numpy.empty¶
-
numpy.
empty
(shape, dtype=float, order='C')¶ Return a new array of given shape and type, without initializing entries.
Parameters: - shape : int or tuple of int
Shape of the empty array, e.g.,
(2, 3)
or2
.- dtype : data-type, optional
Desired output data-type for the array, e.g,
numpy.int8
. Default isnumpy.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.
Returns: - out : ndarray
Array of uninitialized (arbitrary) data of the given shape, dtype, and order. Object arrays will be initialized to None.
See also
empty_like
- Return an empty array with shape and type of input.
ones
- Return a new array setting values to one.
zeros
- Return a new array setting values to zero.
full
- Return a new array of given shape filled with value.
Notes
empty
, unlikezeros
, 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.Examples
>>> np.empty([2, 2]) array([[ -9.74499359e+001, 6.69583040e-309], [ 2.13182611e-314, 3.06959433e-309]]) #random
>>> np.empty([2, 2], dtype=int) array([[-1073741821, -1067949133], [ 496041986, 19249760]]) #random