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

Hi Martin and list:
First let me thank you for thinking of me.?? It is probably apparent that my programming experience is limited, and the vector aspect of R has taken some getting used to.?? A very very long time ago I did some programming in Fortran and for loops and if statements were ordinary, useful, and used frequently.?? Now if I see a for loop and if statement together then it is flatly apparent that I need to rework that code to take advantage of R's strengths using vectoized functions on whatever object I am working on.??
It has also become apparent that one should read manuals, experiment with some code to firmly cement the knowledge, and build a solid foundation.?? My natural inclination is the opposite.? I am anxious to produce some code to solve a problem or satisfy curiosity or ....? R is not something one can learn and use productively in a few weeks or months.?? It is powerful, subtle, and takes some thinking.?? I started this trek into R with Jared Lander's book "R for Everyone",? progressed to Prof Norman Matloff's "The Art of R Programming" (which was way beyond my comprehension at the beginning) and Hadley Wickham's "ggplot2" book, and several courses with Data Camp and Couresra.? One day I will be at the point where I do know what I don't know about R and at that time I will almost be competent with the language.

I have taken the work from Bill Dunlap and Giorgio Garziano and have applied it to my little project and am just amazed that so little code can do so much.? I have also followed Bert Gunter's advice and taken that code and dissected it item by item to comprehend what each element is doing.?? 

The knowledge and help on this list is just amazing and I do appreciate the efforts of all involved.? I read the digest daily .
Carl Sutton CPA

>>>>>? <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