No, in your solution you simply merge the files into two long columns. What
I want is to create a table of data say those are my tables:
table 1:
wavelength absorption
330 0.65
331 0.68
332 0.70
333 0.69
334 0.60
table 2:
wavelength absorption
330 0.45
331 0.49
332 0.52
333 0.50
334 0.48
Notice that the wavelength columns are the same so I can unite the tables
into one:
wavelength absorption1 absorption1
330 0.65 0.45
331 0.68 0.49
332 0.70 0.52
333 0.69 0.50
334 0.60 0.48
On Sun, Nov 1, 2009 at 4:05 PM, MaxTheMouse <maxthemo...@googlemail.com>wrote:
>
>
>
> On Nov 1, 7:20 am, Yotam Avital <yota...@gmail.com> wrote:
> > This is not what I want.
> >
> > sage: !cat file1
> > 1 3
> > 2 0
> > 3 10
> > sage: !cat file2
> > 1 29
> > 2 21
> > 3 -19
> > sage: a=numpy.loadtxt('file1')
> > sage: b=numpy.loadtxt('file2')
> >
> > sage: out = a <some magic function> b
> >
> > sage: out
> > array([[ 1., 3. ,29],
> > [ 2., 0. ,21],
> > [ 3., 10. ,-19]])
> >
> > On Sun, Nov 1, 2009 at 3:02 AM, Jason Grout <jason-s...@creativetrax.com
> >wrote:
> >
> >
> >
>
> You mean like this?
>
> sage: !cat file1 file2
> 1 3
> 2 0
> 3 10
> 1 29
> 2 21
> 3 -19
> sage: !cat file1 file2 > file3
> sage: a=numpy.loadtxt('file3')
> sage: print a
> [[ 1. 3.]
> [ 2. 0.]
> [ 3. 10.]
> [ 1. 29.]
> [ 2. 21.]
> [ 3. -19.]]
>
> Cheers ~ Adam
> >
>
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