Are you using 'read.csv'?  At least include an 'str' of the object you
are wanting to convert so that we know the structure of it, since we
can not guess at what it is.

On Sat, Jul 25, 2009 at 4:32 AM, Junqian Gordon Xu<xjq...@gmail.com> wrote:
> Actually when I read the spreadsheet from cvs file, "S1-[abcd]" are the
> header and "T1-[abcd]" are the strings in first column of the data frame.
>
> Gordon
>
> On 07/25/2009 03:13 AM, jim holtman wrote:
>>
>> It it not entirely clear what the format of your data is. If you have
>> a dataframe that you would like to separate into several different one
>> based on the value in a column, then something like this will work:
>>
>> df.list <- split(yourDF, yourDF$column)
>>
>> This will create a list of dataframes, split according to the contents
>> of "column".
>>
>> On Fri, Jul 24, 2009 at 9:20 PM, Junqian Gordon Xu<xjq...@gmail.com>
>> wrote:
>>>
>>> I have a multidimensional data which looks like the following:
>>>
>>>      "S1-a" "S2-b" "S3-c" "S4-d" "S5-a" "S6-b" "S7-c" "S8-d"
>>> "T1-A"
>>> "T1-B"
>>> "T1-C"
>>> "T1-D"
>>> "T2-A"
>>> "T2-B"
>>> "T2-C"
>>> "T2-D"
>>>
>>> I read it from csv file and would like to have 16 separate data frames
>>> like
>>> this
>>>
>>>    "S1-a" "S2-a"     "S1-b" "S2-b"     "S1-c" "S2-c"    "S1-d" "S2-d"
>>> "T1-A"            "T1-A"            "T1-A"            "T1-A"
>>> "T2-A"            "T2-A"            "T2-A"            "T2-A"
>>>
>>>    "S1-b" "S2-b"   ...
>>> "T1-B"               ...
>>> "T1-B"               ...
>>>
>>> ...
>>> ...
>>>
>>> One way is to use loops to cycle through, but I think it's even simpler
>>> to
>>> use regex expression to separate them since "abcd" and "ABCD" are unique
>>> strings in the table. Does anybody have any pointer on how to do this?
>>>
>>> Thanks
>>> Gordon
>
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>



-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem that you are trying to solve?

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