r - Counting dates that don't exist -


i working on data frame contains 2 columns follows:

    time        frequency   2014-01-06       13   2014-01-07       30   2014-01-09       56

my issue interested in counting days of frequency 0. data pulled using rpostgresql/rsqlite there no datetime given unless there value (i.e. unless frequency @ least 1). if interested in counting these dates don't exist in data frame, there easy way go doing it? i.e. if consider date range 2014-01-01 20-14-01-10, want count 7

my thought brute force create separate dataframe every date (note 4+ years of dates immense undertaking) , merging 2 dataframes , counting number of na values. i'm sure there more elegant solution i've thought of.

thanks!

sort date , gaps.

start <- as.date("2014-01-01") time <- as.date(c("2014-01-06", "2014-01-07","2014-01-09")) end <- as.date("2014-01-10")  time <- sort(unique(time))  # include start , end dates, missing dates 1/1-1/5, 1/8, 1/10 d <- c(time[1]- start,        diff(time) - 1,        end - time[length(time)] )  d # [1] 5 0 1 1 sum(d) # 7 missing days

and days missing...

(gaps <- data.frame(gap_starts = c(start,time+1)[d>0],                     gap_length = d[d>0])) #   gap_starts gap_length # 1 2014-01-01          5 # 2 2014-01-08          1 # 3 2014-01-10          1      (g in 1:nrow(gaps)){   start=gaps$gap_starts[g]   length=gaps$gap_length[g]   for(i in start:(start+length-1)){     print(as.date(i, origin="1970-01-01"))   } } # [1] "2014-01-01" # [1] "2014-01-02" # [1] "2014-01-03" # [1] "2014-01-04" # [1] "2014-01-05" # [1] "2014-01-08" # [1] "2014-01-10"

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