What if you have over 50 matrices and you don't want to write them all out
one-by-one? I know there's something really quite simple, but I haven't
found it yet!...
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I have a vector of unique elements that I want to replicate a variable number
of times depending on the element (lengths all > 800). However I noticed
that the resulting length was not the sum of the each argument. The
following example demonstrates this.
I am confused as to why this works:
I've exceeded the maximum time I am willing to accept for solving simple
problems so I thank all in advance for your assistance.
I am trying to plot text combined with an object value and a superscript.
obv = 5
text = "Population mean ="
ss = ^o # degrees
Something like this (very naive so yo
Is there any really easy way to truncate integers with several consecutive
digits without rounding and without converting from numeric to character
(using strsplit, etc.)?? Something along these lines:
e.g. = 456
truncfun(e.g., location=1)
= 4
truncfun(e.g., location=1:2)
= 45
truncfun(e.g.,
sample(data, 3, replace=FALSE)[,-1:2]
or
sample(data, 3, replace=FALSE)[,-c("id","pID50")]
Tyler
On Wed, Jul 14, 2010 at 1:17 PM, Addi Wei [via R] <
ml-node+2289092-1912443153-77...@n4.nabble.com
> wrote:
> id pID50 apol a_acca_acid a_aro a_base a_count
> 1 mol.11 3.63
this isn't a whole lot different, but if x is a data.frame (and not a
matrix), you could also try this:
names(x)[which(names(x)=="oldname")]= "newname"
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Here is another way of going about it (presuming we are correct about what
you are after):
i=1:10
j=1:10
unlist(lapply(i, function(x) paste("X", x, j, sep="_")))
Tyler
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Henrique is correct; entering duplicated(df) will return an index of TRUE or
FALSE for every row. TRUE indicates a duplicated row.
df[duplicated(df),] # shows which rows are repeated
df[-duplicated(df),] # shows which rows are unique
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It's not really clear what the structure of your data is, nor how exactly you
are sampling it (you need to provide an example), but you could try adding
this to the end of your sample command (if the result is a data.frame or
matrix): [,-1]
Tyler
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I've been constructing utilization distributions for 63 animal movement
trajectories using a Brownian bridge movement model with BBMM. I started
noticing after running the routine numerous times at different resolutions
t
which(!is.na(dat1))
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In conducting studies of animal orientation and displacement, I need to
produce circular histograms of angles (bearings in radians 0-2pi) where the
centre of the circle indicates very few observations for a given bin of
angles and outwardly concentric circles indicate greater frequencies of
observ
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