Tuesday, May 26, 2020

Python NumPy

Python NumPy


Python has large standard-library and third-party tools support, but it does not provide support for built-in multi-dimensional array implicitly. NumPy provides a fast built-in object (N-D Array) which is a multi-dimensional array of a homogeneous data-type.

NumPy is an open-source and general-purpose Python library. It is the short form of Numerical Python. NumPy is a basic and powerful package for performing scientific computations programmatically. 

NumPy also provides a large collection of mathematical functions such as linear algebra, Fourier transform, and matrices. NumPy specifies several Matlab-ish functionalities to perform different types of scientific computations.

It was introduced by Travis Oliphant in 2005. NumPy replaces and extends its ancestors Numeric and Numarray. NumPy's official website is Website https://numpy.org/.

A NumPy array is a collection of homogenous (items of the same type) items is arranged in N-dimensions.

The type can be any arbitrary structure defined using the data-type. 


NumPy provides us

N-dimensional array(N-D Array)

Array capable of containing rectangular data, with the element of the array that can be C-structure or simple data-type. It provides fast algorithms on machine data-types (int, float, etc.)

Universal functions

These functions operate element-by-element and return result fast-loops registered for each fundamental data-type, for example
sin(x) = [sin(xi) i=0..N]
 x+y = [xi + yi i=0..N]

Getting started with NumPy

It can be installed easily into the Python ecosystem using the pip command

C:\Users\user>pip install numpy

Once it is installed successfully, it can be imported using the import command,

import numpy