Removing variables from data frame with a wile card

Sun, Jan 15, 2023 8:54 AM

I am new to this thread. At the risk of presenting something that has been shown before, below I demonstrate how a column in a data frame can be dropped using a wild card, i.e. a column whose name starts with "th" using nothing more than base r functions and base R syntax. While additions to R such as tidyverse can be very helpful, many things that they do can be accomplished simply using base R.  

# Create data frame with three columns
one <- rep(1,10)
one
two <- rep(2,10)
two
three <- rep(3,10)
three
mydata <- data.frame(one=one, two=two, three=three)
cat("Data frame with three columns\n")
mydata

# Drop the column whose name starts with th, i.e. column three
# Find the location of the column
ColumToDelete <- grep("th",colnames((mydata)))
cat("The colomumn to be dropped is the column called three, which is column",ColumToDelete,"\n")
ColumToDelete

# Drop the column whose name starts with "th"
newdata2 <- mydata[,-ColumnToDelete]
cat("Data frame after droping column whose name is three\n")
newdata2

I hope this helps.
John

From: R-help <r-help-bounces at r-project.org> on behalf of 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'
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"...
>>>
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Removing variables from data frame with a wile card

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