numpy.empty(shape, dtype=float, order='C', *, like=None)

Return a new array of given shape and type, without initializing entries.

shapeint or tuple of int

Shape of the empty array, e.g., (2, 3) or 2.

dtypedata-type, optional

Desired output data-type for the array, e.g, numpy.int8. Default is numpy.float64.

order{‘C’, ‘F’}, optional, default: ‘C’

Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.


Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.


The like keyword is an experimental feature pending on acceptance of NEP 35.

New in version 1.20.0.


Array of uninitialized (arbitrary) data of the given shape, dtype, and order. Object arrays will be initialized to None.

See also


Return an empty array with shape and type of input.


Return a new array setting values to one.


Return a new array setting values to zero.


Return a new array of given shape filled with value.


empty, unlike zeros, does not set the array values to zero, and may therefore be marginally faster. On the other hand, it requires the user to manually set all the values in the array, and should be used with caution.


>>> np.empty([2, 2])
array([[ -9.74499359e+001,   6.69583040e-309],
       [  2.13182611e-314,   3.06959433e-309]])         #uninitialized
>>> np.empty([2, 2], dtype=int)
array([[-1073741821, -1067949133],
       [  496041986,    19249760]])                     #uninitialized