[R] Antwort: Antwort: Re: selecting columns from a data frame or data table by type, ie, numeric, integer

PIKAL Petr petr.pikal at precheza.cz
Wed May 4 10:32:00 CEST 2016


Hi

> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of
> G.Maubach at weinwolf.de
> Sent: Wednesday, May 4, 2016 10:06 AM
> To: Martin Maechler <maechler at stat.math.ethz.ch>
> Cc: r-help at r-project.org
> Subject: [R] Antwort: Antwort: Re: selecting columns from a data frame or
> data table by type, ie, numeric, integer
>
> Hi Martin,
>
> many thanks for your answer and your broad explanation.
>
> I am a newbie to "R" and got help on this list and thought I could give
> something back what looked OK to me.
>
> regarding 0)
> You're right, it's pseudo code. I assumed that anybody on the list would be
> able to adapt the code to their needs so that it worked. Next time I will post
> runnable code.
>
> regarding 1)
> Your right: "[, i]" is missing. My fault. Sorry.
>
> regarding 3)
> I got your point and will do better in the future.
>
> One question: What books do you recommend to read to get to know "R"
> better?

Freely available from CRAN

These I can recommend as I went through them

“A Guide for the Unwilling S User” by Patrick Burns
“Using R for Data Analysis and Graphics - Introduction, Examples and Commentary”  by John Maindonald (PDF, data sets and scripts are available at JM's homepage).
“Practical Regression and Anova using R” by Julian Faraway (PDF, data sets and scripts are available at the book homepage).

There are also some German books but I do not have experience with them.

Books from bookstores
Modern Applied Statistics with S. Fourth Edition, by W. N. Venables and B. D. Ripley
Introductory Statistics with R, Authors: Dalgaard, Peter

