There are two ways an empty NumPy array can be created: numpy.zeros
and numpy.empty
. Both of these methods differ slightly, as shown below:
The syntax for using numpy.zeros
and numpy.empty
is shown below:
numpy.zeros(shape, dtype=float, order='C')
numpy.empty(shape, dtype=float, order='C')
# Shape -> Shape of the new array, e.g., (2, 3) or 2.
# dtype -> The desired data-type for the array,e.g., numpy.int8. Default is numpy.float64. This parameter is optional.
# order -> Indicates whether multi-dimensional data should be stored in row-major (C-style) or column-major (Fortran-style) order in memory. This parameter is optional.
Consider the code snippet below that demonstrates how to use numpy.zeros
to create an empty NumPy array:
import numpy as npmyArr = np.zeros((2,3))print(myArr)
The code snippet below demonstrates how to use numpy.empty
to create an empty NumPy array:
import numpy as npmyArr = np.empty((2,3))print(myArr)
numpy.empty
, unlikenumpy.zeros
, does not set the array values to zero and, therefore, may 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.