Try this. The last function removes everything but the
last part, i.e. the part after the -. Then we order the
columns, except the first column, by their last part
and finally split the result by the last part of the ID.
This gives a list of data frames, two in this case:
> last <- function(x) sub(".*-", "", x)
> split(DF[-1][order(last(names(DF)[-1]))], last(DF[[1]]))
$A
S1-a S2-a S1-b S2-b
1 1 3 2 4
3 9 11 10 12
$B
S1-a S2-a S1-b S2-b
2 5 7 6 8
4 13 15 14 16
On Sat, Jul 25, 2009 at 5:14 AM, Junqian Gordon Xu<xjq...@gmail.com> wrote:
> You're right. Using read.csv, the first column is a factor, not string (or
> should I use str?). The following is a 2x2 version of the data frame after
> read.csv
>
> ID S1-a S1-b S2-a S2-b
> 1 001-A 1 2 3 4
> 2 001-B 5 6 7 8
> 3 002-A 9 10 11 12
> 4 002-B 13 14 15 16
>
> the resulting data frame I want is (whether or not to retain the factor ID
> info in the resulting data frame is not important)
>
> S1-a S2-a S1-b S2-b
> 1 1 3 1 2 4
> 2 9 11 2 10 12
>
> S1-a S2-a S1-b S2-b
> 1 5 7 1 6 8
> 2 13 15 2 14 16
>
> Hope it's clearer.
>
> On 07/25/2009 03:37 AM, jim holtman wrote:
>>
>> Are you using 'read.csv'? At least include an 'str' of the object you
>> are wanting to convert so that we know the structure of it, since we
>> can not guess at what it is.
>>
>> On Sat, Jul 25, 2009 at 4:32 AM, Junqian Gordon Xu<xjq...@gmail.com>
>> wrote:
>>>
>>> Actually when I read the spreadsheet from cvs file, "S1-[abcd]" are the
>>> header and "T1-[abcd]" are the strings in first column of the data frame.
>>>
>>> Gordon
>>>
>>> On 07/25/2009 03:13 AM, jim holtman wrote:
>>>>
>>>> It it not entirely clear what the format of your data is. If you have
>>>> a dataframe that you would like to separate into several different one
>>>> based on the value in a column, then something like this will work:
>>>>
>>>> df.list <- split(yourDF, yourDF$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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