Python | Numpy ndarray.__array__() Last Updated : 29 Mar, 2019 Comments Improve Suggest changes Like Article Like Report With the help of ndarray.__array__() method, we can create a new array as we want by giving a parameter as dtype and we can get a copy of an array that doesn't change the data element of original array if we change any element in the new one. Syntax : ndarray.__array__() Return : Returns either a new reference to self if dtype is not given New array of provided data type if dtype is different from the current dtype of the array. Example #1 : In this example we can see that we change the dtype of a new array by just using ndarray.__array__() method. Python3 1== # import the important module in python import numpy as np # make an array with numpy gfg = np.array([1, 2, 3, 4, 5]) # applying ndarray.__array__() method geeks = gfg.__array__(float) print(geeks) Output: [ 1. 2. 3. 4. 5.] Example #2 : Python3 1== # import the important module in python import numpy as np # make an array with numpy gfg = np.array([[1.1, 2, 3.3, 4, 5], [6, 5.2, 4, 3, 2.2]]) # applying ndarray.__array__() method geeks = gfg.__array__(int) print(geeks) Output: [[1 2 3 4 5] [6 5 4 3 2]] Comment More infoAdvertise with us Next Article Python | Numpy ndarray.item() J jitender_1998 Follow Improve Article Tags : Python Python-numpy Python numpy-ndarray Practice Tags : python Similar Reads Python | Numpy ndarray.__iand__() With the help of Numpy ndarray.__iand__() method, we can get the elements that is anded by the value that is provided as a parameter in numpy.ndarray.__iand__() method. Syntax: ndarray.__iand__($self, value, /) Return: self&=value Example #1 : In this example we can see that every element is and 1 min read Python | Numpy ndarray.__iand__() With the help of Numpy ndarray.__iand__() method, we can get the elements that is anded by the value that is provided as a parameter in numpy.ndarray.__iand__() method. Syntax: ndarray.__iand__($self, value, /) Return: self&=value Example #1 : In this example we can see that every element is and 1 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 Python | Numpy ndarray.item() With the help of numpy.ndarray.item() method, we can fetch the data elements that is found at the given index on numpy array. Remember we can give index as one dimensional parameter or can be two dimensional. Parameters: *args : Arguments (variable number and type) -> none: This argument only works 2 min read Python | Numpy ndarray.item() With the help of numpy.ndarray.item() method, we can fetch the data elements that is found at the given index on numpy array. Remember we can give index as one dimensional parameter or can be two dimensional. Parameters: *args : Arguments (variable number and type) -> none: This argument only works 2 min read Like