Hi Philip,
My fault for assuming that what worked for the sample data would work
for the entire data set. If you run the following code:
# read the file into a data frame
phdf<-read.csv("phdf.csv",stringsAsFactors=FALSE)
print(dim(phdf))
# create a logical variable for the subsetting step
keep<-
r
Sent: Friday, August 14, 2020 2:43 PM
To: Philip
Cc: r-help
Subject: Re: [R] Hot Air Balloon Weather Briefings
Well which is it?:
"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. "
or
"It would be eve
On 2020-08-14 15:56 -0700, Bert Gunter wrote:
| On Fri, Aug 14, 2020 at 3:21 PM Rasmus Liland wrote:
| |
| | As to Bert's reply, I am a loss as
| | how to use the lengths list in
| | rle(rap$Speed) for this ...
|
| I showed how in my message for one
| interpretation of the query. I would
| nee
On 2020-08-14 13:58 -0700, Philip 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.
Well which is it?:
"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. "
or
"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 minu
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
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 flig
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