thr3ads.net - R help - [R] Removing variables from data frame with a wile card [Jan 2023]

If this information is useful, please help other people find it:
Share via:

@vi@e@gross m@iii@g oii gm@ii@com

2023-Jan-14 17:27 UTC

[R] Removing variables from data frame with a wile card

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-bounces at r-project.org> On Behalf Of Steven Yen
Sent: Saturday, January 14, 2023 7:49 AM
To: Andrew Simmons <akwsimmo at gmail.com>
Cc: R-help Mailing List <r-help at 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 <akwsimmo at 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 <styen at
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 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.
	[[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.

Valentin Petzel

2023-Jan-14 18:21 UTC

head link

[R] Removing variables from data frame with a wile card

Hello Avi,

while something like d$something <- ... may seem like you're directly
modifying the data it does not actually do so. Most R objects try to be
immutable, that is, the object may not change after creation. This guarantees
that if you have a binding for same object the object won't change sneakily.

There is a data structure that is in fact mutable which are environments. For
example compare

L <- list()
local({L$a <- 3})
L$a

with

E <- new.env()
local({E$a <- 3})
E$a

The latter will in fact work, as the same Environment is modified, while in the
first one a modified copy of the list is made.

Under the hood we have a parser trick: If R sees something like

f(a) <- ...

it will look for a function f<- and call

a <- f<-(a, ...)

(this also happens for example when you do names(x) <- ...)

So in fact in our case this is equivalent to creating a copy with removed
columns and rebind the symbol in the current environment to the result.

The data.table package breaks with this convention and uses C based routines
that allow changing of data without copying the object. Doing

d[, (cols_to_remove) := NULL]

will actually change the data.

Regards,
Valentin

14.01.2023 18:28:33 avi.e.gross at gmail.com:
> 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-bounces at r-project.org> On Behalf Of Steven
Yen
> Sent: Saturday, January 14, 2023 7:49 AM
> To: Andrew Simmons <akwsimmo at gmail.com>
> Cc: R-help Mailing List <r-help at 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 <akwsimmo at
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 <styen at
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 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.
> 
> ??? [[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.
> 
> ______________________________________________
> 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.

John Kane

2023-Jan-14 21:07 UTC

head link

[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.gross at 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-bounces at r-project.org> On Behalf Of Steven
Yen
> Sent: Saturday, January 14, 2023 7:49 AM
> To: Andrew Simmons <akwsimmo at gmail.com>
> Cc: R-help Mailing List <r-help at 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 <akwsimmo at
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 <styen at
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 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.
>
>         [[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.
>
> ______________________________________________
> 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.
>

-- 
John Kane
Kingston ON Canada

	[[alternative HTML version deleted]]

@vi@e@gross m@iii@g oii gm@ii@com

2023-Jan-15 01:03 UTC

head link

[R] Removing variables from data frame with a wile card

Valentin,

You are correct that R does many things largely behind the scenes that make some
operations fairly efficient.
>From a programming point of view, though, many people might make a
data.frame and not think of it as a list of vectors of the same length that are
kept that way.
So if they made a copy of the original data with fewer columns, they might be
tempted to think the original item was completely copied and the original is
either around or if the identifier was re-used, will be garbage collected. As
you note, the only thinks collected are the columns you chose not to include.

For some it seems cleaner to set a list item to NULL, which seems to remove it
immediately.

The real point I hoped to make is that using base R, you can indeed approach
removing (multiple) columns in two logical ways. One is to seemingly remove them
in the original object, even if your point is valid. The other is to make a copy
of just what you want and ignore the rest and it may be kept around or not.

If someone really wanted to get down to the basics, they could get a reference
to all the columns they want to keep, as in col1 <- mydata[["col1"]
] and use those to make a new data.frame, or many other variants on these
methods.

Many programming languages have some qualms (I mean designers and programmers,
and just plain purists) about when "pointers" of sorts are used and
whether things should be mutable and so on so I prefer to avoid religious wars.

-----Original Message-----
From: Valentin Petzel <valentin at petzel.at> 
Sent: Saturday, January 14, 2023 1:21 PM
To: avi.e.gross at gmail.com
Cc: 'R-help Mailing List' <r-help at r-project.org>
Subject: Re: [R] Removing variables from data frame with a wile card

Hello Avi,

while something like d$something <- ... may seem like you're directly
modifying the data it does not actually do so. Most R objects try to be
immutable, that is, the object may not change after creation. This guarantees
that if you have a binding for same object the object won't change sneakily.

There is a data structure that is in fact mutable which are environments. For
example compare

L <- list()
local({L$a <- 3})
L$a

with

E <- new.env()
local({E$a <- 3})
E$a

The latter will in fact work, as the same Environment is modified, while in the
first one a modified copy of the list is made.

Under the hood we have a parser trick: If R sees something like

f(a) <- ...

it will look for a function f<- and call

a <- f<-(a, ...)

(this also happens for example when you do names(x) <- ...)

So in fact in our case this is equivalent to creating a copy with removed
columns and rebind the symbol in the current environment to the result.

The data.table package breaks with this convention and uses C based routines
that allow changing of data without copying the object. Doing

d[, (cols_to_remove) := NULL]

will actually change the data.

Regards,
Valentin

14.01.2023 18:28:33 avi.e.gross at gmail.com:
> 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-bounces at r-project.org> On Behalf Of Steven
Yen
> Sent: Saturday, January 14, 2023 7:49 AM
> To: Andrew Simmons <akwsimmo at gmail.com>
> Cc: R-help Mailing List <r-help at 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 <akwsimmo at
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 <styen at
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 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.
> 
>     [[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.
> 
> ______________________________________________
> 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.

Seemingly Similar Threads

Search for more seemingly similar threads

R help - Jan 2023 - Removing variables from data frame with a wile card

[R] Removing variables from data frame with a wile card

[R] Removing variables from data frame with a wile card

[R] Removing variables from data frame with a wile card

[R] Removing variables from data frame with a wile card

Seemingly Similar Threads