On 14/03/17 14:56, Jinsong Zhao wrote:
Hi there,
I happened to find the following code can generate a data frame with
same column name.
x <- data.frame(a=c(1,2,3))
y <- data.frame(a=c(2,3,4))
z <- cbind(x,y)
However, in this case, one can not use the $ to extract the second
column, right?
I
Hi,
I would like to reshape a data.frame from long to wide format. However, the
reshape function does not seem to accept data containing rows with duplicate
idvar and timevar. Building upon the ?reshape example:
summary(Indometh)
wide <- reshape(Indometh, v.names = "conc", idvar = "Subject",
Hi there,
I happened to find the following code can generate a data frame with
same column name.
> x <- data.frame(a=c(1,2,3))
> y <- data.frame(a=c(2,3,4))
> z <- cbind(x,y)
However, in this case, one can not use the $ to extract the second
column, right?
Is it possible to prevent the cbi
> On Mar 13, 2017, at 5:53 PM, Val wrote:
>
> HI all,
>
> if first name is Alex then I want concatenate the second column to Alex
> to produce Alex and the second column value
>
> DF1 <- read.table(header=TRUE, text='first YR
> Alex2001
> Bob 2001
> Cory2001
> Cory2002
> Bob
HI all,
if first name is Alex then I want concatenate the second column to Alex
to produce Alex and the second column value
DF1 <- read.table(header=TRUE, text='first YR
Alex2001
Bob 2001
Cory2001
Cory2002
Bob 2002
Bob 2003
Alex2002
Alex2003
Alex2004')
Out
Please read and follow the posting guide.
Plain text only + code that you tried + reproducible exam (google it).
In general, we do not do tutorials here, but someone may indeed be
able to refer you to one on the web. Googling "principal coordinates
analysis tutorial R" appeared to bring up releva
Dear all,
First of all, I am so grateful if you can help me
in analyzing principle coordinate analysis of unweighted UniFrac distances
on R.
I am analyzing microbial species profile of an individual (BA) versus
reference population (HMP) and want to generate a PCoA graph to see whether
there any
Hello everyone,
I was working on a DeepNet project at home, with an old PC with 4Gb RAM,
running Ubuntu 16.04.
For efficiency reason, I stored my dataset as a csv file with write.csv and
reloaded it at will with read.csv. I did it several time, everything was
working fine.
This morning, at wo
Thank You
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: "r-help";
: Re: [R] Linear Mixed-Effects Model
Have you read the docs? Is this some kind of homework? -- this list
does not do homework. We expect m
The manual is talking about the angle between the variables in p dimensional
space were p is the number of variables. The angle can appear differently in
2-dimensions depending on your viewing angle (which dimensions you are
ignoring, think of how the 2-dimensional shadow of a 3-dimensional obje
Hi Roslinazairimah,
What you seem to want is fairly simple:
dt<-c("AA14068","AA13194","AE11054","AA12251","AA13228",
"AA13286","AA14090","AA13256","AA13260","AA13291",
"AA14099","AA15071","AA13143","AA14012","AA14039",
"AA15018","AA13234","AA13149","AA13282","AA13218")
dt[grep(pattern="AA14"
I imagine that the FieldStateOption is irrelevant, so you might be able to
create a data.frame like this:
library(tidyr)
fl <- readLines("pdf_dump.txt")
fl <- grep("FieldStateOption", fl, value = TRUE, invert = TRUE)
field_number <- vector(mode = "integer", length = length(fl))
tmpid <- 0
for(i
Hi Vijayan,
You have a bit of a problem with repeated field names. While you can
mangle the field names to do something like this, I don't see how you
are going to make sense of multiple "FieldStateOption" fields. The
strategy I would take is to collect all of the field names and then
set up rows w
Hi Roslinazairimah,
As Bert suggested, you should get acquainted with regular expressions. It
can be confusing at times, but pays off in the long run.
In your case, the pattern of "^[A-Z]{2}14.*" might work.
Best,
Ulrik
On Mon, 13 Mar 2017 at 06:20 roslinazairimah zakaria
wrote:
> Another que
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