[Numpy-discussion] ndarray from column data
Robert
kxroberto@googlemail....
Thu Jul 2 14:00:19 CDT 2009
Elaine Angelino wrote:
> Hi there --
>
> Is there a fast way to make a numpy ndarray from column data?
>
> For example, suppose I want to make an ndarray with 2 rows and 3 columns
> of different data types based on the following column data:
>
> C0 = [1,2]
> C1 = ['a','b']
> C2 = [3.3,4.4]
>
> I could create an empty ndarray and fill the columns one by one:
>
> X = numpy.core.ndarray((2,), dtype='<i4,|S1,<f8')
> X['f0'] = C0
> X['f1'] = C1
> X['f2'] = C2
>
> The result is the same as:
>
> X = numpy.array([(1,'a',3.3), (2,'b',4.4)], dtype='<i4,|S1,<f8')
>
> but I would like to make X directly from the column data.
>
> [ I know that numpy.core.records.fromarrays will produce a numpy
> recarray from column data, but this of course is a recarray and not a
> ndarray! For ex:
>
> X = numpy.numpy.core.records.fromarrays([C0,C1,C2]) ]
>
> Thanks for any help,
>
> Elaine
>
>>> np.array(zip(C0,C1,C2), dtype='<i4,|S1,<f8')
array([(1, 'a', 3.2999999999999998), (2, 'b', 4.4000000000000004)],
dtype=[('f0', '<i4'), ('f1', '|S1'), ('f2', '<f8')])
Well, such thing is never a real 2D ndarray with real "columns"
anyway, which you can access like X[row,col], but a 1D array of
tuples.
for iso-type data -> 2D there is
>>> np.column_stack((C0,C1,C2))
array([['1', 'a', '3.3'],
['2', 'b', '4.4']],
dtype='|S8')
Robert
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