
subject block condition prev_total_RT total_RT Item_number
<chr> <dbl> <chr> <chr> <dbl> <dbl>
1 E1 3 EI 963 271 17
2 E1 3 I NA 1042 46
3 E1 4 EI 963 409 17
4 E1 4 I NA 406 46
5 E1 5 EI 963 544 17
6 E1 5 I NA 490 46
7 E1 6 EI 963 645 17
8 E1 6 I NA 465 46
While values of "prev_total_RT" for the condition "EI" are provided, it is not provided for the condition "I". I need a code that would generate the values of "prev_total_RT" for the condition "I".
The values of "prev_total_RT" for the condition "I" should be the sum of "total_RT" for condition "I" in "block" = 3, 4, and 5. This should be conditioned by each "subject" and "Item_number". For example, for the subject "E1" and Item_number "46" in condition "I", the value of "prev_total_RT" should be the sum of "total_RT" values in "block" 3, 4, 5 : 1042 + 406 + 490 = 1938.
The desired output is provided below:
> dput(data_2)
structure(list(subject = c("E1", "E1", "E1", "E1", "E1", "E1",
"E1", "E1"), block = c(3, 3, 4, 4, 5, 5, 6, 6), condition = c("EI",
"I", "EI", "I", "EI", "I", "EI", "I"), prev_total_RT = c(963,
1938, 963, 1938, 963, 1938, 963, 1938), total_RT = c(271, 1042,
409, 406, 544, 490, 645, 465), Item_number = c(17, 46, 17, 46,
17, 46, 17, 46)), row.names = c(NA, -8L), class = c("tbl_df",
"tbl", "data.frame"))
> data_2
# A tibble: 8 x 6
subject block condition prev_total_RT total_RT Item_number
<chr> <dbl> <chr> <dbl> <dbl> <dbl>
1 E1 3 EI 963 271 17
2 E1 3 I 1938 1042 46
3 E1 4 EI 963 409 17
4 E1 4 I 1938 406 46
5 E1 5 EI 963 544 17
6 E1 5 I 1938 490 46
7 E1 6 EI 963 645 17
8 E1 6 I 1938 465 46
Any help with this would be greatly appreciated.
>Solution :
A straight forward method,
library(dplyr)
df %>%
group_by(subject, Item_number) %>%
mutate(prev_total_RT = replace(prev_total_RT, condition == 'I', sum(total_RT[block %in% c(3, 4, 5)])))
# subject block condition prev_total_RT total_RT Item_number
# <chr> <dbl> <chr> <chr> <dbl> <dbl>
#1 E1 3 EI 963 271 17
#2 E1 3 I 1938 1042 46
#3 E1 4 EI 963 409 17
#4 E1 4 I 1938 406 46
#5 E1 5 EI 963 544 17
#6 E1 5 I 1938 490 46
#7 E1 6 EI 963 645 17
#8 E1 6 I 1938 465 46