Python Numpy

In this tutorial you will learn:

• Numpy Introduction
• Numpy Installation
• Uses of Numpy

Numpy Introduction

Now that we have all the basic knowledge of Python it’s time to study the advanced topcs. Numpy is a library used for scientific computing. It gives us access to multi dimensional array objects and different functions to manipulate those arrays and data structures. Numpy also allows us to integrate C/C++ code with Python and gives us wide range of mathematical functions as well. These mathematical functions include Fourier transforms, Linear Algebraic models and random number generators.

Numpy Installation

To use Numpy it’s recommended to use SciPy known as Scientific Python. To use Scientific Python we recommend downloading and installing a software called Anaconda. Latest version can be downloaded from the link below.

https://www.anaconda.com/distribution/

Another way is to install Numpy using a package manager such as Pip. Details of Pip are already discussed in the previous tutorials. If package manager is already setup then we can run the following command.

For using Numpy we can simply import it in the required file.

Uses of Numpy

1. Numpy arrays are faster then lists in Python.
2. Numpy allows only same type of data in each column thus allowing us to maintain data in specifically formatted columns.
3. It provids a N dimensional array object which has immense usage in Linear Algebraic equations.
4. Numpy is an alternative to MATLAB
Numpy is used in complex scientific computing applications