- 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 of given shape filled with zeros and also set the desired output in Numpy

To return a new array of given shape and type, filled with zeros, use the **np.zeros() **method in Python
Numpy. The 1st parameter sets the shape of the array. The 2nd parameter is the desired data-type
for the array.

The dtype is the desired data-type for the array, e.g., numpy.int8. Default is numpy.float64. The order parameter suggests whether to store multi-dimensional data in row-major (C-style) or columnmajor (Fortran-style) order in memory. The like parameter is the reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.

## Steps

At first, import the required library −

import numpy as np

To return a new array of given shape and type, filled with zeros, use the np.zeros() method in Python Numpy. The 2nd parameter is the desired data-type for the array −

arr = np.zeros((6,6), dtype = int)

Display the array −

print("Array...

",arr)

Get the datatype −

print("

Array datatype...

",arr.dtype)

Get the dimensions of the Array: −

print("

Array Dimensions...

",arr.ndim)

Get the shape of the array −

print("

Our Array Shape...

",arr.shape)

Get the number of elements of the Array −

print("

Number of elements in the Array...

",arr.size)

## Example

import numpy as np import numpy.ma as ma # To return a new array of given shape and type, filled with zeros, use the np.zeros() method in Python Numpy # The 1st parameter sets the shape of the array # The 2nd parameter is the desired data-type for the array arr = np.zeros((6,6), dtype = int) # Displaying the array print("Array...

",arr) # Get the datatype print("

Array datatype...

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

Array Dimensions...

",arr.ndim) # Get the shape of the Array print("

Our Array Shape...

",arr.shape) # Get the number of elements of the Array print("

Number of elements in the Array...

",arr.size)

## Output

Array... [[0 0 0 0 0 0] [0 0 0 0 0 0] [0 0 0 0 0 0] [0 0 0 0 0 0] [0 0 0 0 0 0] [0 0 0 0 0 0]] Array datatype... int64 Array Dimensions... 2 Our Array Shape... (6, 6) Number of elements in the Array... 36

- Related Articles
- Return a new array of given shape filled with zeros and also set the desired datatype in Numpy
- Return a new array of given shape filled with ones and also set the desired data-type in Numpy
- Return a new array of given shape filled with zeros in Numpy
- Return a new array of given shape filled with ones in Numpy
- Return a new array of given shape filled with a fill value and a different output type in Numpy
- Return a new array of a given shape filled with ones in Numpy
- Return a new array of given shape and type, filled with array-like 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 filled with ones but with different datatype in Numpy
- Return an array of zeros with the same shape and type as a given array in Numpy
- 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 in Numpy
- Return a new array of given shape without initializing entries in Numpy
- Return a new array of given shape and type without initializing entries in Numpy
- Return a new array with the same shape and type as a given array and change the order in Numpy