John,
I am very familiar with the evolving tidyverse and some messages a while back
included people who wanted this forum to mainly stick to base R, so I leave out
examples.
Indeed, the tidyverse is designed to make it easy to select columns with all
kinds of conditions including using regular expressions that allow more
precision (as does grep) so you want to match “yr” followed by exactly one or
two digits. Some of the answers suggest starting with “yr” was enough. They
also allow selecting on arbitrary considerations like whether the column
contains numeric data. You can do most things in base R, albeit I find the
tidyverse method easier most of the time and also able to do some extremely
complicated things with some care, such as creating multiple new columns form a
set of columns that each implement a different function like mean, and mode and
standard deviation and make the new columns the same names as the one they are
derived from but a different suffix reflecting what transformation was done.
One nice feature is the ideas behind how data streams through multiple steps
with one or a few transformations in each step, and the intermediate parts you
do not want, simply melt away. The part about selecting or deselecting columns
can often be used in many of the verbs.
From: John Kane <jrkrid...@gmail.com>
Sent: Saturday, January 14, 2023 4:07 PM
To: avi.e.gr...@gmail.com
Cc: R-help Mailing List <r-help@r-project.org>
Subject: Re: [R] Removing variables from data frame with a wile card
You rang sir?
library(tidyverse)
xx = 1:10
yr1 = yr2 = yr3 = rnorm(10)
dat1 <- data.frame(xx , yr1, yr2, y3)
dat1 %>% select(!starts_with("yr"))
or for something a bit more exotic as I have been trying to learn a bit about
the "data.table package
library(data.table)
xx = 1:10
yr1 = yr2 = yr3 = rnorm(10)
dat2 <- data.table(xx , yr1, yr2, yr3)
dat2[, !names(dat2) %like% "yr", with=FALSE ]
On Sat, 14 Jan 2023 at 12:28, <avi.e.gr...@gmail.com
<mailto:avi.e.gr...@gmail.com> > wrote:
Steven,
Just want to add a few things to what people wrote.
In base R, the methods mentioned will let you make a copy of your original DF
that is missing the items you are selecting that match your pattern.
That is fine.
For some purposes, you want to keep the original data.frame and remove a column
within it. You can do that in several ways but the simplest is something where
you sat the column to NULL as in:
mydata$NAME <- NULL
using the mydata["NAME"] notation can do that for you by using a loop of
unctional programming method that does that with all components of your grep.
R does have optimizations that make this less useful as a partial copy of a
data.frame retains common parts till things change.
For those who like to use the tidyverse, it comes with lots of tools that let
you select columns that start with or end with or contain some pattern and I
find that way easier.
-----Original Message-----
From: R-help <r-help-boun...@r-project.org
<mailto:r-help-boun...@r-project.org> > On Behalf Of Steven Yen
Sent: Saturday, January 14, 2023 7:49 AM
To: Andrew Simmons <akwsi...@gmail.com <mailto:akwsi...@gmail.com> >
Cc: R-help Mailing List <r-help@r-project.org <mailto:r-help@r-project.org> >
Subject: Re: [R] Removing variables from data frame with a wile card
Thanks to all. Very helpful.
Steven from iPhone
> On Jan 14, 2023, at 3:08 PM, Andrew Simmons <akwsi...@gmail.com
> <mailto:akwsi...@gmail.com> > wrote:
>
> You'll want to use grep() or grepl(). By default, grep() uses
> extended regular expressions to find matches, but you can also use
> perl regular expressions and globbing (after converting to a regular
> expression).
> For example:
>
> grepl("^yr", colnames(mydata))
>
> will tell you which 'colnames' start with "yr". If you'd rather you
> use globbing:
>
> grepl(glob2rx("yr*"), colnames(mydata))
>
> Then you might write something like this to remove the columns starting with
> yr:
>
> mydata <- mydata[, !grepl("^yr", colnames(mydata)), drop = FALSE]
>
>> On Sat, Jan 14, 2023 at 1:56 AM Steven T. Yen <st...@ntu.edu.tw
>> <mailto:st...@ntu.edu.tw> > wrote:
>>
>> I have a data frame containing variables "yr3",...,"yr28".
>>
>> How do I remove them with a wild card----something similar to "del yr*"
>> in Windows/doc? Thank you.
>>
>>> colnames(mydata)
>> [1] "year" "weight" "confeduc" "confothr" "college"
>> [6] ...
>> [41] "yr3" "yr4" "yr5" "yr6" "yr7"
>> [46] "yr8" "yr9" "yr10" "yr11" "yr12"
>> [51] "yr13" "yr14" "yr15" "yr16" "yr17"
>> [56] "yr18" "yr19" "yr20" "yr21" "yr22"
>> [61] "yr23" "yr24" "yr25" "yr26" "yr27"
>> [66] "yr28"...
>>
>> ______________________________________________
>> R-help@r-project.org <mailto:R-help@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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______________________________________________
R-help@r-project.org <mailto:R-help@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.
______________________________________________
R-help@r-project.org <mailto:R-help@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.
--
John Kane
Kingston ON Canada
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______________________________________________
R-help@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.
