Filling not observed observations - r

Question

I want to make a time series with the frequency a date and time is observed. The raw data looked something like this:
dd-mm-yyyy hh:mm
28-2-2018 0:12
28-2-2018 11:16
28-2-2018 12:12
28-2-2018 13:22
28-2-2018 14:23
28-2-2018 14:14
28-2-2018 16:24
The date and time format is in the wrong way for R, so I had to adjust it:
extracted_times <- as.POSIXct(bedrijf.CSV$viewed_at, format = "%d-%m-%Y %H:%M")
I ordered the data with frequency in a table using the following code:
timeserieswithoutzeros <- table(extracted_times)
The data looks something like this now:
2018-02-28 00:11:00 2018-02-28 01:52:00 2018-02-28 03:38:00
1 2 5
2018-02-28 04:10:00 2018-02-28 04:40:00 2018-02-28 04:45:00
2 1 1
As you may see there are a lot of unobserved dates and times.
I want to add these unobserved dates and times with the frequency of 0.
I tried the complete function, but the error states that it can't best used, because I use as.POSIXct().
Any ideas?

Answer 1

As already mentinoned in the comments by #eric-lecoutre, you can combine your observations with a sequence begining at the earliest ending at the last date using seq and subtract 1 of the frequency table.
timeseriesWithzeros <- table(c(extracted_times, seq(min(extracted_times), max(extracted_times), "1 min")))-1

Answer 2

Maybe the following is what you want.
First, coerce the data to class "POSIXt" and create the sequence of all date/time between min and max by steps of 1 minute.
bedrijf.CSV$viewed_at <- as.POSIXct(bedrijf.CSV$viewed_at, format = "%d-%m-%Y %H:%M")
new <- seq(min(bedrijf.CSV$viewed_at),
max(bedrijf.CSV$viewed_at),
by = "1 mins")
tmp <- data.frame(viewed_at = new)
Now see if these values are in the original data.
tmp$viewed <- tmp$viewed_at %in% bedrijf.CSV$viewed_at
tbl <- xtabs(viewed ~ viewed_at, tmp)
sum(tbl != 0)
#[1] 7
Final clean up.
rm(new, tmp)