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 <[email protected]> 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 <[email protected]> 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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