Extracting time information from a raw dataset in R - r

Question

I would like to extract ID, item information and time information from an unstructured dataset. Here is my sample dataset looks like:
df <- data.frame(Text_1 = c("Scoring", "1 = Incorrect","Text1","Text2","Text3","Text4", "Demo 1: Color Naming","Amarillo","Azul","Verde","Azul",
"Demo 1: Errors","Item 1: Color naming","Amarillo","Azul","Verde","Azul",
"Item 1: Time in seconds","Item 1: Errors",
"Item 2: Shape Naming","Cuadrado/Cuadro","Cuadrado/Cuadro","Círculo","Estrella","Círculo","Triángulo",
"Item 2: Time in seconds","Item 2: Errors"),
School.2 = c("Teacher:","DC Name:","Date (mm/dd/yyyy):","Child Grade:","Student Study ID:",NA, NA,NA,NA,NA,NA,
0,"1 = Incorrect responses",0,1,NA,NA,NA,0,"1 = Incorrect responses",0,NA,NA,1,1,0,NA,0),
X_Elementary_School..3 = c("Bill:","X District","10/7/21","K","123-2222-2:",NA, NA,NA,NA,NA,NA,
NA,"Child response",NA,NA,NA,NA,NA,NA,"Child response",NA,NA,NA,NA,NA,NA,NA,NA),
School.4 = c("Teacher:","DC Name:","Date (mm/dd/yyyy):","Child Grade:","Student Study ID:",NA, 0,NA,1,NA,NA,0,"1 = Incorrect responses",0,1,NA,NA,120,0,"1 = Incorrect responses",NA,1,0,1,NA,1,110,0),
Y_Elementary_School..2 = c("John:","X District","11/7/21","K","112-1111-3:",NA, NA,NA,NA,NA,NA,NA,"Child response",NA,NA,NA,NA,NA,NA,"Child response",NA,NA,NA,NA,NA,NA, NA,NA))
> df
Text_1 School.2 X_Elementary_School..3 School.4 Y_Elementary_School..2
1 Scoring Teacher: Bill: Teacher: John:
2 1 = Incorrect DC Name: X District DC Name: X District
3 Text1 Date (mm/dd/yyyy): 10/7/21 Date (mm/dd/yyyy): 11/7/21
4 Text2 Child Grade: K Child Grade: K
5 Text3 Student Study ID: 123-2222-2: Student Study ID: 112-1111-3:
6 Text4 <NA> <NA> <NA> <NA>
7 Demo 1: Color Naming <NA> <NA> 0 <NA>
8 Amarillo <NA> <NA> <NA> <NA>
9 Azul <NA> <NA> 1 <NA>
10 Verde <NA> <NA> <NA> <NA>
11 Azul <NA> <NA> <NA> <NA>
12 Demo 1: Errors 0 <NA> 0 <NA>
13 Item 1: Color naming 1 = Incorrect responses Child response 1 = Incorrect responses Child response
14 Amarillo 0 <NA> 0 <NA>
15 Azul 1 <NA> 1 <NA>
16 Verde <NA> <NA> <NA> <NA>
17 Azul <NA> <NA> <NA> <NA>
18 Item 1: Time in seconds <NA> <NA> 120 <NA>
19 Item 1: Errors 0 <NA> 0 <NA>
20 Item 2: Shape Naming 1 = Incorrect responses Child response 1 = Incorrect responses Child response
21 Cuadrado/Cuadro 0 <NA> <NA> <NA>
22 Cuadrado/Cuadro <NA> <NA> 1 <NA>
23 Círculo <NA> <NA> 0 <NA>
24 Estrella 1 <NA> 1 <NA>
25 Círculo 1 <NA> <NA> <NA>
26 Triángulo 0 <NA> 1 <NA>
27 Item 2: Time in seconds <NA> <NA> 110 <NA>
28 Item 2: Errors 0 <NA> 0 <NA>
Here, When the first column has encounters Item #: Time in seconds, I would like to keep corresponding value under School.2 and School.4 columns. So the first students has those Item 1 and Item 2 time information as empty cell so they are NA. The second student has those time information as 120 and 110. These two students have two items in the example dataset.
There are multiple columns for the real dataset so I need something to be in a generalized loop.
My desired output would be:
> time
id itemid time
1 123-2222-2 Item 1 NA
2 123-2222-2 Item 2 NA
3 112-1111-3 Item 1 120
4 112-1111-3 Item 2 110
This is my attempt but I could not add the id yet.
time.data <- df %>%
filter(str_detect(Text_1, 'Time in seconds')) # %>%
# select(time = 4)
select_time_cols <- seq(from = 2, to = ncol(time.data), by = 2)
time <- time.data %>%
select(time = select_time_cols)
time.t<-as.data.frame(t(time))
rownames(time.t)<-seq(1,nrow(time.t),1)
colnames(time.t)<-paste0('i',seq(1,ncol(time.t),1))
time.t<-apply(time.t,2,as.numeric)
time.t<-as.data.frame(time.t)
> time.t
item1 item2
1 NA NA
2 120 110

Answer 1

I came up with a solution with your test dataset, though this isn't particularly robust or elegant, so there will likely be better options out there. The key thing I did was shift the text3 row over, so that the id and time were in the same column. I put notes in the code to illuminate my steps. Hopefully this points you in the right direction or prompts those with better coding skills than my own!
library(dplyr)
library(tidyr)
df2<-df%>% #Turning all to character, so that I can move the row without interfering with factor level
mutate_all(as.character)
df2[5, 2:(ncol(df2) - 1)] <- df2[5, 3:ncol(df2)] #shifting row 5, which is the "Text3" that has studentID to be the same column as the times
df3<-df2%>%
filter(grepl("Text3|Time in seconds", Text_1))%>% #removing unnecessary rows
mutate(type = case_when(grepl("Text", Text_1) ~ "itemid", #Relabling the Text_1 column
grepl("Item 1", Text_1) ~ "1",
grepl("Item 2", Text_1) ~ "2"))%>%
select(grep("type|^School", names(.))) #only keeping needed columns
colnames(df3) <- df3[1,] #Taking the first row and making it the column names
df3 <- df3[-1, ] #removing row 1, since it was made into column names
df3%>%
tidyr::pivot_longer(-itemid, names_to = "id", values_to = "time")%>% #Making the data into longer format
select(id, itemid, time)%>% #relocating columns to match desired output
arrange(desc(id)) #sorting to match desired output