Python | Numpy matrix.copy() Last Updated : 12 Apr, 2019 Comments Improve Suggest changes Like Article Like Report With the help of Numpy matrix.copy() method, we can make a copy of all the data elements that is present in matrix. If we change any data element in the copy, it will not affect the original matrix. Syntax : matrix.copy() Return : Return copy of matrix Example #1 : In this example we can see that with the help of matrix.copy() method we are making the copy of an elements in different matrix. Python3 1== # import the important module in python import numpy as np # make matrix with numpy gfg = np.matrix('[1, 2, 3]') # applying matrix.copy() method geeks = gfg.copy() print(geeks) Output: [[1 2 3]] Example #2 : Python3 1== # import the important module in python import numpy as np # make a matrix with numpy gfg = np.matrix('[1, 2, 3; 4, 5, 6]') # applying matrix.copy() method geeks = gfg.copy() print(geeks) Output: [[1 2 3] [4 5 6]] Comment More infoAdvertise with us Next Article Python | Numpy matrix.copy() J Jitender_1998 Follow Improve Article Tags : Python Python-numpy Python numpy-Matrix Function Practice Tags : python Similar Reads 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 Python | Numpy ndarray.__copy__() With the help of Numpy ndarray.__copy__() method, we can make a copy of all the data elements that is present in numpy array. If you change any data element in the copy, it will not affect the original numpy array. Syntax : numpy.__copy__() Return : Copy of all the data elements Example #1 : In this 1 min read Numpy matrix.I function | Python With the help ofnumpy.matrix.I() function we can get the multiplicative inverse of the same size as of our given matrix. Syntax : numpy.matrix.I() Return : [matrix object] If self is non-singular, ret is such that ret * self == self * ret == np.matrix(np.eye(self[0, :].size) all return True. Return 1 min read numpy.copysign() in Python numpy.copysign(arr1, arr2, out = None, where = True, casting = âsame_kindâ, order = âKâ, dtype = None) : This mathematical function helps user to change the sign of arr1 and arr2. Both arr1 or arr2 can be either list/sequence or a scalar value. If sequence, both must have same dimension; otherwise a 2 min read Python | Numpy numpy.matrix.A() With the help of Numpy numpy.matrix.A() method, we can get the same matrix as self. It means through this method we can get the identical matrix. Syntax : numpy.matrix.A() Return : Return self matrix Example #1 : In this example we can see that with the help of matrix.A() method, we are able to get 1 min read numpy.eye() in Python numpy.eye() is a function in the NumPy library that creates a 2D array with ones on the diagonal and zeros elsewhere. This function is often used to generate identity matrices with ones along the diagonal and zeros in all other positions.Let's understand with the help of an example:Pythonimport nump 2 min read Python | Numpy matrix.transpose() With the help of Numpy matrix.transpose() method, we can find the transpose of the matrix by using the matrix.transpose()method in Python. Numpy matrix.transpose() Syntax Syntax : matrix.transpose() Parameter: No parameters; transposes the matrix it is called on. Return : Return transposed matrix Wh 3 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.multiply() in Python The numpy.multiply() is a numpy function in Python which is used to find element-wise multiplication of two arrays or scalar (single value). It returns the product of two input array element by element.Syntax:numpy.multiply(arr1, arr2, out=None, where=True, casting='same_kind', order='K', dtype=None 3 min read Like