numpy.array_equal() in Python Last Updated : 29 Nov, 2018 Comments Improve Suggest changes Like Article Like Report numpy.array_equal(arr1, arr2) : This logical function that checks if two arrays have the same shape and elements. Parameters : arr1 : [array_like]Input array or object whose elements, we need to test. arr2 : [array_like]Input array or object whose elements, we need to test. Return : True, if both arrays have same shape and value; otherwise False Code : Explaining Working Python # Python program explaining # array_equal() function import numpy as np # input arr1 = np.arange(4) arr2 = [7, 4, 6, 7] print ("arr1 : ", arr1) print ("arr2 : ", arr2) print ("\nResult : ", np.array_equal(arr1, arr2)) arr1 = np.arange(4) arr2 = np.arange(4) print ("\n\narr1 : ", arr1) print ("arr2 : ", arr2) print ("\nResult : ", np.array_equal(arr1, arr2)) arr1 = np.arange(4) arr2 = np.arange(5) print ("\n\narr1 : ", arr1) print ("arr2 : ", arr2) print ("\nResult : ", np.array_equal(arr1, arr2)) Output : arr1 : [0 1 2 3] arr2 : [7, 4, 6, 7] Result : False arr1 : [0 1 2 3] arr2 : [0 1 2 3] Result : True arr1 : [0 1 2 3] arr2 : [0 1 2 3 4] Result : False References : https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.array_equal.html . Comment More infoAdvertise with us Next Article NumPy Array in Python M mohit gupta_omg :) Follow Improve Article Tags : Python Python-numpy Python numpy-Logic Functions Practice Tags : python Similar Reads numpy.array_equiv() in Python numpy.array_equiv(arr1, arr2) : This logical function that checks if two arrays have the same elements and shape consistent. Shape consistent means either they are having the same shape, or one input array can be broadcasted to create the same shape as the other one. Parameters : arr1 : [array_like] 2 min read NumPy Array in Python NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C 2 min read NumPy Array in Python NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C 2 min read numpy.asarray() in Python numpy.asarray()function is used when we want to convert input to an array. Input can be lists, lists of tuples, tuples, tuples of tuples, tuples of lists and arrays. Syntax : numpy.asarray(arr, dtype=None, order=None) Parameters : arr : [array_like] Input data, in any form that can be converted to a 2 min read numpy.not_equal() in Python The numpy.not_equal() checks whether two element are unequal or not. Syntax : numpy.not_equal(x1, x2[, out])Parameters : x1, x2 : [array_like]Input Array whose elements we want to checkout : [ndarray, optional]Output array that returns True/False. A placeholder the same shape as x1 to store the resu 2 min read numpy.array_str() in Python numpy.array_str()function is used to represent the data of an array as a string. The data in the array is returned as a single string. This function is similar to array_repr, the difference being that array_repr also returns information on the kind of array and its data type. Syntax : numpy.array_st 2 min read Like