[R] data$variable=factor(....) <NA> <NA> <NA>

[Rui Barradas]

Hello,

Just to add that the op's data$gender has 4 levels, not just 2. So it 
would be better to remove the leading spaces from " F" and " M", by 
using ?sub or ?gsub.

Hope this helps,

Rui Barradas

Em 11-07-2015 21:19, Jeff Newmiller escreveu:
> Well, you can help yourself on this list if you stop letting your email
> client determine the format (HTML in this case) that you use since that
> format gets corrupted on this mailing list leading to frequent
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> format.
>
> If you go back to your first line and look at str(data), you will see
> that read.csv automatically converted the gender column to a factor for
> you. In your later attempt to convert it you thought it would draw on
> the underlying integer values when it "acts" like character data so none
> of the specified levels ("1" or "2") were found in it.
>
> If you want to control the levels used in the factor (as I usually
> prefer to do) then use either the as.is=TRUE or stringsAsFactors=FALSE
> parameter to the read.csv function to make sure no factors are
> automatically created. Then specify character values for your levels
> instead of second-guessing R.
>
> Note that there is a bit of an art to reading the help files, as in:
>
> ?read.csv
>
> that you should start to practice. When you do read that help file, you
> will find that there are a lot of parameters to the "read.table"
> function, and rather fewer specified for the read.csv definition. The
> reason is that the read.csv function simply calls the read.table
> function with certain parameters forced to specific values. You can set
> any of the other parameters that read.table expects in your call to
> read.csv and they will be passed on to read.table.
>
> Oh, and one other thing: functions are quite similar to data objects in
> R, and there is a function called "data" that comes with R. While
> defining your own object called "data" works in this case, it is good
> practice to learn to not re-use object names like that since it can make
> reading your code confusing at the very least.
>
> On Sat, 11 Jul 2015, Dagmar Jurankov? wrote:
>
>> Hello everybody, I have a problem with R.
>>
>>
>> I uploaded a questionnaire saved as csv into R and I tried to test
>> independence between two variables.
>>
>>
>>
>> data <- read.csv("C:/Users/Me/Desktop/data.csv")>   View(data)> df =
>> read.csv("C:/Users/Me/Desktop/data.csv")> ls()
>> [1] "df"     "data"> attributes(data$gender)
>> $levels
>> [1] " F" " M" "F"  "M"
>>
>> $class
>> [1] "factor"
>>
>>
>> I changed my variable "gender" into a factor using:
>>
>>
>> data$gender=factor(data$gender, levels=c(1:2), labels= c( "F", "M"),
>> exclude= NA, nmax= NA).
>>
>>
>> Then I wrote data$gender and the only thing i got was:
>>
>>
>> [1] <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
>> <NA> <NA> <NA> <NA> <NA> <NA>
>>
>> [21] <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
>> <NA>
>> <NA> <NA> <NA> <NA> <NA> <NA>
>>
>> [41] <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
>> <NA>
>> <NA> <NA> <NA> <NA> <NA> <NA>
>>
>> [61] <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
>>
>> Levels: F M
>>
>>
>> Does anybody know why?
>>
>>
>> -My csv doc in the column gender is filled out properly. (M=Male, F=
>> Female)
>>
>> -My imported dataset in R is complete (all values)
>>
>>
>> ! I have done this with a different excel document and it worked out
>> without any problems. I am really clueless. I cant go further and compare
>> the variables and do t-tests without this working.
>>
>>
>> Could someone please help me out?
>>
>> Thank you.
>>
>>     [[alternative HTML version deleted]]
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>
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> ______________________________________________
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> and provide commented, minimal, self-contained, reproducible code.