- Trending Categories
- Data Structure
- Networking
- RDBMS
- Operating System
- Java
- MS Excel
- iOS
- HTML
- CSS
- Android
- Python
- C Programming
- C++
- C#
- MongoDB
- MySQL
- Javascript
- PHP
- Physics
- Chemistry
- Biology
- Mathematics
- English
- Economics
- Psychology
- Social Studies
- Fashion Studies
- Legal Studies

- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who

# Return a new array with the same shape and type as a given array and change the order in Numpy

To return a new array with the same shape and type as a given array, use the **numpy.empty_like()** method in Python Numpy. It returns the array of uninitialized (arbitrary) data with the same shape and type as prototype. The 1st parameter here is the shape and data-type of prototype(array-like) that define these same attributes of the returned array. We have set the order using the "**order**" parameter.

The order overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if prototype is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of prototype as closely as possible. The shape overrides the shape of the result. If order=’K’ and the number of dimensions is unchanged, will try to keep order, otherwise, order=’C’ is implied. The overrides parameter overrides the data type of the result.

The subok parameter, if True, then the newly created array will use the sub-class type of prototype, otherwise it will be a base-class array. Defaults to True.

## Steps

At first, import the required library −

import numpy as np

Creating a numpy Three-Dimensional array using the array() method. We have added elements of int type −

arr = np.array([[[5,10],[15,20]],[[25,30],[35,40]],[[50,60],[70,80]]])

Display the array −

print("Array...

",arr)

Get the type of the array −

print("

Array type...

", arr.dtype)

Get the dimensions of the Array −

print("

Array Dimensions...

", arr.ndim)

To return a new array with the same shape and type as a given array, use the numpy.empty_like() method in Python Numpy. We have set the order using the "order" parameter −

newArr = np.empty_like(arr, order = 'C') print("

New Array..

", newArr)

Get the type of the new array −

print("

New Array type...

", newArr.dtype)

Get the dimensions of the new array −

print("

New Array Dimensions...

", newArr.ndim)

## Example

import numpy as np # Creating a numpy Three-Dimensional array using the array() method # We have added elements of int type arr = np.array([ [[5,10],[15,20]], [[25,30],[35,40]], [[50,60],[70,80]] ]) # Display the array print("Array...

",arr) # Get the type of the array print("

Array type...

", arr.dtype) # Get the dimensions of the Array print("

Array Dimensions...

", arr.ndim) # To return a new array with the same shape and type as a given array, use the numpy.empty_like() method in Python Numpy # It returns the array of uninitialized (arbitrary) data with the same shape and type as prototype. # The 1st parameter here is the shape and data-type of prototype(array-like) that define these same attributes of the returned array. # We have set the order using the "order" parameter newArr = np.empty_like(arr, order = 'C') print("

New Array..

", newArr) # Get the type of the new array print("

New Array type...

", newArr.dtype) # Get the dimensions of the new array print("

New Array Dimensions...

", newArr.ndim)

## Output

Array... [[[ 5 10] [15 20]] [[25 30] [35 40]] [[50 60] [70 80]]] Array type... int64 Array Dimensions... 3 New Array.. [[[ 0 0] [ 0 0]] [[140556668570992 140556671038576] [140556668571056 140556668441520]] [[140556668441712 140556668441776] [140556668441840 140556668442416]]] New Array type... int64 New Array Dimensions... 3

- Related Articles
- Return a new array with the same shape and type as given array in Numpy
- Return a new array with the same shape and type as a given array and change the order to K style in Numpy
- Return a new array with the same shape and type as a given array and change the order to C style in Numpy
- Return a new array with the same shape and type as a given array in Numpy
- Return a new array with the same shape as a given array but change the default type in Numpy
- Return a full array with the same shape and type as a given array in Numpy
- Return an array of ones with the same shape and type as a given array in Numpy
- Return an array of zeros with the same shape and type as a given array in Numpy
- Return a new array of given shape and type, filled with array-like in Numpy
- Return a new array of given shape without initializing entries and change the default type in Numpy
- Return an array of zeroes with the same shape as a given array but with a different type in Numpy
- Return a new array of given shape and type filled with a fill value in Numpy
- Return a new array of given shape and type without initializing entries in Numpy
- Return a masked array containing the same data but with a new shape viewed as row-major order in Numpy
- Return a masked array containing the same data but with a new shape viewed as column-major order in Numpy