# Return an array of zeros with the same shape and type as a given array in Numpy

To return an array of zeros with the same shape and type as a given array, use the numpy.zeroes_like() method in Python Numpy. The 1st parameter here is the shape and data-type of array-like that define these same attributes of the returned array.

The dtype overrides the data type of the result. The order parameter overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if a is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of a as closely as possible. The subok parameter, if True, then the newly created array will use the sub-class type of a, otherwise it will be a base-class array. Defaults to True.

## Steps

At first, import the required library −

import numpy as np

Create a new array using the numpy.array() method in Python Numpy −

arr = np.array([[35, 56, 66], [88, 73, 98]])


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 an array of zeros with the same shape and type as a given array, use the numpy.zeroes_like() method in Python Numpy. The 1st parameter here is the shape and data-type of array-like that define these same attributes of the returned array −

newArr = np.zeros_like(arr)
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

# Create a new array using the numpy.array() method in Python Numpy
arr = np.array([[35, 56, 66], [88, 73, 98]])

# 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 an array of zeros with the same shape and type as a given array, use the numpy.zeroes_like() method in Python Numpy
# The 1st parameter here is the shape and data-type of array-like that define these same attributes of the returned array.
newArr = np.zeros_like(arr)
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...
[[35 56 66]
[88 73 98]]

Array type...
int64

Array Dimensions...
2

New Array..
[[0 0 0]
[0 0 0]]

New Array type...
int64

New Array Dimensions...
2

Updated on: 10-Feb-2022

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