numpy.ones() in Python Last Updated : 08 Mar, 2024 Summarize Comments Improve Suggest changes Share Like Article Like Report The numpy.ones() function returns a new array of given shape and type, with ones. Syntax: numpy.ones(shape, dtype = None, order = 'C') Parameters : shape : integer or sequence of integers order : C_contiguous or F_contiguous C-contiguous order in memory(last index varies the fastest) C order means that operating row-rise on the array will be slightly quicker FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster. dtype : [optional, float(byDefault)] Data type of returned array. Returns : ndarray of ones having given shape, order and datatype. Python # Python Program illustrating # numpy.ones method import numpy as geek b = geek.ones(2, dtype = int) print("Matrix b : \n", b) a = geek.ones([2, 2], dtype = int) print("\nMatrix a : \n", a) c = geek.ones([3, 3]) print("\nMatrix c : \n", c) Output : Matrix b : [1 1] Matrix a : [[1 1] [1 1]] Matrix c : [[ 1. 1. 1.] [ 1. 1. 1.] [ 1. 1. 1.]] Note : Ones, unlike zeros and empty, does not set the array values to zero or random values respectively.Also, these codes won’t run on online-ID. Please run them on your systems to explore the working. Comment More infoAdvertise with us Next Article numpy.ones() in Python K kartik Improve Article Tags : Python Python-numpy Python numpy-arrayCreation Practice Tags : python Similar Reads numpy.ones_like() in Python The numpy.one_like() function returns an array of given shape and type as a given array, with ones. Syntax: numpy.ones_like(array, dtype = None, order = 'K', subok = True) Parameters : array : array_like input subok : [optional, boolean]If true, then newly created array will be sub-class of array; o 2 min read numpy.any() in Python The numpy.any() function tests whether any array elements along the mentioned axis evaluate to True. Syntax : numpy.any(a, axis = None, out = None, keepdims = class numpy._globals._NoValue at 0x40ba726c) Parameters : array :[array_like]Input array or object whose elements, we need to test. axis : 3 min read numpy.packbits() in Python numpy.packbits() is another function for doing binary operations in numpy.It is used to packs the elements of a binary-valued array into bits in a uint8 array.The result is padded to full bytes by inserting zero bits at the end. Syntax : numpy.packbits(arr, axis=None) Parameters : arr : [array_like] 2 min read numpy.all() in Python The numpy.all() function tests whether all array elements along the mentioned axis evaluate to True. Syntax: numpy.all(array, axis = None, out = None, keepdims = class numpy._globals._NoValue at 0x40ba726c) Parameters : array :[array_like]Input array or object whose elements, we need to test. axis 3 min read Python NumPy Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. It is the fundamental package for scientific computing with Python.Besides its obvious scientific uses, Numpy can also be used as an efficient m 6 min read Like