Check out this website for a couple examples of how to use transform()
and replace() - (look under recode):
http://www.ku.edu/~pauljohn/R/Rtips.html
-Andrea
>Hello,
>
>I have read through the manuals and can't seem to find an answer.
>
>I have a categorical, character variable that has hundreds of values.
I want
>to group the existing values of this variable into a new, derived
>(categorical) variable by applying conditions to the values in the
data.
>
>For example, suppose I have a data frame with variables: date, country,
x, y,
>and z.
>
>x,y,z are numeric and country is a 2-digit character string. I want to
create
>a new derived variable named "continent" that would also exist in the
data
>frame. The Continent variable would have values of "Asia", "Europe",
"North
>America", etc...
>
>How would this best be done for a large dataset (>10MB) ?
>I have tried many variations on following without success (note in a
real
>example I would have a longer list of countries and continent values):
>
>> mydata$continent <- mydata[ mydata$country==list('US','CA','MX'), ]
->
>> "North America"
>
>I have read about factors, but I am not sure how they apply here.
>
>Can anyone help me with the syntax? I am sure it is trivial and a
common
>thing to do.
>The ultimate goal is to compute percentages of x by continent.
>
>Thanks for any help in advance.
>
>-Avram
>
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