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.. _routines.rec:
Record Arrays (:mod:`numpy.rec`)
================================
.. currentmodule:: numpy.rec
.. module:: numpy.rec
Record arrays expose the fields of structured arrays as properties.
Most commonly, ndarrays contain elements of a single type, e.g. floats,
integers, bools etc. However, it is possible for elements to be combinations
of these using structured types, such as:
.. try_examples::
>>> import numpy as np
>>> a = np.array([(1, 2.0), (1, 2.0)],
... dtype=[('x', np.int64), ('y', np.float64)])
>>> a
array([(1, 2.), (1, 2.)], dtype=[('x', '<i8'), ('y', '<f8')])
Here, each element consists of two fields: x (and int), and y (a float).
This is known as a structured array. The different fields are analogous
to columns in a spread-sheet. The different fields can be accessed as
one would a dictionary:
>>> a['x']
array([1, 1])
>>> a['y']
array([2., 2.])
Record arrays allow us to access fields as properties:
>>> ar = np.rec.array(a)
>>> ar.x
array([1, 1])
>>> ar.y
array([2., 2.])
Functions
---------
.. autosummary::
:toctree: generated/
array
find_duplicate
format_parser
fromarrays
fromfile
fromrecords
fromstring
Also, the `numpy.recarray` class and the `numpy.record` scalar dtype are present
in this namespace.
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