I'm new and can't figure it out how to solve this problem. I have a data.frame = schedule
| Week_number | Start | End |
|---|---|---|
| 1 | 09:00 | 15:00 |
| 1 | 09:00 | 15:00 |
| 1 | 09:00 | 15:00 |
| 1 | 09:00 | 15:00 |
| 1 | 09:00 | 15:00 |
| 1 | NA | NA |
| 1 | NA | NA |
| 2 | 09:00 | 15:00 |
| 2 | 09:00 | 15:00 |
| 2 | 09:00 | 15:00 |
| 2 | 09:00 | 15:00 |
| 2 | 09:00 | 15:00 |
| 2 | NA | NA |
| 2 | NA | NA |
| 3 | 09:00 | 15:00 |
| 3 | 09:00 | 15:00 |
| 3 | 09:00 | 15:00 |
| 3 | 09:00 | 15:00 |
| 3 | 09:00 | 15:00 |
| 3 | NA | NA |
| 3 | NA | NA |
| ----------------------------- | ||
| .. | ||
| 52 | ||
| ----------------------------- |
I have a shift dictionary :
> start_vec <- c("06:00", "08:00", "14:00")
> end_vec <- c("14:00", "16:00", "22:00")
My loop is to go through all 52 weeks and replace 9am and 3pm with a dictionary value. But the problem is that the values should not be repeated, i.e. each week should be different.
For example, I start the year with : 08:00 - 16:00. The year can start with any shift. Please find an example below :
| Week_number | Start | End |
|---|---|---|
| 1 | 08:00 | 16:00 |
| 1 | 08:00 | 16:00 |
| 1 | 08:00 | 16:00 |
| 1 | 08:00 | 16:00 |
| 1 | 08:00 | 16:00 |
| 1 | NA | NA |
| 1 | NA | NA |
| 2 | 14:00 | 22:00 |
| 2 | 14:00 | 22:00 |
| 2 | 14:00 | 22:00 |
| 2 | 14:00 | 22:00 |
| 2 | 14:00 | 22:00 |
| 2 | NA | NA |
| 2 | NA | NA |
| 3 | 06:00 | 14:00 |
| 3 | 06:00 | 14:00 |
| 3 | 06:00 | 14:00 |
| 3 | 06:00 | 14:00 |
| 3 | 06:00 | 14:00 |
| 3 | NA | NA |
| 3 | NA | NA |
| ----------------------------- | ||
| .. | ||
| 52 | ||
| ----------------------------- |
I tryed to make nest loop, or make week_number vector to be able replace all 1 without NA with specific value.
> rd_dt <- data.frame()
> for (i in 1:length(schedule$Week_number)){
> for (s in start_vec){
> for (e in end_vec){
> dt <- schedule[i,]
> if (schedule$Start == NA){
> next
> else {
Thanks in advance for any hint.
I think you do not need a loop to do this. Here is one approach that may be helpful. Using ifelse check for NA - if not NA, then refer to start_vec and end_vec for substitute values. It will use the Week_number as an index in your vector, and uses the %% modulus operator where 3 is the length of your vectors, so it will restart at beginning if exceeds the length of the vectors.
library(dplyr)
df %>%
mutate(Start = ifelse(is.na(Start), NA, start_vec[1 + Week_number %% 3]),
End = ifelse(is.na(End), NA, end_vec[1 + Week_number %% 3]))
Output
Week_number Start End
1 1 08:00 16:00
2 1 08:00 16:00
3 1 08:00 16:00
4 1 08:00 16:00
5 1 08:00 16:00
6 1 <NA> <NA>
7 1 <NA> <NA>
8 2 14:00 22:00
9 2 14:00 22:00
10 2 14:00 22:00
11 2 14:00 22:00
12 2 14:00 22:00
13 2 <NA> <NA>
14 2 <NA> <NA>
15 3 06:00 14:00
16 3 06:00 14:00
17 3 06:00 14:00
18 3 06:00 14:00
19 3 06:00 14:00
20 3 <NA> <NA>
21 3 <NA> <NA>