numpy.column_stack with numeric and string arrays

Question

I have several arrays, some of them have float numbers and others have string characters, all the arrays have the same length. When I try to use numpy.column_stack in these arrays, this function convert to string the float numbers, for example:

a = np.array([3.4,3.4,6.4])
b = np.array(['holi','xlo','xlo'])

B = np.column_stack((a,b))

print B
>>> [['3.4' 'holi']
     ['3.4' 'xlo']
     ['3.4' 'xlo']

type(B[0,0])
>>> numpy.string

Why? It's possible to avoid it? Thanks a lot for your time.

Answer 1

The easiest structured array approach is with the rec.fromarrays function:

In [1411]: a=np.array([3.4,3.4,6.4]); b=np.array(['holi','xlo','xlo'])
In [1412]: B = np.rec.fromarrays([a,b],names=['a','b'])
In [1413]: B
Out[1413]: 
rec.array([(3.4, 'holi'), (3.4, 'xlo'), (6.4, 'xlo')], 
          dtype=[('a', '<f8'), ('b', '<U4')])
In [1414]: B['a']
Out[1414]: array([ 3.4,  3.4,  6.4])
In [1415]: B['b']
Out[1415]: 
array(['holi', 'xlo', 'xlo'], 
      dtype='<U4')

Check its docs for more parameters. But it basically constructs an empty array of the correct compound dtype, and copies your arrays to the respective fields.