Python Lists VS Numpy Arrays

Python | numpy.array_split() method

Last Updated : 17 Sep, 2019

With the help of numpy.array_split() method, we can get the splitted array of having different dimensions by using numpy.array_split() method.

Syntax : numpy.array_split() Return : Return the splitted array of one dimension.

Example #1 : In this example we can see that by using numpy.array_split() method, we are able to split the array in the number of subarrays by passing it as a parameter.

Python3 1=1

# import numpy
import numpy as np

array = np.arange(9)

# using numpy.array_split() method
gfg = np.array_split(array, 4)

print(gfg)

Output :

[array([0, 1, 2]), array([3, 4]), array([5, 6]), array([7, 8])]

Example #2 :

Python3 1=1

# import numpy
import numpy as np

array = [[1, 2, 3],
         [4, 5, 6],
         [7, 8, 9]]

# using numpy.array_split() method
gfg = np.array_split(array, 3)

print(gfg)

Output :

[array([[1, 2, 3]]), array([[4, 5, 6]]), array([[7, 8, 9]])]

Python Lists VS Numpy Arrays

J

Improve

Article Tags :

Practice Tags :

python

Similar Reads

Python | Numpy fromarrays() method

With the help of numpy.core.fromarrays() method, we can create the record array by using the list of different arrays by using numpy.core.fromarrays() method. Syntax : numpy.core.fromarrays([li1, li2....], metadata) Return : Return the record of an array. Example #1 : In this example we can see that

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

Python Lists VS Numpy Arrays

Here, we will understand the difference between Python List and Python Numpy array. What is a Numpy array?NumPy is the fundamental package for scientific computing in Python. Numpy arrays facilitate advanced mathematical and other types of operations on large numbers of data. Typically, such operati

Python | Numpy numpy.ndarray.__rshift__()

With the help of numpy.ndarray.__rshift__() method, we can get the elements that is right shifted by the value that is provided as a parameter in numpy.ndarray.__rshift__() method. Syntax: ndarray.__rshift__($self, value, /) Return: self>>value Example #1 : In this example we can see that ever

numpy.array_repr() in Python

numpy.array_repr()function is used to convert an array to a string. Syntax : numpy.array_repr(arr, max_line_width=None, precision=None, suppress_small=None) Parameters : arr : [array_like] Input array. max_line_width : [int, optional] The maximum number of columns the string should span. Newline cha

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

Python | Numpy numpy.ndarray.__sub__()

With the help of Numpy numpy.ndarray.__sub__(), We can subtract a particular value that is provided as a parameter in the ndarray.__sub__() method. Value will be subtracted to each and every element in a numpy array. Syntax: ndarray.__sub__($self, value, /) Return: self-value Example #1 : In this ex

numpy.vsplit() function | Python

numpy.vsplit() function split an array into multiple sub-arrays vertically (row-wise). vsplit is equivalent to split with axis=0 (default), the array is always split along the first axis regardless of the array dimension. Syntax : numpy.vsplit(arr, indices_or_sections) Parameters : arr : [ndarray] A

Python - Numpy fromrecords() method

numpy.fromrecords() method is a powerful tool in the NumPy library that allows you to create structured arrays from a sequence of tuples or other array-like objects. Let's understand the help of an example:Pythonimport numpy as np # Define a list of records records = [(1, 'Alice', 25.5), (2, 'Bob',

Numpy MaskedArray asarray() method | Python

numpy.ma.asarray() function is used when we want to convert input to a masked array of the given data-type. No copy is performed if the input is already a ndarray. If arr is a subclass of MaskedArray, a base class MaskedArray is returned. Syntax : numpy.ma.asarray(arr, dtype=None, order=None) Parame