On 09.08.2010 13:17, szisziszilvi wrote:
Hello!
E.g. I have a file like sample.csv:
condition1;condition2;myVar
0.902443929;0.879344831;0.963357725
0.91014254;0.717720763;0.953787867
0.899773581;0.871760835;1.031798755
0.892074969;0.863043345;1.080447426
0.847759139;0.894642857;1.080521187
0.847179086;0.89650009;1.111348011
0.849229318;0.912751303;1.154026236
See function plot3d() in package "rgl", cloud() in "lattice",
scatterplot3d() in "scatterplot3d", etc.
Uwe Ligges
(... some thousands of measurements, like (p,V,T) - just other types of
physical quantities)
(wherever a data misses, it's sign is -999)
I can read it into a data frame like:
mes<- read.csv("sample.csv", sep=";", na.strings="-999")
But what shall I do afterwards? I've tried to understand persp, but that
doesn't really seem to be the solution.
Maybe it would help if you could tell me just which example to check more
carefully on the mentioned page. I've tried to search for one, but failed
unfortunatelly.
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