R Issue adding NA values for missing rows using data frames - r

Question

Thanks in advance for any help that is provided.
Long story short: I am working with hourly time series data from a measurement device (exported from SQL then imported in to R in order to properly format the date time ) - the time series contains missing data, sometimes in groups, and I need to locate these missing rows/indices and insert a new row for each instance that holds an NA value.
Related Questions that did not solve my problem:
how to insert missing observations on a data frame
Adding row to a data frame with missing values
Problem Data
The dataset that I am working with in this case is fairly large and varies depending on the measurement device I select. As a test case, I have one time series that contains 17469 hourly observations. I located a small section of the dataset that may be used for testing purposes. Here it is:
> snip
date Reading
408 2015-12-15 00:00:00 4.40
409 2015-12-14 23:00:00 4.62
410 2015-12-14 22:00:00 4.61
411 2015-12-14 21:00:00 6.15
412 2015-12-14 20:00:00 6.06
413 2015-12-14 19:00:00 7.04
414 2015-12-14 18:00:00 8.57
415 2015-12-14 11:00:00 4.12
416 2015-12-14 10:00:00 3.73
We can see that observations are missing for 2015-12-14 12:00:00 to 2015-12-14 17:00:00. I would like to first locate then populate the time series with these date times and input NA for the Reading column in these positions. I would also like to return the indices that are missing in an additional vector.
How can this be done?
So far I have tried the following code (as suggested here, how to add a missing dates and remove repeated dates in hourly time series), but all I end up with is NA values when I perform the merge function and still need to identify where the missing indices are located.
Here is the result:
> grid = data.frame(date=seq.POSIXt(min(snip[,1]), to=max(snip[,1]), by="1 hours"));
> dat = merge(grid, snip, by="date", all.x=TRUE)
> dat
date Reading
1 2015-12-14 10:00:00 NA
2 2015-12-14 11:00:00 NA
3 2015-12-14 12:00:00 NA
4 2015-12-14 13:00:00 NA
5 2015-12-14 14:00:00 NA
6 2015-12-14 15:00:00 NA
7 2015-12-14 16:00:00 NA
8 2015-12-14 17:00:00 NA
9 2015-12-14 18:00:00 NA
10 2015-12-14 19:00:00 NA
11 2015-12-14 20:00:00 NA
12 2015-12-14 21:00:00 NA
13 2015-12-14 22:00:00 NA
14 2015-12-14 23:00:00 NA
15 2015-12-15 00:00:00 NA
What am I missing here? Is it because grid and snip$date are in reverse order? For additional information here is what the date time format looks like (in case this is from where my issue stems):
> snip[2,1]
[1] "2015-12-14 23:00:00 GMT"
The result of the dput(snip) command is as follows (thanks for the suggestion #42):
> dput(snip)
structure(list(date = structure(list(sec = c(0, 0, 0, 0, 0, 0,
0, 0, 0), min = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), hour = c(0L,
23L, 22L, 21L, 20L, 19L, 18L, 11L, 10L), mday = c(15L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L), mon = c(11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L), year = c(115L, 115L, 115L, 115L, 115L, 115L,
115L, 115L, 115L), wday = c(2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), yday = c(348L, 347L, 347L, 347L, 347L, 347L, 347L, 347L, 347L
), isdst = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("sec",
"min", "hour", "mday", "mon", "year", "wday", "yday", "isdst"
), class = c("POSIXlt", "POSIXt"), tzone = "GMT"), Reading = c(4.4,
4.62, 4.61, 6.15, 6.06, 7.04, 8.57, 4.12, 3.73)), .Names = c("date",
"Reading"), row.names = 408:416, class = "data.frame")

Answer 1

Here's how I was able to do it with some help from na.locf documentation. Does it help?
dat<- dget("yoursample")
require(xts)
datxts<- as.xts(dat[,-1],order.by = dat$date,frequency = 24)
tzn<-tzone(datxts)
g<- seq(start(datxts), end(datxts), "hour")
gxts<- xts(rep(NA,length(g)),order.by = as.POSIXct(g), tzone = tzn)
merge(datxts,gxts,all = T)$datxts
Edit: And also, your method works if you add a column of NA's to generated dataframe
dates=seq.POSIXt(min(snip[,1]), to=max(snip[,1]), by="1 hours")
grid = data.frame(date=dates,dummydata=rep(NA,length(dates)));
dat = merge(grid, snip, by="date", all=T)