Hot Air Balloon Weather Briefings
Hi Philip, Not very elegant, but: phdf<-read.table(text="Minute Second Speed 29 47 0 29 53 0 29 59 0 30 5 0 30 11 0 30 17 0 30 23 0 30 29 0 30 35 0 30 41 0 30 47 0 30 53 0 30 59 0 31 5 0 31 11 0 31 17 0.402649 31 23 0.671081 31 29 1.588225 31 35 2.438261 31 41 2.706693 31 47 2.930386 31 53 3.310666 31 59 3.198819 32 5 3.422512", header=TRUE,stringsAsFactors=FALSE) keep<-rep(TRUE,length(phdf$Speed)) for(mini in unique(phdf$Minute)) if(all(phdf$Speed[phdf$Minute == mini] == 0)) keep[phdf$Minute == mini]<-FALSE phdf<-phdf[keep,] Jim
On Sat, Aug 15, 2020 at 6:59 AM Philip <herd_dog at cox.net> wrote:
I?m trying to compare National Weather Service Rapid Update Forecast (RAP) data to GPS breadcrumbs collected by a really clever Apple Phone Ap that lays down longitude, latitude, altitude, compass direction, and speed every six seconds. Below is a small subset of the GPS data from another flight.
I want to delete the rows where the balloon does not move (Speed column) for a full minute assuming that it is sitting on the ground ? beginning of the flight, changing passengers, or waiting for the chase crew at the end of the flight. for example, I want to eliminate the data for minute 30 but keep the data for minute 31 because the balloon starts to move again at second 17. Any suggestions? I?ve tried putzing around with multiple lags without success.
Minute Second Speed
29 47 0
29 53 0
29 59 0
30 5 0
30 11 0
30 17 0
30 23 0
30 29 0
30 35 0
30 41 0
30 47 0
30 53 0
30 59 0
31 5 0
31 11 0
31 17 0.402649
31 23 0.671081
31 29 1.588225
31 35 2.438261
31 41 2.706693
31 47 2.930386
31 53 3.310666
31 59 3.198819
32 5 3.422512
It would be even better if I could delete the rows where there were ten consecutive zero speed entries such as from minute 30 second 17 to minute 31 second 11.
Thanks,
Philip Heinrich
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