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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