Hi,
thanks for your reply.
I attached the example.
I tried your suggestion:
data[is.factor(data)] <- lapply(data[is.factor(data)], function(x)
as.numeric(as.character(x)))
But I still have the var as factors.
I'm thinking now, in the txt file the decimals numbers are separated with a
coma. W
probelm solved:
data <- read.table("pdvspt.txt", header = T, dec = ",")
It was the coma, now I have everything in numeric.
Thanks a lot for the support!
Ale
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8:05 AM
> To: r-help@r-project.org
> Subject: [R] as.integer
>
>
> Hi,
>
> Is there a way to recursively change the variables imported with
> read.table(..) - and then attached with attach(..) - from as.factor to
> as.integer?
> I have about 9 variables that are no
1) Give us a reproducible example.
2) You probably don't want to use attach.
3) Yes there is a way, but without an example, it's hard to say what
will work. Assume a data.frame called df, maybe something like the
following, which is untested...
df[is.factor(df)] <- lapply(df[is.factor(df)],
Hi,
Is there a way to recursively change the variables imported with
read.table(..) - and then attached with attach(..) - from as.factor to
as.integer?
I have about 9 variables that are now recognized as factors but I need to do
statistics on them so I need to change them in as.integer. It works,
another way:
> x <- c(1.1,2.1,3.1,4.1,5.1)
> as.integer((x - round(x)) * 10)
[1] 1 1 1 0 0
> as.integer((10 * x - round(10 * x, -1)))
[1] 1 1 1 1 1
>
2010/3/11 Lilia Leticia Ramírez Ramírez
> Hello All,
>
> I would like to report the following bug or maybe you can explain if I am
> wrong.
>
>
FAQ 7.31
2010/3/11 Lilia Leticia Ramírez Ramírez
> Hello All,
>
> I would like to report the following bug or maybe you can explain if I am
> wrong.
>
> I am sampling from two different populations with weights. The two
> populations have the same age groups and I want to distinguish where I a
Hello All,
I would like to report the following bug or maybe you can explain if I am
wrong.
I am sampling from two different populations with weights. The two
populations have the same age groups and I want to distinguish where I am
sampling from. That is why I am using a matrix such as:
matrix
a
Thanks to all!
This is really helpful!
Sincerely,
Erin
On Jan 17, 2008 12:00 PM, Marc Schwartz <[EMAIL PROTECTED]> wrote:
> Erin Hodgess wrote:
> > Hi R People:
> >
> > I'm reading "Statistical Computing with R", by Maria Rizzo, and it's
> > really good.
> >
> > Anyhow, I have a question about
Erin Hodgess wrote:
> Hi R People:
>
> I'm reading "Statistical Computing with R", by Maria Rizzo, and it's
> really good.
>
> Anyhow, I have a question about something in there.
>
>> u<- runif(5)
>> u
> [1] 0.1177041 0.4271790 0.4601597 0.2204846 0.4051473
>> #in the book
>> sum(as.integer(u> 0.4
Erin Hodgess wrote:
> Hi R People:
>
> I'm reading "Statistical Computing with R", by Maria Rizzo, and it's
> really good.
>
> Anyhow, I have a question about something in there.
>
>
>> u <- runif(5)
>> u
>>
> [1] 0.1177041 0.4271790 0.4601597 0.2204846 0.4051473
>
>> #in the book
>> sum
Hi R People:
I'm reading "Statistical Computing with R", by Maria Rizzo, and it's
really good.
Anyhow, I have a question about something in there.
> u <- runif(5)
> u
[1] 0.1177041 0.4271790 0.4601597 0.2204846 0.4051473
> #in the book
> sum(as.integer(u > 0.4))
[1] 3
> #what I would do
> sum(u
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