# Numpy Tutorial in Python

**Numpy Tutorial in Python**, Welcome to the world of Python NumPy Tutorial. Are you the one who is looking forward to knowing the Python NumPy? Or the one who is very keen to explore the NumPy tutorial in Python with examples that are available? Then you’ve landed on the Right path which provides the standard information of Python NumPy Tutorial.

## What is NumPy in Python?

NumPy is an array-processing package. It provides a multidimensional array object and tools for working with these arrays with high-performance.## Features of Numpy in Python

1. A powerful N-dimensional array object 2. Sophisticated (broadcasting) functions 3. Tools for integrating C/C++ and Fortran code**Useful linear algebra, Fourier transform, and random number capabilities**

NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined using Numpy which allows NumPy to seamlessly and speedily integrate with a large variety of databases.
## Installation of Python Numpy

**Installation of Numpy on Mac**

**Step1)**Open the terminal

**Step2)**pip install numpy

**Installation of Numpy on windows**

**Step1)**Go to the File menu

**Step2)**Go to settings

**Step3)**Go to Project

**Step4)**Go to project Interpreter

**Step5)**Click on ‘+’ icon

**Step6)**Type numPy.

**Step7)**Select it and install it.

**Step8)**import numpy as n

**Step9)**Use it

**Properties of Numpy**

**Arrays in NumPy:**NumPy’s mainly used for homogeneous multidimensional array. 1. It is a table kind structure consisting of elements, having a similar data type, indexed by a tuple of positive integers. 2. In NumPy dimensions are known as axes. The number of axes is rank. Ex) [[11,22,33], [44,55,66]] Here, rank= 2 (as it is two dimensional or you can say it has 2 axis)

### How to implement Numpy

Ex) import numpy as n a=n.array([2,3,4]) print(a)## Numpy Arrays in Python

**Arrays are of 2 types**

**Single Dimension Arrays:**Arrays having only one dimension i.e. only a row or only a column. Ex) import numpy as n a=n.array([1,8,6])

**Multi Dimension Arrays:**Array having more than one dimension is known as multi-dimension arrays. Ex) import numpy as n a= n.array([1,2,4],[2,5,7],[7,8,9],[1,2,4]) 1. It occupies Less Memory. 2. It is a pity Fast as compared to List 3. It is also convenient to use Convenient