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
misunderstandings. Learn how to make your email client send plain text
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.
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