Re: [R] proc standardize & data frame x and y
> 1) Can someone recommend an equivalent to SAS PROC Standardize in R? I > am in need to frequently standardize a data frame, with z-scores, or > squash to 0-1 scale - is there a slick function or package someone can > recommend? You could try rescaler in the reshape package. It currently supports five column wise rescaling/standardisation methods (common range, common variance, robust equivalent, rank, do nothing), and I could add more if needed. Regards, Hadley __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] proc standardize & data frame x and y
zubin,
for your second question:
supposed you have x1 and x2 and want to combine them in a matrix X in
a data frame called data, try the following code:
X<-matrix(1:10, ncol = 2, dimnames = list(NULL, c("x1", "x2")));
class(X)
class(X)<-"AsIs";
class(X)
data<-data.frame(X);
summary(data);
On 8/12/06, zubin <[EMAIL PROTECTED]> wrote:
> Hello! i know these are basic but i cannot seem to find the answer thru
> my searches..
>
> 1) Can someone recommend an equivalent to SAS PROC Standardize in R? I
> am in need to frequently standardize a data frame, with z-scores, or
> squash to 0-1 scale - is there a slick function or package someone can
> recommend?
>
> 2) Also, have data sets with a lot of predictor variables. in the
> diabetes data frame i see that fields have been grouped to X and Y
> variables, making it very easy to identify X and Y in the regression
> techniques. How is this done, how do you group lets say a group of
> columns into 1 matrix, within a data frame. example: the AsIs group is
> a matrix of X variables:
>
> > str(diabetes)
> `data.frame': 442 obs. of 3 variables:
> $ x : AsIs [1:442, 1:10] 0.038075 -0.00188 0.085298
> -0.08906 0.005383 ...
> ..- attr(*, "dimnames")=List of 2
> .. ..$ : NULL
> .. ..$ : chr "age" "sex" "bmi" "map" ...
> ..- attr(*, "class")= chr "AsIs"
> $ y : num 151 75 141 206 135 97 138 63 110 310 ...
> $ x2: AsIs [1:442, 1:64] 0.038075 -0.00188 0.085298
> -0.08906 0.005383 ...
> ..- attr(*, ".Names")= chr "age" "age" "age" "age" ...
> ..- attr(*, "dimnames")=List of 2
> .. ..$ : chr "1" "2" "3" "4" ...
> .. ..$ : chr "age" "sex" "bmi" "map" ...
> ..- attr(*, "class")= chr "AsIs"
>
> __
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
WenSui Liu
(http://spaces.msn.com/statcompute/blog)
Senior Decision Support Analyst
Health Policy and Clinical Effectiveness
Cincinnati Children Hospital Medical Center
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] proc standardize & data frame x and y
for proc standardzize, check ?scale On 8/12/06, zubin <[EMAIL PROTECTED]> wrote: > > Hello! i know these are basic but i cannot seem to find the answer thru > my searches.. > > 1) Can someone recommend an equivalent to SAS PROC Standardize in R? I > am in need to frequently standardize a data frame, with z-scores, or > squash to 0-1 scale - is there a slick function or package someone can > recommend? > > 2) Also, have data sets with a lot of predictor variables. in the > diabetes data frame i see that fields have been grouped to X and Y > variables, making it very easy to identify X and Y in the regression > techniques. How is this done, how do you group lets say a group of > columns into 1 matrix, within a data frame. example: the AsIs group is > a matrix of X variables: > > > str(diabetes) > `data.frame': 442 obs. of 3 variables: > $ x : AsIs [1:442, 1:10] 0.038075 -0.00188 0.085298 > -0.08906 0.005383 ... > ..- attr(*, "dimnames")=List of 2 > .. ..$ : NULL > .. ..$ : chr "age" "sex" "bmi" "map" ... > ..- attr(*, "class")= chr "AsIs" > $ y : num 151 75 141 206 135 97 138 63 110 310 ... > $ x2: AsIs [1:442, 1:64] 0.038075 -0.00188 0.085298 > -0.08906 0.005383 ... > ..- attr(*, ".Names")= chr "age" "age" "age" "age" ... > ..- attr(*, "dimnames")=List of 2 > .. ..$ : chr "1" "2" "3" "4" ... > .. ..$ : chr "age" "sex" "bmi" "map" ... > ..- attr(*, "class")= chr "AsIs" > > __ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- WenSui Liu (http://spaces.msn.com/statcompute/blog) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
