On Wed, Sep 22, 2010 at 2:04 AM, keekychen.shared <keekychen.shared@gmail.com> wrote:

 Dear All,

See below code pls,

import sicpy import numpy as np

x = np.zeros((2,),dtype=('i4,f4,a10')) x[:] = [(1,2.,'Hello'),(2,3.,"World")]

y = x['f2'] #array(['Hello', 'World'],      dtype='|S10')

x['f2'] = y x #array([(1, 2.0, 'Hello'), (2, 3.0, 'World')],      dtype=[('f0', '<i4'), ('f1', '<f4'), ('f2', '|S10')])

y = y.astype('object') y array([Hello, World], dtype=object)

x['f2'] = y array([(1, 2.0, 'HellWorld'), (2, 3.0, '\x00\x00\x00\x00\x00\x00\x18')],      dtype=[('f0', '<i4'), ('f1', '<f4'), ('f2', '|S10')])

##here comes the problem: the f2 col type has not been changed and the data is not I wanted... ----------------------------------------------------------------------------

here is why I need using this: suppose I have a datasource, csv, sql based db or what ever look like this:

1, 2.0, 'Hello' 2, 3.0, 'World' 3, 2.0, 'other string'

I want to read them to a numpy array and process it's columns, it has no problem for processing the float or int type but string. After reading the manual and found the object dtype may store variable string then I want to exact the string col into an new array, try to process it then store back to the numpy "matrix" then store it back to the data source.

May I know how I can do that? I do not care performance now.

I *guess* that you can do this by changing only the type of the string column to object dt = np.dtype([('f0', '<i4'), ('f1', '<f4'), ('f2', object)])

...

...

x = np.zeros((2,),dtype=('i4,f4,O')) x[:] = [(1,2.,'Hello'),(2,3.,"World")] x array([(1, 2.0, 'Hello'), (2, 3.0, 'World')], dtype=[('f0', '<i4'), ('f1', '<f4'), ('f2', '|O4')]) x['f2'] = 'hellooooooooooooooooo' x array([(1, 2.0, 'hellooooooooooooooooo'), (2, 3.0, 'hellooooooooooooooooo')], dtype=[('f0', '<i4'), ('f1', '<f4'), ('f2', '|O4')])

Josef

Thanks for any hints

Rgs,

KC

_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion