On Nov 20, 2009, at 8:04 AM, David Winsemius wrote:


On Nov 20, 2009, at 6:26 AM, Stefan Strohmeier wrote:

Dear R users,

I have a time series of precipitation data. The time series comprises ~ 20 years and it is supposed to be constant (one value per day), but due to some failure of the measuring device some days or periods are missing. I would like to find these missing days or periods just to get a first idea about the reliability of the measurements. The only function I could find was is.constant(), but of course I only get a true or false statement instead of the dates missing. Google searches and a look at the R help mailing did not reveal an answer.

Please find attached a few dates of the time series with missing values from February to April. I would like R to detect those missing dates.

> dtdta <- read.table(textConnection("2916 2002-02-17  0.0
+ 2917 2002-02-18  0.3
+ 2918 2002-02-19  3.8
+ 2919 2002-02-20 43.6
+ 2920 2002-02-21  1.0
+ 2921 2002-02-22  5.6
+ 2922 2002-02-23 10.6
+ 2923 2002-02-24  2.8
+ 2924 2002-02-25 19.1
+ 2925 2002-02-26 20.5
+ 2926 2002-03-06  0.0
+ 2927 2002-05-06  0.0
+ 2928 2002-05-07  0.0
+ 2929 2002-05-08  0.0
+ 2930 2002-05-09  0.0") )

> dtdta[dtdta$V3 == 0, ]

    V1         V2 V3
1  2916 2002-02-17  0
11 2926 2002-03-06  0
12 2927 2002-05-06  0
13 2928 2002-05-07  0
14 2929 2002-05-08  0
15 2930 2002-05-09  0

You seem to be using "0" as a missing marker. That's bad practice, but I suppose it's possble you cannot change how your instruments report. You should be using NA and the functions that support proper treatment of "missingness".


David,

I think that he is actually looking for dates where there is no measurement as opposed to dates where the measurement is 0.

Thus:

> DF
     V1         V2   V3
1  2916 2002-02-17  0.0
2  2917 2002-02-18  0.3
3  2918 2002-02-19  3.8
4  2919 2002-02-20 43.6
5  2920 2002-02-21  1.0
6  2921 2002-02-22  5.6
7  2922 2002-02-23 10.6
8  2923 2002-02-24  2.8
9  2924 2002-02-25 19.1
10 2925 2002-02-26 20.5
11 2926 2002-03-06  0.0
12 2927 2002-05-06  0.0
13 2928 2002-05-07  0.0
14 2929 2002-05-08  0.0
15 2930 2002-05-09  0.0


# Convert V2 to dates
# Default format is "%Y-%m-%d"
# See ?as.Date
DF$V2 <- as.Date(DF$V2)


# Get the range of dates covered
DateRange <- seq(min(DF$V2), max(DF$V2), by = 1)


# Get the dates in DateRange that are not in DF$V2
# See ?"%in%"
> DateRange[!DateRange %in% DF$V2]
 [1] "2002-02-27" "2002-02-28" "2002-03-01" "2002-03-02" "2002-03-03"
 [6] "2002-03-04" "2002-03-05" "2002-03-07" "2002-03-08" "2002-03-09"
[11] "2002-03-10" "2002-03-11" "2002-03-12" "2002-03-13" "2002-03-14"
[16] "2002-03-15" "2002-03-16" "2002-03-17" "2002-03-18" "2002-03-19"
[21] "2002-03-20" "2002-03-21" "2002-03-22" "2002-03-23" "2002-03-24"
[26] "2002-03-25" "2002-03-26" "2002-03-27" "2002-03-28" "2002-03-29"
[31] "2002-03-30" "2002-03-31" "2002-04-01" "2002-04-02" "2002-04-03"
[36] "2002-04-04" "2002-04-05" "2002-04-06" "2002-04-07" "2002-04-08"
[41] "2002-04-09" "2002-04-10" "2002-04-11" "2002-04-12" "2002-04-13"
[46] "2002-04-14" "2002-04-15" "2002-04-16" "2002-04-17" "2002-04-18"
[51] "2002-04-19" "2002-04-20" "2002-04-21" "2002-04-22" "2002-04-23"
[56] "2002-04-24" "2002-04-25" "2002-04-26" "2002-04-27" "2002-04-28"
[61] "2002-04-29" "2002-04-30" "2002-05-01" "2002-05-02" "2002-05-03"
[66] "2002-05-04" "2002-05-05"

HTH,

Marc Schwartz

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