Re: [Numpy-discussion] recarray

[Francesc A. <fa...@ca...>]

A Divendres 15 Setembre 2006 15:57, Robert Kern va escriure:
> Lionel Roubeyrie wrote:
> > Hi all,
> > I try to use recarray with rec.fromrecords on time-series, datas come
> > from a file where they are stored in csv format, with after each data
> > colum there is one column meanning the state of the data, and the first
> > column is for dates. Then, is it possible to directly transform column =
of
> > strings to a integer one (or datetime one), and to remove a not used
> > column?
>
> When I import CSV files into record arrays, I usually read in all of the
> data and transpose the list of rows to get a list of columns. Then I can
> remove columns and transform them _en masse_, usually with map().

Another possibility is to play with columns directly from the initial=20
recarray. The next is an example:

In [101]: ra=3Dnumpy.rec.array("1"*36, dtype=3D"a4,i4,f4", shape=3D3)
In [102]: ra
Out[102]:
recarray([('1111', 825307441, 2.5784852031307537e-09),
       ('1111', 825307441, 2.5784852031307537e-09),
       ('1111', 825307441, 2.5784852031307537e-09)],
      dtype=3D[('f0', '|S4'), ('f1', '<i4'), ('f2', '<f4')])
In [103]: rb=3Dnumpy.rec.fromarrays([numpy.array(ra['f0'], 'i4'),ra['f2']],=
=20
names=3D'f0,f1')
In [104]: rb
Out[104]:
recarray([(1111, 2.5784852031307537e-09), (1111, 2.5784852031307537e-09),
       (1111, 2.5784852031307537e-09)],
      dtype=3D[('f0', '<i4'), ('f1', '<f4')])

where ra is the original recarray and rb is a derived one where its first=20
column is the original from ra, but converted to integers ('i4'), and the=20
second it's the third column from ra (so the second column from ra has been=
=20
stripped out from rb).

HTH,

=2D-=20
>0,0<   Francesc Altet =A0 =A0 http://www.carabos.com/
V   V   C=E1rabos Coop. V. =A0=A0Enjoy Data
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