NumPy Array in Python

Python | Numpy ndarray.array()

Last Updated : 29 Mar, 2019

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]]

NumPy Array in Python

J

Improve

Article Tags :

Practice Tags :

python

Similar Reads

Python | Numpy ndarray.__ior__()

With the help of Numpy ndarray.__ior__() method, we can get the elements that is OR by the value that is provided as a parameter in numpy.ndarray.__ior__() method. Syntax: ndarray.__ior__($self, value, /) Return: self|=value Example #1 : In this example we can see that every element is or by the val

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

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

Python | Numpy ndarray.__ixor__()

With the help of Numpy ndarray.__ixor__() method, we can get the elements that is XOR by the value that is provided as a parameter in numpy.ndarray.__ixor__() method. Syntax: ndarray.__ixor__($self, value, /) Return: self^=value Example #1 : In this example we can see that every element is xor by th

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

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

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

Python | Numpy ndarray.__imod__()

With the help of Numpy ndarray.__imod__(), every element in an array is operated on binary operator i.e mod(%). Remember we can use any type of values in an array and value for mod is applied as the parameter in ndarray.__imod__(). Syntax: ndarray.__imod__($self, value, /) Return: self%=value Exampl

Python | Numpy ndarray.__ipow__()

With the help of Numpy ndarray.__ipow__() method, we will get all the elements powered with the value that is provided as a parameter in numpy.ndarray.__ipow__() method. Syntax: ndarray.__ipow__($self, value, /) Return: self**=value Example #1 : In this example we can see that every element get powe

numpy.asfortranarray() in Python

numpy.asfortranarray() function is used when we want to convert input to a array which is laid out in Fortran order in memory. Input includes scalar, lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Syntax : numpy.asfortranarray(arr, dtype=None)Â Parameters :Â arr : [ar