R help - Apr 2016 - selecting columns from a data frame or data table by type, ie, numeric, integer

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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> dt1[ vapply(dt1, FUN=is.numeric, FUN.VALUE=NA) ]
    a   c
1   1 1.1
2   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
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
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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

? ? ? ? [[alternative HTML version deleted]]

______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.




  
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