R时间序列-识别缺失的观测值（时间戳）并插入NA以创建给定长度的时间序列

Question

I have a set of 24 grouped (hierarchical) time series supposedly running over 3 years, and I want to look at monthly sales, but it turns out that a number of them have missing observations, eg

getCounts(Shop1, ...)
2011-01 2011-02 2011-03 2011-04 2011-05 2011-06 2011-07 2011-08 2011-09 2011-10 2011-11 2011-12 2012-02 2012-03 2012-04 2012-05 2012-06 2012-07 2012-08 2012-09 2012-10 2012-11 
 10      22      10      12      36      31      25      19       7       7       7       5       1       9       9      11      10      16      25       3       2       5 

is missing an observation for January 2012 and ends in November 2012 although it's supposed to run to December 2013.

getCounts uses the command

with(myDF, tapply(varName, substr(dateName, 1, 7), sum))

to get the monthly counts.

I want to replace the missing observations, both in the middle of the time series and at the end, with NAs, so that all my time series have the same number of observations and, if there are any "holes" they will be visible in a plot.

Can anybody help me do this?

Thanks!

Edit: My preferred output would be something like this:

      Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2011   1  NA   2   3   4   5   6  NA   7   8   9  10
2012   2   3   4   5   6  NA  NA  NA  NA  NA  NA  NA

where each NA is replacing a missing observation.

Edit 2: getCounts() look like this:

getCounts <- function(dataObject, dateName, varName){ 
dataNameString <- deparse(substitute(dataObject))   
countsStr <- paste0("with(", dataNameString,", tapply(", varName, ", substr(", dateName, ", 1, 7), sum))")
counts <- eval(parse(text = countsStr))
return(counts)
}

And here's the dput:

structure(c(10, 22, 10, 12, 36, 31, 25, 19, 7, 7, 7, 5, 1, 9, 
9, 11, 10, 16, 25, 3, 2, 5), .Dim = 22L, .Dimnames = list(c("2011-01", 
"2011-02", "2011-03", "2011-04", "2011-05", "2011-06", "2011-07", 
"2011-08", "2011-09", "2011-10", "2011-11", "2011-12", "2012-02", 
"2012-03", "2012-04", "2012-05", "2012-06", "2012-07", "2012-08", 
"2012-09", "2012-10", "2012-11")))

Answer 1

Try this

df <- data.frame(Year = substr(names(x), 1, 4),
                 Month = factor(month.abb[as.numeric(substr(names(x), 6, 7))], 
                         levels = month.abb),
                 Value = x)

library(tidyr)
spread(df, Month, Value)
#   Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
# 1 2011  10  22  10  12  36  31  25  19   7   7   7   5
# 2 2012  NA   1   9   9  11  10  16  25   3   2   5  NA

---

Data

x <- structure(c(10, 22, 10, 12, 36, 31, 25, 19, 7, 7, 7, 5, 1, 9, 
                 9, 11, 10, 16, 25, 3, 2, 5), .Dim = 22L, .Dimnames = list(c("2011-01", 
                 "2011-02", "2011-03", "2011-04", "2011-05", "2011-06", "2011-07", 
                 "2011-08", "2011-09", "2011-10", "2011-11", "2011-12", "2012-02", 
                 "2012-03", "2012-04", "2012-05", "2012-06", "2012-07", "2012-08", 
                 "2012-09", "2012-10", "2012-11")))