On 11/28/2016 1:06 AM, jean-philippe wrote:
dear all,
I have a dataframe of 500 rows and 4004 columns that I would like to
reshape to a dataframe of 500500 rows and 4 columns. That is from this
dataframe:
V1 V2 V3 V4 ... V4001 V4002 V4003 V4004
1 2 3 4 ... 4001 4002 4003 4004
1 2 3 4 ... 4001 4002 4003 4004
1 2 3 4 ... 4001 4002 4003 4004
... ... ... ... ... ... ... ... ... ... ... ... ...
1 2 3 4 ... 4001 4002 4003 4004
I would like :
V1 V2 V3 V4
1 2 3 4
1 2 3 4
1 2 3 4
1 2 3 4
... ... ... ... ... ... ... ... ...
4001 4002 4003 4004
4001 4002 4003 4004
4001 4002 4003 4004
... ... ... ... ...
4001 4002 4003 4004
I tried already to use y=matrix(as.matrix(dataGaus[[1]]),500500,4)
(where dataGaus is my dataframe) but it doesn't give the expected
result. I tried also to use reshape but I can't manage to use it to
reproduce the result (and I have been through lot of posts on
StackOverflow and on the net). In python, we can do this with a simple
command numpy.array(dataGaus[[1]]).reshape(-1,4). For some reasons, I am
doing my analysis in R, and I would like to know if there is a function
which does the same thing as the reshape(-1,4) of numpy in Python?
Thanks in advance, best
Jean-Philippe
I don't know about efficiency, but it looks like you could do something
like this:
y <- t(matrix(t(dataGaus),4))
Maybe someone will come along with something better,
Dan
--
Daniel Nordlund
Port Townsend, WA USA
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