Python | Numpy numpy.matrix.any() Last Updated : 08 Apr, 2019 Comments Improve Suggest changes Like Article Like Report With the help of Numpy numpy.matrix.any() method, we are able to compare each and every element of one matrix with another or we can provide the axis on the we want to apply comparison if any of the element matches it return true. Syntax : numpy.matrix.any() Return : Return true if any match found else false Example #1 : In this example we can see that with the help of matrix.any() method, we are able to compare any two matrix having different dimensions and if any match found then return true. Python3 1== # import the important module in python import numpy as np # make a matrix with numpy gfg1 = np.matrix('[1, 2, 3, 4]') gfg2 = np.matrix('[1, 2]') # applying matrix.any() method geeks = (gfg1 == gfg2).any() print(geeks) Output: True Example #2 : Python3 1== # import the important module in python import numpy as np # make a matrix with numpy gfg1 = np.matrix('[1, 2, 3; 4, 5, 6; 7, 8, 9]') gfg2 = np.matrix('[1, 2, 3]') # applying matrix.any() method geeks = (gfg1 == gfg2).any() print(geeks) Output: True Comment More infoAdvertise with us Next Article Python | Numpy numpy.matrix.any() J Jitender_1998 Follow Improve Article Tags : Python Python-numpy Python numpy-Matrix Function Practice Tags : python Similar Reads Python | Numpy numpy.matrix.all() With the help of Numpy numpy.matrix.all() method, we are able to compare each and every element of one matrix with another or we can provide the axis on the we want to apply comparison. Syntax : numpy.matrix.all() Return : Return true if found match else false Example #1 : In this example we can see 1 min read numpy.asmatrix() in Python numpy.asmatrix(data, dtype = None) Returns a matrix by interpreting the input as a matrix. Parameters : data : array-like input data dtype : Data type of returned array Returns : Interprets the input as a matrix Python # Python Programming illustrating # numpy.asmatrix import numpy as geek # array-l 1 min read numpy.matrix() in Python This class returns a matrix from a string of data or array-like object. Matrix obtained is a specialised 2D array. Syntax : numpy.matrix(data, dtype = None) : Parameters : data : data needs to be array-like or string dtype : Data type of returned array. Returns : data interpreted as a matrix Python 1 min read numpy.any() in Python The numpy.any() function tests whether any array elements along the mentioned axis evaluate to True. Syntax :Â numpy.any(a, axis = None, out = None, keepdims = class numpy._globals._NoValue at 0x40ba726c) Parameters :Â array :[array_like]Input array or object whose elements, we need to test. axis : 3 min read Python | Numpy numpy.ndarray.__or__() With the help of Numpy numpy.ndarray.__or__() method, we can get the elements that is OR by the value that is provided as a parameter in numpy.ndarray.__or__() method. Syntax: ndarray.__or__($self, value, /) Return: self|value Example #1 : In this example we can see that every element is or by the v 1 min read Python | Numpy numpy.ndarray.__ne__() With the help of numpy.ndarray.__ne__() method of Numpy, We can find that which element in an array is not equal to the value which is provided in the parameter. It will return you numpy array with boolean type having only values True and False. Syntax: ndarray.__ne__($self, value, /) Return: self!= 1 min read numpy.matrix.A() function - Python numpy.matrix.A() function return self as an ndarray object. Syntax : numpy.matrix.A() Parameters : None Return : [ndarray] Return self as an ndarray. Code #1 : Python3 # Python program explaining # numpy.matrix.A() function # importing numpy as geek import numpy as geek mat = geek.matrix(geek.arange 1 min read Python | Numpy matrix.take() With the help of Numpy matrix.take() method, we can select the elements from a given matrix by passing the parameter as index value of that element. It will return a matrix having one dimension. Remember it will work for one axis at a time. Syntax : matrix.take(index, axis) Return : Return matrix of 1 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 :Â array :[array_like]Input array or object whose elements, we need to test. axis 3 min read numpy.empty() in Python numpy.empty(shape, dtype = float, order = 'C') : Return a new array of given shape and type, with random values. Parameters : -> shape : Number of rows -> order : C_contiguous or F_contiguous -> dtype : [optional, float(by Default)] Data type of returned array. Python # Python Programming i 1 min read Like