Adding a field to a structured numpy array

Question

What is the cleanest way to add a field to a structured numpy array? Can it be done destructively, or is it necessary to create a new array and copy over the existing fields? Are the contents of each field stored contiguously in memory so that such copying can be done efficiently?

score 20 · Accepted Answer · edited Jan 29 '14 at 19:56

20

If you're using numpy 1.3, there's also numpy.lib.recfunctions.append_fields().

For many installations, you'll need to import numpy.lib.recfunctions to access this. import numpy will not allow one to see the numpy.lib.recfunctions

edited Jan 29 '14 at 19:56

Roland

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answered Jul 30 '09 at 17:18

DopplerShift

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Note that `append_fields` creates an array of type 'numpy.ma.core.MaskedArray'. If you want an array of type 'numpy.ndarray', you can convert the result with `df = np.array(df)`. – nico Jul 17 '23 at 12:03

score 8 · Answer 2 · edited Sep 24 '15 at 09:10

import numpy

def add_field(a, descr):
    """Return a new array that is like "a", but has additional fields.

    Arguments:
      a     -- a structured numpy array
      descr -- a numpy type description of the new fields

    The contents of "a" are copied over to the appropriate fields in
    the new array, whereas the new fields are uninitialized.  The
    arguments are not modified.

    >>> sa = numpy.array([(1, 'Foo'), (2, 'Bar')], \
                         dtype=[('id', int), ('name', 'S3')])
    >>> sa.dtype.descr == numpy.dtype([('id', int), ('name', 'S3')])
    True
    >>> sb = add_field(sa, [('score', float)])
    >>> sb.dtype.descr == numpy.dtype([('id', int), ('name', 'S3'), \
                                       ('score', float)])
    True
    >>> numpy.all(sa['id'] == sb['id'])
    True
    >>> numpy.all(sa['name'] == sb['name'])
    True
    """
    if a.dtype.fields is None:
        raise ValueError, "`A' must be a structured numpy array"
    b = numpy.empty(a.shape, dtype=a.dtype.descr + descr)
    for name in a.dtype.names:
        b[name] = a[name]
    return b

Can this be amended to avoid duplicating memory? (see [this question](http://stackoverflow.com/q/39965994/974555)) — gerrit, Oct 10 '16 at 20:21

Adding a field to a structured numpy array

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