Hi,
This is the input data frame:
###
df.1 = read.table(header=T,text=
id gender WMC_alcohol WMC_caffeine WMC_no.drug RT_alcohol RT_caffeine
RT_no.drug
1 1 female 3.7 3.7 3.9 488 236 371
2 2 female 6.4 7.3 7.9 607 376 349
3 3 female 4.6 7.4 7.3 643 226
I see your desired output has rather fewer data than the input data frame.
Instead of making us pore over a bunch of numbers, can you explain exactly
what filtering you wish to do to get the specific subset
of {male/female} {alcohol/caffeine} you're trying to get?
BHM wrote
Hi,
This is
On Nov 29, 2013, at 9:42 AM, Burhan ul haq wrote:
Hi,
This is the input data frame:
###
df.1 = read.table(header=T,text=
id gender WMC_alcohol WMC_caffeine WMC_no.drug RT_alcohol RT_caffeine
RT_no.drug
1 1 female 3.7 3.7 3.9 488 236 371
2 2
Hi,
First, a big thanks to all those who replied.
I am including all the replies in one email for easier reference later:
# Input from David
#
reshape(df.1, idvar=1:2, sep=_, direction=long,
varying=names(df.1)[3:8])
#
# Input from Dennis
#
dfr1 - reshape(df.1, idvar = c(id, gender),
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