How do you remove a column from a structured numpy array?

Question

I have another basic question, that I haven\'t been able to find the answer for, but it seems like something that should be easy to do.

Ok, imagine you have a structured

Answer 1

It's not quite a single function call, but the following shows one way to drop the i-th field:

In [67]: a
Out[67]: 
array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], 
      dtype=[('A', '

Wrapped up as a function:

def remove_field_num(a, i):
    names = list(a.dtype.names)
    new_names = names[:i] + names[i+1:]
    b = a[new_names]
    return b

It might be more natural to remove a given field name:

def remove_field_name(a, name):
    names = list(a.dtype.names)
    if name in names:
        names.remove(name)
    b = a[names]
    return b

Also, check out the drop_rec_fields function that is part of the mlab module of matplotlib.

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Update: See my answer at How to remove a column from a structured numpy array *without copying it*? for a method to create a view of subsets of the fields of a structured array without making a copy of the array.