This worked! Thank you!
-----Original Message-----
From: Rui Barradas [mailto:ruipbarra...@sapo.pt]
Sent: Thursday, June 4, 2020 2:49 PM
To: Ted Stankowich <theodore.stankow...@csulb.edu>; William Dunlap
<wdun...@tibco.com>
Cc: r-help@r-project.org
Subject: Re: [R] na.omit not omitting rows
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replying, opening links or attachments.
Hello,
If the problem is the "na.action" attribute, here are two ways of solving it.
First, an example data set.
set.seed(2020) # Make the example reproducible
phamComplBinomial <- sprintf("f%003d", 1:356)
is.na(UphamComplBinomial) <- sample(356, 37) DarkEum <- factor(sample(1:2, 356,
TRUE))
Protect1 <- data.frame(UphamComplBinomial = factor(UphamComplBinomial),
DarkEum)
1. Setting the attribute "na.action" to NULL removes it
Protect2 <- na.omit(Protect1)
attributes(Protect2)
attr(Protect2, "na.action") <- NULL
attributes(Protect2)
2. Use an index vector to subset the data
na <- is.na(Protect1$UphamComplBinomial)
Protect3 <- Protect1[!na, ]
The results are identical. But if you have more than one column with NA's, this
second way will be more complicated.
identical(Protect2, Protect3)
#[1] TRUE
Hope this helps,
Rui Barradas
Às 22:27 de 04/06/20, Ted Stankowich escreveu:
> Thanks, but no that doesn’t work. The na.omit attributes are still in
> the dataframe, which you can see in the str outputs from the post. The
> problem line is likely: - attr(*, "na.action")= 'omit' Named int
> [1:2] 2 3
>
> From: William Dunlap [mailto:wdun...@tibco.com]
> Sent: Thursday, June 4, 2020 12:39 PM
> To: Ted Stankowich <theodore.stankow...@csulb.edu>
> Cc: r-help@r-project.org
> Subject: Re: [R] na.omit not omitting rows
>
> CAUTION: This email was sent from an external source. Use caution when
> replying, opening links or attachments.
>
> Does droplevels() help?
>
>> d <- data.frame(size = factor(c("S","M","M","L","L"),
>> levels=c("S","M","L")), id=c(101,NA,NA,104,105))
>> str(d)
> 'data.frame': 5 obs. of 2 variables:
> $ size: Factor w/ 3 levels "S","M","L": 1 2 2 3 3
> $ id : num 101 NA NA 104 105
>> str(na.omit(d))
> 'data.frame': 3 obs. of 2 variables:
> $ size: Factor w/ 3 levels "S","M","L": 1 3 3
> $ id : num 101 104 105
> - attr(*, "na.action")= 'omit' Named int [1:2] 2 3
> ..- attr(*, "names")= chr [1:2] "2" "3"
>> str(droplevels(na.omit(d)))
> 'data.frame': 3 obs. of 2 variables:
> $ size: Factor w/ 2 levels "S","L": 1 2 2
> $ id : num 101 104 105
> - attr(*, "na.action")= 'omit' Named int [1:2] 2 3
> ..- attr(*, "names")= chr [1:2] "2" "3"
>
> Bill Dunlap
> TIBCO Software
> wdunlap tibco.com<http://tibco.com>
>
>
> On Thu, Jun 4, 2020 at 12:18 PM Ted Stankowich
> <theodore.stankow...@csulb.edu<mailto:theodore.stankow...@csulb.edu>> wrote:
> Hello! I'm trying to create a subset of a dataset and then remove all rows
> with NAs in them. Ultimately, I am running phylogenetic analyses with trees
> that require the tree tiplabels to match exactly with the rows in the
> dataframe. But when I use na.omit to delete the rows with NAs, there is still
> a trace of those omitted rows in the data.frame, which then causes an error
> in the phylogenetic analyses. Is there any way to completely scrub those
> omitted rows from the dataframe? The code is below. As you can see from the
> result of the final str(Protect1) line, there are attributes with the omitted
> features still in the dataframe (356 species names in the UphamComplBinomial
> factor, but only 319 observations). These traces are causing errors with the
> phylo analyses.
>
>> Protect1=as.data.frame(cbind(UphamComplBinomial, DarkEum, NoctCrep,
>> Shade)) #Create the dataframe with variables of interest from an
>> attached dataset row.names(Protect1)=Protect1$UphamComplBinomial
>> #assign species names as rownames
>> Protect1=as.data.frame(na.omit(Protect1)) #drop rows with missing
>> data
>> str(Protect1)
> 'data.frame': 319 obs. of 4 variables:
> $ UphamComplBinomial: Factor w/ 356 levels
> "Allenopithecus_nigroviridis_CERCOPITHECIDAE_PRIMATES",..: 1 2 3 4 5 8 9 10
> 11 12 ...
> $ DarkEum : Factor w/ 2 levels "0","1": 2 1 2 2 2 2 2 2 2 2 ...
> $ NoctCrep : Factor w/ 2 levels "0","1": 1 2 1 1 1 1 1 1 1 1 ...
> $ Shade : Factor w/ 59 levels "0.1","0.2","0.25",..: 10 58 53
> 17 49 52 52 39 39 41 ...
> - attr(*, "na.action")= 'omit' Named int 6 7 23 36 37 40 42 50 51 60 ...
> ..- attr(*, "names")= chr "Alouatta_macconnelli_ATELIDAE_PRIMATES"
> "Alouatta_nigerrima_ATELIDAE_PRIMATES" "Ateles_fusciceps_ATELIDAE_PRIMATES"
> "Callicebus_baptista_PITHECIIDAE_PRIMATES" ...
>
> Dr. Ted Stankowich
> Associate Professor
> Department of Biological Sciences
> California State University Long Beach Long Beach, CA 90840
> theodore.stankow...@csulb.edu<mailto:theodore.stankow...@csulb.edu><ma
> ilto:theodore.stankow...@csulb.edu<mailto:theodore.stankow...@csulb.ed
> u>>
> 562-985-4826
> http://www.csulb.edu/mammal-lab/
> @CSULBMammalLab
>
>
>
>
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>
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