.. _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.