Python numpy empty_like method example

How to use empty_like in numpy with example:

empty_like is a method of NumPy that returns a new array with same shape and type as the provided array. In this post, I will show you how to use empty_like method with examples.

Definition of empty_like:

empty_like is defined as like below:

empty_like(p, dtype=None, order='K', subok=True, shape=None)

Here,

p is the prototype, the data-type and shape define the same attributes of the returning array. It is an array_like parameter.
dtype is a data-type optional parameter. It is used to override the data type of the result array.
order is an optional parameter that overrides the memory layout of the result array. It can be ‘C’, ‘F’, ‘A’ or ‘K’.
subok is an optional boolean value. For False, the result array will be base-class array. If True, it will use the sub class type of prototype.
shape is an optional value, it can be int or sequence of ints. It overrides the shape of the result array.

Example program:

Let’s try this with an example:

import numpy as np

given_arr = ([1,2],[3,4], [5,6])

print(np.empty_like(given_arr))

It will print one output as like below:

[[-4611686018427387904 -4611686018427387904]
 [ 4616981938510757898  4613349226564724111]
 [-4611686018427387904 -4611686018427387904]]

It created an uninitialized array.

Each time you run this program, it will create one different uninitialized array.

With a different dtype:

Let’s change the data type of the returned array to string:

import numpy as np

given_arr = ([1,2],[3,4], [5,6])

print(np.empty_like(given_arr, dtype=str))

It will give:

[['' '']
 ['' '']
 ['' '']]

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Python numpy empty_like method example

How to use empty_like in numpy with example:

Definition of empty_like:

Example program:

With a different dtype:

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