[R] time-series data and time-invariant missing values

[Gabor Grothendieck]

Check out na.locf in the zoo package.  Here we fill in
NAs going forward and just in case there were NAs
right at the beginning we fill them in backward as well.

library(zoo)
x <- as.Date(c(NA, "2000-01-01", NA))
x2 <- na.locf(x, na.rm = FALSE)
x2 <- na.locf(x2, fromLast = TRUE, na.rm = FALSE)

gives:

> x2
[1] "2000-01-01" "2000-01-01" "2000-01-01"


On Mon, Apr 6, 2009 at 7:13 AM, Kunzler, Andreas <a.kunzler at bzaek.de> wrote:
> Dear list,
>
> I have some problems with time-series data and missing values of time-invariant informations like sex or the birth-date.
>
> Assume a data (d) structure like
>
> id      birth           sex     year of observation
> 1       NA              NA      2006
> 1       1976-01-01      male    2007
> 1       NA              NA      2008
>
> I am looking for a way to replace the missing values.
>
> Right know my answer to this problem slows down R
>
>
>
> for (i in 1:length(d[,1])){ # for all observations
>
>        if (is.na(d$birth)[i])==F){ # Check if birth of observation(i) is missing
>            d$birth_2[i] <- as.Date(birth[i],"%d.%m.%Y")
>        }else{
>            d$birth2[i]  <- d$birth[id[i]==d$id & is.na(d$birth)==F],"%d.%m.%Y")[1] # if birth of observation (i) is missing, take a observation of another year
>        }
>    }
> }
>
> Result:
>
>
> id      birth           sex     year of observation     birth2
> 1       NA              NA      2006                    1976-01-01
> 1       01.01.1976      male    2007                    1976-01-01
> 1       NA              NA      2008                    1976-01-01
>
> unfortunately the data consists of over 20000 observations a year.
>
> Does anybody know a better way?
>
> Thanks
>
> Mit freundlichen Grüßen
>
> Andreas Kunzler
> ____________________________
> Bundeszahnärztekammer (BZÄK)
> Chausseestraße 13
> 10115 Berlin
>
> Tel.: 030 40005-113
> Fax:  030 40005-119
>
> E-Mail: a.kunzler at bzaek.de
>
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