[R] Row exclude

[Rui Barradas]

Hello,

Getting creative, here is another way with mapply.


regex <- list("[[:digit:]]", "[[:alpha:]]", "[[:alpha:]]")

i <- mapply(\(x, r) grepl(r, x), dat1, regex)
dat1[rowSums(i) == 0L, ]

#  Name Age Weight
#2   Bob   25       142
#3 Carol   24       120
#5  Katy   35       160


Hope this helps,

Rui Barradas


Às 06:30 de 29/01/2022, David Carlson via R-help escreveu:
> Given that you know which columns should be numeric and which should be
> character, finding characters in numeric columns or numbers in character
> columns is not difficult. Your data frame consists of three character
> columns so you can use regular expressions as Bert mentioned. First you
> should strip the whitespace out of your data:
>
> dat1 <-read.table(text="Name, Age, Weight
>    Alex,  20,  13X
>    Bob,  25,  142
>    Carol, 24,  120
>    John,  3BC,  175
>    Katy,  35,  160
>    Jack3, 34,  140",sep=",", header=TRUE, stringsAsFactors=FALSE,
> strip.white=TRUE)
>
> Now check to see if all of the fields are character as expected.
>
> sapply(dat1, typeof)
> #        Name         Age      Weight
> # "character" "character" "character"
>
> Now identify character variables containing numbers and numeric variables
> containing characters:
>
> BadName <- which(grepl("[[:digit:]]", dat1$Name))
> BadAge <- which(grepl("[[:alpha:]]", dat1$Age))
> BadWeight <- which(grepl("[[:alpha:]]", dat1$Weight))
>
> Next remove those rows:
>
> (dat2 <- dat1[-unique(c(BadName, BadAge, BadWeight)), ])
> #    Name Age Weight
> #  2   Bob  25    142
> #  3 Carol  24    120
> #  5  Katy  35    160
>
> You still need to convert Age and Weight to numeric, e.g. dat2$Age <-
> as.numeric(dat2$Age).
>
> David Carlson
>
>
> On Fri, Jan 28, 2022 at 11:59 PM Bert Gunter <bgunter.4567 using gmail.com> wrote:
>
>> As character 'polluted' entries will cause a column to be read in (via
>> read.table and relatives) as factor or character data, this sounds like a
>> job for regular expressions. If you are not familiar with this subject,
>> time to learn. And, yes, ZjQcmQRYFpfptBannerStart
>> This Message Is From an External Sender
>> This message came from outside your organization.
>> ZjQcmQRYFpfptBannerEnd
>>
>> As character 'polluted' entries will cause a column to be read in (via
>> read.table and relatives) as factor or character data, this sounds like a
>> job for regular expressions. If you are not familiar with this subject,
>> time to learn. And, yes, some heavy lifting will be required.
>> See ?regexp for a start maybe? Or the stringr package?
>>
>> Cheers,
>> Bert
>>
>>
>>
>>
>> On Fri, Jan 28, 2022, 7:08 PM Val <valkremk using gmail.com> wrote:
>>
>>> Hi All,
>>>
>>> I want to remove rows that contain a character string in an integer
>>> column or a digit in a character column.
>>>
>>> Sample data
>>>
>>> dat1 <-read.table(text="Name, Age, Weight
>>>   Alex,  20,  13X
>>>   Bob,   25,  142
>>>   Carol, 24,  120
>>>   John,  3BC,  175
>>>   Katy,  35,  160
>>>   Jack3, 34,  140",sep=",",header=TRUE,stringsAsFactors=F)
>>>
>>> If the Age/Weight column contains any character(s) then remove
>>> if the Name  column contains an digit then remove that row
>>> Desired output
>>>
>>>     Name   Age weight
>>> 1   Bob     25    142
>>> 2   Carol   24    120
>>> 3   Katy    35    160
>>>
>>> Thank you,
>>>
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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