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

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

Steven,

The default is drop=TRUE.

If you want to retain a data.frame and not have it reduced to a vector under some circumstances. 

https://win-vector.com/2018/02/27/r-tip-use-drop-false-with-data-frames/

-----Original Message-----
From: R-help <r-help-bounces using r-project.org> On Behalf Of Steven T. Yen
Sent: Sunday, February 12, 2023 5:19 PM
To: Andrew Simmons <akwsimmo using gmail.com>
Cc: R-help Mailing List <r-help using r-project.org>
Subject: Re: [R] Removing variables from data frame with a wile card

In the line suggested by Andrew Simmons,

mydata <- mydata[, !grepl("^yr", colnames(mydata)), drop = FALSE]

what does drop=FALSE do? Thanks.

On 1/14/2023 8:48 PM, Steven Yen wrote:
> Thanks to all. Very helpful.
>
> Steven from iPhone
>
>> On Jan 14, 2023, at 3:08 PM, Andrew Simmons <akwsimmo using 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 using 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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