Cheers
Petr

>
> Kind regards
>
> Georg
>
>
>
>
> Von:    Martin Maechler <maechler at stat.math.ethz.ch>
> An:     <G.Maubach at weinwolf.de>,
> Kopie:  Carl Sutton <suttoncarl at ymail.com>, "r-help at r-project.org"
> <r-help at r-project.org>
> Datum:  04.05.2016 09:05
> Betreff:        [R] Antwort: Re: selecting columns from a data frame or
> data table      by type, ie, numeric, integer
>
>
>
> >>>>>   <G.Maubach at weinwolf.de>
> >>>>>     on Wed, 4 May 2016 08:30:50 +0200 writes:
>
> > Hi All,
> > Hi Carl,
> >
> > I am not sure if this is useful to you, but I followed your
> > conversation
>
> > and thought of you when I read this:
> >
> > for (i in 1:ncol(dataset)) {
> >   if(class(dataset) == "character|numeric|factor|or whatsoever") {
> >     dataset[, i] <- as.factor(dataset[, i])
> >   }
> > }
>
> Ouch -- so many problems in such a short piece of R code !!!
>
> > Source: Zumel, Nina / Mount, John: Practical Data Science with R,
> Manning
> > Publications: Shelter Island, 2014, Chapter 2: Loading data into R, p.
> 25
>
> Sorry, but after reading the above, I'd strongly recommend getting better
> books about R...
>        {{maybe do not take those containing "data science" ;-)}}
>
> Compared to the nice and efficient solution of Bill Dunlap, the above is really
> bad-bad-bad  in at least four ways :
>
> 0) They way you write it above, you cannot use it,
>      <string> == "variant1|variant2|..."
>    is pseudocode and does not really work
>
> 1) Note the missing "[, i]"  in the 2nd line: It should be
>      if(class(dataset[, i]) ...
>
> 2) A for loop changing each column at a time is really slow for
>    largish data sets
>
> 3) [last but not at all least!]
>    Please ... many of you readers, do learn:
>
>  Using checks such as
>        if ( class(x) == "numeric" )
>  are (almost) always wrong by design !!!
>
>  Instead you really should (almost) always use
>
>                   if(inherits(x, "numeric"))
>
> Why?  Because classes in R (S3 or S4) can *extend* other classes.
> Example: Many of you know that after   fm <- glm(...)
> class(fm) is   c("glm", "lm")   and so
>
>     > if(class(fm) == "lm")
>     + "yes"
>     Warning message:
>     In if (class(fm) == "lm") "yes" :
>       the condition has length > 1 and only the first element will be used
>
> Similarly, in your case
>
> y <- 1:10
> class(y) <- c("myNumber", "numeric")
>
> when that 'y' is a column in your data frame, the test for  if(class(dataset[,i])
> == "numeric")  will *not* work but actually produce the above warning.
>
> However, one  could als have had
>
> Num <- setClass("Num", contains="numeric") N <- Num(1:10)
>
>      > Num <- setClass("Num", contains="numeric")
>      > N <- Num(1:10)
>      > N
>      An object of class "Num"
>       [1]  1  2  3  4  5  6  7  8  9 10
>      > if(class(N) == "numeric") "yes" else "no"
>      [1] "no"
>      >
>
> I hope that many of the readers --- including *MANY* authors of R packages
> !! --- have understood the above and will fix their R code -- and even more
> their books where applicable !!
>
> Martin Maechler,
> ETH Zurich & R Core Team
>
> >
>
>
> > This way you can select variables of a certain class only and do
> > transformations. I found that this approach is not applicable if used
> with
> > statistical functions like head(). Transformations worked fine for me.
> >
> > I found reading the above given source worthwile.
> >
> > Kind regards
> >
> > Georg
> >
> > PS: I am not related to the above given authors. I am just a reader
> > reporting on - at least to me - a valuable ressource.
> >
> >
> >
> > Von:    Carl Sutton via R-help <r-help at r-project.org>
> > An:     William Dunlap <wdunlap at tibco.com>,
> > Kopie:  "r-help at r-project.org" <r-help at r-project.org>
> > Datum:  29.04.2016 22:08
> > Betreff:        Re: [R] selecting columns from a data frame or data
> table
> > by type, ie, numeric, integer
> > Gesendet von:   "R-help" <r-help-bounces at r-project.org>
> >
> >
> >
> > Thank you Bill Dunlap.  So simple I never tried that approach. Tried
> > dozens of others though, read manuals till I was getting headaches,
> > and
> of
> > course the answer was simple when one is competent.   Learning, its a
> > struggle, but slowly getting there.
> > Thanks again
> >  Carl Sutton CPA
> >
> >
> >     On Friday, April 29, 2016 10:50 AM, William Dunlap
> <wdunlap at tibco.com>
> > wrote:
> >
> >
> >
> >  > dt1[ vapply(dt1, FUN=is.numeric, FUN.VALUE=NA) ]    a   c1   1 1.12 2
>
> > 1.0...10 10 0.2
> >
> >
> > Bill Dunlap
> > TIBCO Software
> > wdunlap tibco.com
> > On Fri, Apr 29, 2016 at 9:19 AM, Carl Sutton via R-help
> > <r-help at r-project.org> wrote:
> >
> > Good morning RGuru's
> > I have a data frame of 575 columns.  I want to extract only those
> columns
> > that are numeric(double) or integer to do some machine learning with.
> > I
>
> > have searched the web for a couple of days (off and on) and have not
> found
> > anything that shows how to do this.   Lots of ways to extract rows, but
> > not columns.  I have attempted to use "(x == y)" indices extraction
> method
> > but that threw error that == was for atomic vectors and lists, and I
> > was
>
> > doing this on a data frame.
> >
> > My test code is below
> >
> > #  a technique to get column classes
> > library(data.table)
> > a <- 1:10
> > b <- c("a","b","c","d","e","f","g","h","i","j")
> > c <- seq(1.1, .2, length = 10)
> > dt1 <- data.table(a,b,c)
> > str(dt1)
> > col.classes <- sapply(dt1, class)
> > head(col.classes)
> > dt2 <- subset(dt1, typeof = "double" | "numeric")
> > str(dt2)
> > dt2   #  not subset
> > dt2 <- dt1[, list(typeof = "double")]
> > str(dt2)
> > class_data <- dt1[,sapply(dt1,is.integer) | sapply(dt1, is.numeric)]
> > class_data
> > sum(class_data)
> > typeof(class_data)
> > names(class_data)
> > str(class_data)
> >  Any help is appreciated
> > Carl Sutton CPA
>
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