{"id":79461,"date":"2020-07-21T13:35:00","date_gmt":"2020-07-21T08:05:00","guid":{"rendered":"https:\/\/techvidvan.com\/tutorials\/?p=79461"},"modified":"2020-07-21T13:35:00","modified_gmt":"2020-07-21T08:05:00","slug":"python-numpy-tutorial","status":"publish","type":"post","link":"https:\/\/techvidvan.com\/tutorials\/python-numpy-tutorial\/","title":{"rendered":"Python NumPy Tutorial for Data Science"},"content":{"rendered":"

In this NumPy Tutorial, we will learn what is NumPy<\/strong>. We will learn about its uses<\/strong>, installation<\/strong>, operations<\/strong> and many other features.<\/p>\n

So let’s start!!!<\/p>\n

NumPy Introduction<\/h3>\n

NumPy stands for \u2018Numerical Python\u2019<\/strong>. It is a package<\/strong> in Python to work with arrays<\/strong>. It is a basic scientific library<\/strong>. Its most important feature is the n-dimensional array object<\/strong>. It has uses in statistical functions<\/strong>, linear algebra<\/strong>, arithmetic operations<\/strong>, bitwise operations<\/strong>, etc.<\/p>\n

We perform all the operations<\/strong> on the array elements<\/strong>. We can initialize<\/strong> these arrays<\/strong> in several ways.<\/p>\n

Prerequisite to Learn NumPy<\/h3>\n

The two basic prerequisites<\/strong> for NumPy are Python<\/strong> and Mathematics<\/strong>. We need to know the python basics<\/strong> to work with the NumPy module<\/strong>.<\/p>\n

The functions available in NumPy<\/strong> are built<\/strong> on python language<\/strong>. We can hence combine the knowledge of python arrays<\/strong> and list<\/strong> for array initialization<\/strong> and operations<\/strong>.<\/p>\n

NumPy Installation<\/h3>\n

We can install Python NumPy by going to the command prompt<\/strong> and typing<\/strong> a simple command<\/strong> pip<\/strong> install NumPy<\/strong>. Then go to the IDE<\/strong> and use the import command import NumPy<\/strong> as np<\/strong>.<\/p>\n

We can now access<\/strong> all the functionalities<\/strong> of the NumPy module<\/strong>.<\/p>\n

Uses of NumPy<\/h3>\n

\"Uses<\/a><\/p>\n

NumPy is one of the most useful external libraries<\/strong> available in Python. It has a wide variety of functions<\/strong> to work with arrays<\/strong> and a powerful multi-dimensional array object<\/strong>. It has operations<\/strong> that are applicable<\/strong> to a vast range<\/strong> of platforms<\/strong>.<\/p>\n

Numpy can be put to use for storing<\/strong>, manipulation<\/strong>, and deletion<\/strong> of array elements<\/strong>. We can use it for sorting<\/strong>, indexing<\/strong>, and stacking<\/strong> of the array elements<\/strong>. It has modules regarding various operations:<\/p>\n