[R] Filling in missing time samples with na.approx

[Felipe Carrillo]

strange,,I don't see any change either, could it be that we have an older 
version of zoo?
 
Felipe D. Carrillo
Supervisory Fishery Biologist
Department of the Interior
US Fish & Wildlife Service
California, USA



----- Original Message ----
> From: Gabor Grothendieck <ggrothendieck at gmail.com>
> To: Jason Edgecombe <jason at rampaginggeek.com>
> Cc: r-help at stat.math.ethz.ch
> Sent: Mon, November 29, 2010 10:51:07 AM
> Subject: Re: [R] Filling in missing time samples with na.approx
> 
> On Mon, Nov 29, 2010 at 1:33 PM, Jason Edgecombe
> <jason at rampaginggeek.com> wrote:
> > On 11/29/2010 10:00 AM, Gabor Grothendieck wrote:
> >>
> >> On Mon, Nov 29, 2010 at 9:45 AM, Jason Edgecombe
> >> <jason at rampaginggeek.com>  wrote:
> >>
> >>>
> >>> Hi Everyone,
> >>>
> >>> I have a some data from a sports gps device like the following:
> >>>
> >>>        time latitude longitude altitude  distance heartrate
> >>> 1 1277648884 0.304048 -0.793819      260  0.000000        94
> >>> 2 1277648885 0.304056 -0.793772      262  4.307615        95
> >>> 3 1277648888 0.304060 -0.793696      263 11.262347        97
> >>> 4 1277648894 0.304075 -0.793544      263 25.237911       103
> >>> 5 1277648898 0.304085 -0.793455      263 33.322525       108
> >>> 6 1277648902 0.304064 -0.793387      256 40.042988       115
> >>>
> >>> As you can see, the samples have irregular holes in the time column. How
> >>> can
> >>> I fill in the missing samples using na.approx?
> >>>
> >>> I've tried to creating a blank series with no gaps and combine them, but
> >>> "merge" just adds columns and "rbind" compains about duplicate indexes.
> >>>
> >>> P.S. My GPS still has holes in the data when I turn off "smart recording"
> >>> :(
> >>>
> >>>
> >>
> >> Try this:
> >>
> >> Lines<- "time latitude longitude altitude  distance heartrate
> >> 1277648884 0.304048 -0.793819      260  0.000000        94
> >> 1277648885 0.304056 -0.793772      262  4.307615        95
> >> 1277648888 0.304060 -0.793696      263 11.262347        97
> >> 1277648894 0.304075 -0.793544      263 25.237911       103
> >> 1277648898 0.304085 -0.793455      263 33.322525       108
> >> 1277648902 0.304064 -0.793387      256 40.042988       115"
> >>
> >> # read in data
> >> library(zoo)
> >> z<- read.zoo(textConnection(Lines), header = TRUE)
> >>
> >> na.approx(z, xout = seq(min(time(z)), max(time(z))))
> >>
> >>
> >>
> >>
> >
> > No change:
> >> na.approx(z, xout = seq(min(time(z)), max(time(z))))
> >           latitude longitude altitude  distance heartrate
> > 1277648884 0.304048 -0.793819      260  0.000000        94
> > 1277648885 0.304056 -0.793772      262  4.307615        95
> > 1277648888 0.304060 -0.793696      263 11.262347        97
> > 1277648894 0.304075 -0.793544      263 25.237911       103
> > 1277648898 0.304085 -0.793455      263 33.322525       108
> > 1277648902 0.304064 -0.793387      256 40.042988       115
> >
> 
> It works for me.
> 
> > Lines <- "time latitude longitude altitude  distance heartrate
> + 1277648884 0.304048 -0.793819      260  0.000000        94
> + 1277648885 0.304056 -0.793772      262  4.307615        95
> + 1277648888 0.304060 -0.793696      263 11.262347        97
> + 1277648894 0.304075 -0.793544      263 25.237911      103
> + 1277648898 0.304085 -0.793455      263 33.322525      108
> + 1277648902 0.304064 -0.793387      256 40.042988      115"
> >
> > # read in data
> > library(zoo)
> > z <- read.zoo(textConnection(Lines), header = TRUE)
> >
> > na.approx(z, xout = seq(min(time(z)), max(time(z))))
>             latitude  longitude altitude  distance heartrate
> 1277648884 0.3040480 -0.7938190 260.0000  0.000000  94.00000
> 1277648885 0.3040560 -0.7937720 262.0000  4.307615  95.00000
> 1277648886 0.3040573 -0.7937467 262.3333  6.625859  95.66667
> 1277648887 0.3040587 -0.7937213 262.6667  8.944103  96.33333
> 1277648888 0.3040600 -0.7936960 263.0000 11.262347  97.00000
> 1277648889 0.3040625 -0.7936707 263.0000 13.591608  98.00000
> 1277648890 0.3040650 -0.7936453 263.0000 15.920868  99.00000
> 1277648891 0.3040675 -0.7936200 263.0000 18.250129 100.00000
> 1277648892 0.3040700 -0.7935947 263.0000 20.579390 101.00000
> 1277648893 0.3040725 -0.7935693 263.0000 22.908650 102.00000
> 1277648894 0.3040750 -0.7935440 263.0000 25.237911 103.00000
> 1277648895 0.3040775 -0.7935218 263.0000 27.259065 104.25000
> 1277648896 0.3040800 -0.7934995 263.0000 29.280218 105.50000
> 1277648897 0.3040825 -0.7934773 263.0000 31.301371 106.75000
> 1277648898 0.3040850 -0.7934550 263.0000 33.322525 108.00000
> 1277648899 0.3040797 -0.7934380 261.2500 35.002641 109.75000
> 1277648900 0.3040745 -0.7934210 259.5000 36.682756 111.50000
> 1277648901 0.3040693 -0.7934040 257.7500 38.362872 113.25000
> 1277648902 0.3040640 -0.7933870 256.0000 40.042988 115.00000
> 
> 
> 
> -- 
> Statistics & Software Consulting
> GKX Group, GKX Associates Inc.
> tel: 1-877-GKX-GROUP
> email: ggrothendieck at gmail.com
> 
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