How to convert a Numpy 2D array with object dtype to a regular 2D array of floats

Question

As part of broader program I am working on, I ended up with object arrays with strings, 3D coordinates and etc all mixed. I know object arrays might not be very favorite in

Answer 1

You may want to use structured array, so that when you need to access the names and the values independently you can easily do so. In this example, there are two data points:

x = zeros(2, dtype=[('name','S10'), ('value','f4',(3,))])
x[0][0]='item1'
x[1][0]='item2'
y1=x['name']
y2=x['value']

the result:

>>> y1
array(['item1', 'item2'], 
      dtype='|S10')
>>> y2
array([[ 0.,  0.,  0.],
       [ 0.,  0.,  0.]], dtype=float32)

See more details: http://docs.scipy.org/doc/numpy/user/basics.rec.html