These are GPS information from 3 trips.
Data frames with the following variables.
Index
Measurement number
Time
a POSIXt, Time of measurement
Elevation
a numeric vector, Elevation in Feet
Leg.Dist
a character/numeric vector, The distance
traveled in that leg (in feet for ccc
)
Leg.Time
a difftime, the time of that leg
Speed
a numeric vector, Speed in mph
Direction
a numeric vector, Direction in Degrees, 0 is North, 90 is East, 180 is South, 270 is West
LatLon
a character vector, Latitude and Longitude as characters
Leg.Dist.f
a numeric vector, Length of that leg in feet
Leg.Dist.m
a numeric vector, Length of that leg in miles
Lat
a numeric vector, Numeric latitude
Lon
a numeric vector, Numeric longitude (negative for west)
Distance
a numeric vector, Distance from start in feet
Distance.f
a numeric vector, Distance from start in feet
Distance.m
a numeric vector, Distance from start in miles
Time2
a difftime, Time from start
Time3
a difftime, cumsum of Leg.Time
The data frame ccc
came from when I was walking back to my
office from a meeting and decided to take the scenic route and started
the GPS.
The data frame h2h
is a trip from my office to another for a
meeting. The first part is traveling by car, the last part by foot
from the parking lot to the building. Speed is a mixture of
distributions.
The data frame towork
came from driving to work one morning
(the first point is where the GPS got it's first lock, not my house).
The overall trip was mostly NorthWest but with enough North and
NorthEast that a simple average of direction shows SouthEast, good
example for circular stats.
if( interactive() ){
with(ccc, TkApprox(Distance, Elevation))
}
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