×

numpy.zeros in Python

numpy.zeros in Python

The zeros() method of Python numpy class returns a new array of given shape and type, filled with zeros.

Syntax

numpy.zeros(shape, dtype=float, order='C')

Parameter

The numpy.zeros() method consists of three parameters, which are as follows:

shape : This parameter represents the shape of the new array.

order  : The order parameter can be either C_contiguous or F_contiguous. C order means that operating row-rise on the array will be slightly quicker

FORTRAN-contiguous order in memory (the first index varies the fastest). F order means that column-wise operations will be faster.

dtype : It is an optional parameter. It depicts the data type of returned array, and by default, it is a float.

Return

This method returns the array of zeros with the specified shape, order and datatype.

Example 1

# Python Programming giving an example for
# numpy.zeros() method
import numpy as numpy
obj1 = numpy.zeros(2, dtype = int)
print("Matrix : \n", obj1)
obj2 = numpy.zeros([2, 2], dtype = int)
print("\nMatrix : \n", obj2)  
obj3 = numpy.zeros([3, 3])
print("\nMatrix : \n", obj3)

Output

Original array :
[[0 1]
[2 3]
[4 5]
[6 7]
[8 9]]
Matrix :
[[ 1.  1.]
[ 1.  1.]
[ 1.  1.]
[ 1.  1.]
[ 1.  1.]]
Matrix :
[1 1 1 1 1 1 1 1]

Related Topics

numpy.atleast_2d() in Python

numpy.atleast_2d() in Python The numpy.atleast_2d() function converts the inputs as arrays with at least two dimensions. Syntax numpy.atleast_2d(*arys) Parameter arys1, arys2, … : This parameter represents one or more array-like sequences where the non-array inputs are converted...

1 minute read.

numpy.squeeze() in Python

numpy.squeeze() in Python The numpy.squeeze() function removes single-dimensional entries from the shape of an array. Syntax numpy.squeeze(a, axis=None) Parameter The numpy.squeeze() function has three parameters which are as follows: a: It represents the Input data. axis: This parameter signifies an int or...

1 minute read.

numpy.broadcast_to() in Python

numpy.broadcast_to() in Python The numpy.broadcast_to() function broadcasts an array to a new shape. Syntax numpy.broadcast_to(array, shape, subok=False) Parameter The numpy.broadcast_to() function has three parameters which are as follows:  array: This parameter represents the array to broadcast. shape: It signifies the shape...

1 minute read.

numpy.zeros in Python

numpy.zeros in Python The zeros() method of Python numpy class returns a new array of given shape and type, filled with zeros. Syntax numpy.zeros(shape, dtype=float, order='C') Parameter The numpy.zeros() method consists of three parameters, which are as...

1 minute read.

numpy.eye() in Python

numpy.eye() in Python: The eye() method of Python numpy class returns a 2-D array with ones on the diagonal and zeros elsewhere. Syntax numpy.eye(N, M=None, k=0, dtype=<class 'float'>, order='C') Parameters The numpy.eye()  method consists of five parameters, which...

1 minute read.

numpy.trim_zeros() in Python

numpy.trim_zeros() in Python The numpy.trim_zeros() trims the leading and/or trailing zeros from a 1-D array or sequence. Syntax numpy.trim_zeros(filt, trim='fb') Parameter The numpy.trim_zeros() function consists of two parameters, which are as follows: filt : This parameter represents the 1-D...

1 minute read.

numpy.empty() in Python

numpy.empty() in Python The empty() method of Python numpy class returns a new array of the specified shape and type, without initializing the entries. Syntax numpy.empty(shape, dtype=float, order='C') Parameters The numpy.empty method consists of three parameters, which...

1 minute read.

numpy.delete() in Python

numpy.delete() in Python The numpy.delete() function returns a new array with sub-arrays along an axis deleted. For 1-D array, this function returns those entries which are not returned by arr[obj]. Syntax numpy.delete(arr, obj, axis=None) Parameter arr: This parameter returns...

2 minutes read.

numpy.split() in Python

numpy.split() in Python The numpy.split() function splits an array into multiple sub-arrays. Syntax numpy.split(ary, indices_or_sections, axis=0) Parameter ary: This parameter represents the Array to be divided into sub-arrays. indices_or_sections : This parameter represents an int or an 1-D array. If indices_or_sections is an...

1 minute read.

numpy.diagflat() in Python

numpy.diagflat() in Python The diagflat() function of Python numpy class creates a two-dimensional array with the array_like input as a diagonal to the new output array. Syntax numpy.diagflat (a, k = 0) Parameter a :...

1 minute read.

numpy.swapaxes() in Python

numpy.swapaxes() in Python The numpy.swapaxes() function interchanges the two specified axes of the given array. Syntax numpy.swapaxes(a, axis1, axis2) Parameter The numpy.swapaxes() method consists of three parameters, which are as follows: a : This parameter represents the Input array. axis1 : It represents...

1 minute read.

Numpy.copy() in Python with Example

Numpy.copy() in Python The copy() function of Python numpy class returns an array copy for the given object. Syntax numpy.copy(a, order='K') Parameter a: It represent the array_like input data. order :  This parameter controls the memory layout of...

1 minute read.

numpy.ones() in Python

numpy.ones() in Python The ones() method of Python numpy class returns a new array of given shape and type, filled with ones. Syntax numpy.ones(shape, dtype=None, order='C') Parameter The numpy.ones() method consists of three parameters, which are as...

1 minute read.

numpy.concatenate() in Python

numpy.concatenate() in Python The numpy.concatenate() function joins a sequence of arrays along an existing axis. Syntax numpy.concatenate((a1, a2, ...), axis=0, out=None) Parameter a1, a2, … : This parameter represents the sequence of the array where they must have the same shape,...

1 minute read.

Numpy.asmatrix() in Python with Example

Numpy.asmatrix() in Python The asmatrix() function returns the specified input as a matrix. It does not make a copy if the input is already a matrix or an ndarray. Syntax numpy.asmatrix(data, dtype=None) Parameter data  :This parameter...

1 minute read.

Numpy Attributes

Numpy Attributes The Numpy collections give attributes to the numpy arrays. These attributes assist us with knowing the shape, aspect, and different properties of a given numpy array. As we know,...

4 minutes read.

numpy.atleast_3d() in Python

numpy.atleast_3d() in Python The numpy.atleast_3d() function views the inputs as arrays with at least three dimensions. Syntax numpy.atleast_3d(*arys) Parameter arys1, arys2, … : This parameter represents one or more array-like sequences where the non-array inputs are converted...

1 minute read.

numpy.transpose() in Python

numpy.transpose() in Python The numpy.transpose() permutes the dimensions of an array. Syntax numpy.transpose(a, axes=None) Parameter a : This parameter represents an input array. axes : It is an optional parameter which by default, reverses the dimensions, otherwise permutes the axes according...

1 minute read.

numpy.meshgrid() in Python

numpy.meshgrid() in Python The meshgrid() function of Python numpy class returns the coordinate matrices from coordinate vectors. Syntax numpy.meshgrid(*xi, **kwargs) Parameter The numpy.meshgrid() function consists of four parameters which are as follow: x1, x2,…, xn: This parameter signifies...

2 minutes read.

NumPy vs SciPy

NumPy- NumPy is the most important Python package for scientific computing. It's a Python library that includes a multidimensional array object, derived objects (like masked arrays and matrices), and a...

3 minutes read.