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?
Kind regards
Georg
Von: Martin Maechler <maech...@stat.math.ethz.ch>
An: <g.maub...@weinwolf.de>,
Kopie: Carl Sutton <suttonc...@ymail.com>, "r-help@r-project.org"
<r-help@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.maub...@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@r-project.org>
> An: William Dunlap <wdun...@tibco.com>,
> Kopie: "r-help@r-project.org" <r-help@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-boun...@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
<wdun...@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@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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