frequency of a time series with NA (R software) - r

Question

I would like to work with time series in R, but I am stuck at the beginning cause I have a problem with the frequency. I have monthly data for 30 years (start date = 1988, end date = 2018), but with holes sometimes: I have months or years with no data.
I would prefer not to interpolate or mediate in order to fill the hole, but just omit the empty month/year using na.omit. The problem is that I am going to have some years with 12 months and others with less months.
My question is..How could I determine and work with my frequency now?
Here an example of two years:
YEAR MONTH Temp Salt
1988 1 NA NA
1988 2 NA NA
1988 3 NA NA
1988 4 NA NA
1988 5 NA NA
1988 6 NA NA
1988 7 16.45388889 37.4064537
1988 8 17.48898148 37.89002778
1988 9 NA NA
1988 10 NA NA
1988 11 15.8050463 38.08833333
1988 12 NA NA
1989 1 NA NA
1989 2 10.74912037 38.2787037
1989 3 NA NA
1989 4 NA NA
1989 5 NA NA
1989 6 14.52092593 37.71060185
1989 7 16.84342593 37.32300926
1989 8 17.97930556 37.82277778
1989 9 NA NA
1989 10 NA NA
1989 11 16.23837963 38.00009259
1989 12 13.6325463 37.97509259
Any advice would be useful!
Thank you very much!

Answer 1

The zooreg class in the zoo package is intended for this type of situation where you have an underlying regularity but some values may not be present.
Assuming the input in the Note at the end this produces a zooreg series with frequency 12. This is a time series that has frequency 12 but without all values. Replace text = Lines with your filename, e.g. "myfile.dat" to read it in from a file. Note that the yearmon class stores the time as a year plus 0 for January, 1/12 for Feb, 2/12 for March, etc.
library(zoo)
to_ym <- function(y, m) as.yearmon(paste(y, m, sep = "-"))
z <- read.zoo(text = Lines, header = TRUE, index = 1:2, FUN = to_ym, regular = TRUE)
z <- na.omit(z)
frequency(z)
## [1] 12
The question is not clear on exactly what you have (a file? a data frame?) but if what you have is a data.frame DF read it in from that. to_ym is from above.
DF <- read.table(text = Lines, header = TRUE)
z <- read.zoo(DF, index = 1:2, FUN = to_ym, regular = TRUE)
z <- na.omit(z)
To restore the NA's just convert it to a ts series:
z_na <- as.zooreg(as.ts(z))
Also, if you do decide to fill in the NAs then there are several routines available including na.spline, na.approx, na.StructTS (Kalman filter) and na.locf.
We can now work with z like like this:
as.integer(time(z)) # year
cycle(time(z)) # month (1 = Jan, 2 = Feb, ...)
start(z) # starting time of series
end(z) # ending time of series
plot(z)
plot(scale(z), screen = 1, col = 1:2)
legend("bottomleft", leg = names(z), col = 1:2, lty = 1)
library(ggplot2)
autoplot(z)
autoplot(z) + facet_free()
autoplot(z, facet = NULL)
autoplot(scale(z), facet = NULL)
Note
Lines <- "
YEAR MONTH Temp Salt
1988 1 NA NA
1988 2 NA NA
1988 3 NA NA
1988 4 NA NA
1988 5 NA NA
1988 6 NA NA
1988 7 16.45388889 37.4064537
1988 8 17.48898148 37.89002778
1988 9 NA NA
1988 10 NA NA
1988 11 15.8050463 38.08833333
1988 12 NA NA
1989 1 NA NA
1989 2 10.74912037 38.2787037
1989 3 NA NA
1989 4 NA NA
1989 5 NA NA
1989 6 14.52092593 37.71060185
1989 7 16.84342593 37.32300926
1989 8 17.97930556 37.82277778
1989 9 NA NA
1989 10 NA NA
1989 11 16.23837963 38.00009259
1989 12 13.6325463 37.97509259"