How to create “NA” for missing data in a time series

Question

I have several files of data that look like this:

X code year month day pp  
1 4515 1953     6   1  0  
2 4515 1953     6   2  0  
3 4515 1953     6   3  0  
4         


        

Answer 1

The first thing to note is that z.date is character, not Date.

Here's how I would solve your problem using xts (a subclass of zoo).

# remove the third obs from sample data
CET <- CET[-3,]
# create an actual Date column in CET
CET$date <- as.Date(with(CET, paste(year, month, day, sep="-")))
# create an xts object using 'date' column
x <- xts(CET[,c("code","pp")], CET$date)
# now merge 'x' with a regular date sequence spanning the start/end of 'x'
X <- merge(x, timeBasedSeq(paste(start(x), end(x), sep="::")))
X
#            code  pp
# 1953-06-01 4515 0.0
# 1953-06-02 4515 0.0
# 1953-06-03   NA  NA
# 1953-06-04 4515 0.0
# 1953-06-05 4515 3.5