loop for list element with datetime in r - r

Question

loop for list element with datetime in r
I have a df with name mistake. I splitted the mistake df by ID. Now I have over 300 different objects in the list.
library(dplyr)
df <- split.data.frame(mistake, mistake$ID)
Every list object has two different datetime stamps. At first I need the minutes between this two datetime stamps. Then I duplicate the rows of the object by the variable stay (this is the difftime between the sat and end time too). Then I overwrite the test variable with the increment n_mintes.
library(lubridate)
start_date <- df[[1]]$datetime
end_date <- df[[1]]$gehtzeit
n_minutes <- interval(start_date,end_date)/minutes(1)
see <- start_date + minutes(0:n_minutes)#the diff time in minutes I need
df[[1]]$test<- Sys.time()#a new variable
df[[1]] <- data.frame(df[[1]][rep(seq_len(dim(df[[1]])[1]),df[[1]]$stay+1),1:17, drop= F], row.names=NULL)
df[[1]]$test <- format(start_date + minutes(0:n_minutes), format = "%d.%m.%Y %H:%M:%S")
I want to do this with every objcet of the list. And then 'rbind' or 'unsplit' my list. I know I need a loop. But I don' t know how to do this with the list element.
Any help would be create!
Here is a small df example;
mistake
Baureihe Verbund Fahrzeug Code Codetext Subsystem Kommt.Zeit
71 411 ICE1166 93805411866-7 1A50 Querfederdruck 1 ungleich Sollwert Neigetechnik 29.07.2018 23:00:07
72 411 ICE1166 93805411866-7 1A50 Querfederdruck 1 ungleich Sollwert Neigetechnik 04.08.2018 11:16:41
Geht.Zeit Anstehdauer Jahr Monat KW Tag Wartung.geht datetime gehtzeit
71 29.07.2018 23:02:56 00 Std 02 Min 49 Sek 2018 7 KW30 29 0 2018-07-29 23:00:00 2018-07-29 23:02:00
72 04.08.2018 11:19:20 00 Std 02 Min 39 Sek 2018 8 KW31 4 0 2018-08-04 11:16:00 2018-08-04 11:19:00
bleiben ID
71 2 secs 2018-07-29 23:00:00 2018-07-29 23:02:00 1A50
72 3 secs 2018-08-04 11:16:00 2018-08-04 11:19:00 1A50
And here ist the structure:
str(mistake)
'data.frame': 2 obs. of 18 variables:
$ Baureihe : int 411 411
$ Verbund : Factor w/ 1 level "ICE1166": 1 1
$ Fahrzeug : Factor w/ 7 levels "93805411066-4",..: 7 7
$ Code : Factor w/ 6 levels "1A07","1A0E",..: 3 3
$ Codetext : Factor w/ 6 levels "ITD Karte gestört",..: 5 5
$ Subsystem : Factor w/ 1 level "Neigetechnik": 1 1
$ Kommt.Zeit : Factor w/ 70 levels "02.08.2018 00:07:23",..: 68 6
$ Geht.Zeit : Factor w/ 68 levels "01.08.2018 01:30:25",..: 68 8
$ Anstehdauer : Factor w/ 46 levels "00 Std 00 Min 01 Sek ",..: 12 4
$ Jahr : int 2018 2018
$ Monat : int 7 8
$ KW : Factor w/ 5 levels "KW27","KW28",..: 4 5
$ Tag : int 29 4
$ Wartung.geht: int 0 0
$ datetime : POSIXlt, format: "2018-07-29 23:00:00" "2018-08-04 11:16:00"
$ gehtzeit : POSIXlt, format: "2018-07-29 23:02:00" "2018-08-04 11:19:00"
$ bleiben :Class 'difftime' atomic [1:2] 2 3
.. ..- attr(*, "units")= chr "secs"
$ ID : chr "2018-07-29 23:00:00 2018-07-29 23:02:00 1A50" "2018-08-04 11:16:00 2018-08-04 11:19:00 1A50"

Answer 1

Consider building a generalized user-defined function that receives a data frame as input parameter. Then, call the function with by. Like split, by also subsets a data frame by one or more factor(s) such as ID but, unlike split, by can then pass subsets into a function. To row bind all together, run do.call at end.
Below removes the redundant df$test <- Sys.time() which is overwritten later and uses see object inside format() call at end to avoid re-calculation and repetition.
calc_datetime <- function(df) {
# INITIAL CALCS
start_date <- df$datetime
end_date <- df$gehtzeit
n_minutes <- interval(start_date, end_date)/minutes(1)
see <- start_date + minutes(0:n_minutes) # the diff time in minutes I need
# BUILD OUTPUT DF
df <- data.frame(df[rep(seq_len(dim(df)[1]), df$stay+1), 1:17, drop= F], row.names=NULL)
df$test <- format(see, format = "%d.%m.%Y %H:%M:%S")
return(df)
}
# BUILD LIST OF SUBSETTED DFs
df_list <- by(mistake, mistake$ID, calc_datetime)
# APPEND ALL RESULT DFs TO SINGLE FINAL DF
final_df <- do.call(rbind, df_list)

Answer 2

Along the same lines as Parfait's answer, and using the same user defined function calc_datetime, but I would use map_dfr from the purrr package:
df_list <- split(mistake, mistake$ID)
final_df <- map_dfr(df_list, calc_datetime)
If you update the question to have data I can use I can give a demonstration that works