The most important object defined in NumPy is an N-dimensional array type called ndarray. It describes the collection of items of the same type. Items in the collection can be accessed using a zero-based index.
Every item in an ndarray takes the same size of block in the memory. Each element in ndarray is an object of data-type object (called dtype).
Any item extracted from ndarray object (by slicing) is represented by a Python object of one of array scalar types. The following diagram shows a relationship between ndarray, data type object (dtype) and array scalar type −
An instance of ndarray class can be constructed by different array creation routines described later in the tutorial. The basic ndarray is created using an array function in NumPy as follows −
numpy.array
It creates an ndarray from any object exposing array interface, or from any method that returns an
array.numpy.array(object, dtype = None, copy = True, order = None, subok = False, ndmin = 0)
Sr.No. | Parameter & Description | |||
---|---|---|---|---|
1 | object: Any object exposing the array interface method returns an array, or any (nested) sequence. | |||
2 | dtype: Desired data type of array, optional | |||
3 | copy: Optional. By default (true), the object is copied | |||
4 | order: C (row major) or F (column major) or A (any) (default) | |||
5 | subok: By default, returned array forced to be a base class array. If true, sub-classes passed through | |||
6 | ndmin: Specifies minimum dimensions of resultant array |
import numpy as np
a = np.array([1,2,3])
print (a)
# more than one dimensions
import numpy as np
a = np.array([[1, 2], [3, 4]])
print (a)
# minimum dimensions
import numpy as np
a = np.array([1, 2, 3,4,5], ndmin = 2)
print (a)
The ndarray object consists of contiguous one-dimensional segment of computer memory, combined with an indexing scheme that maps each item to a location in the memory block.
If you are more comfortable learning through video tutorials then we would recommend that you subscribe to our YouTube channel.
When going through coding examples, it's quite common to have doubts and errors.
If you have doubts about some code examples or are stuck somewhere when trying our code, send us an email at coderzcolumn07@gmail.com. We'll help you or point you in the direction where you can find a solution to your problem.
You can even send us a mail if you are trying something new and need guidance regarding coding. We'll try to respond as soon as possible.
If you want to