that others must surely have encountered and overcome this
challenge. If anyone can kindly point me in a productive direction, I will
be most grateful.
-
Glen Sargeant
Research Wildlife Biologist
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){
plot(df.lst[[nms]][,2], df.lst[[nms]][,3],col=clr[[nms]])
mtext(nms)})
dev.off()
-
Glen Sargeant
Research Wildlife Biologist
--
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can use lapply() to carry out the same operation on
#each component of your list. For example, to send plots to
#a pdf with 1 page for each component:
pdf(plot.pdf)
lapply(df.lst,function(df)plot(df[,2],df[,3]))
dev.off()
-
Glen Sargeant
Research Wildlife Biologist
--
View this message
one factor containing pixel values of 0-5 and
another factor containing all other pixel values. I have been
struggling to work out how to do this using either cut.im() or
cut.default(). Can anyone help?
-
Glen Sargeant
Research Wildlife Biologist
--
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http
Keith,
If you are working within a single time zone, including time zone
information with each record does not seem necessary and you probably are
not recording times to the sub-second. The best solution may thus be to use
a simpler date/time class that does not include time zone information.
Inchallah Yarab wrote:
i want to do a table summerizing the number of variable where z is in
[0-1000],],[1000-3000], [ 3000]
You can use cut to create a new vector of labels and tabulate the result.
Options control closed/open endpoints (see ?cut):
z -
jlwoodard wrote:
Each of the above lines successfully excludes the BLUE subjects, but the
BLUE category is still present in my data set; that is, if I try
table(Color) I get
RED WHITE BLUE
82 151 0
How can I eliminate the BLUE category completely so I can do a t-test
See also file.path() and create.dir(). You can use them with getwd() and
setwd() to specify and/or create subdirectories, relative to your current
working directory. Handy because they allow you to create paths and
directories with names derived within functions.
For example, I have used them
alamoboy wrote:
Newbie here. Many apologies in advance for using the incorrect lingo.
I'm new to statistics and VERY new to R.
I'm attempting to group or bin data together in order to analyze them
as a combined group rather than as discrete set. I'll provide a simple
example of the
alamoboy wrote:
Newbie here. Many apologies in advance for using the incorrect lingo.
I'm new to statistics and VERY new to R.
I'm attempting to group or bin data together in order to analyze them
as a combined group rather than as discrete set. I'll provide a simple
example of the
lawnboy34 wrote:
Hello,
Is there a combination of par() settings or other commands that will allow
me to uniformly reduce the size of graphics outputs? It appears that the
png() device outputs 5-inch by 5-inch images, and I am trying to change
my
whole script to produce 4x4 images
pmatch() facilitates a very simple solution:
#Data
IA - factor(c(1,2,2,3,3,4,3,5,5))
FixTime - c(200,350,500,600,700,850,1200,1350,1500)
#First occurrence of each level
first. - pmatch(levels(IA),IA)
#Use first occurrence to subscript a vector or data frame
FixTime[first.]
A simple way to
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