What is NumPy & why it is used?

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 NumPy is a Python library created in 2005 that performs numerical calculations. It is used for working with arrays.It also includes a wide range of mathematical functions,such as linear algebra,random number generation etc, which can be applied to arrays.

NumPy is generally used for

1.Machine Learning

2.Data Science

3.Image and signal Processing

4.Scientific Computing

 

Getting Started With NumPy

In this Numpy tutorial, we will be using Jupyter Notebook, which is an open-source web application that comes with built-in packages and enables you to run code in real-time.

Let’s get started by importing our NumPy module and writing basic code.

NumPy is usually imported under the np alias.

If NumPy is not installed, u can install through pip3/conda commands.

 


 You can create a array with one-dimensional array shown below

 


The array object in NumPy is called ndarray which is also called as N-Dimension array.

 

NDIM:

The ndim() attribute is used to find the dimensions of the array.

 


DTYPE:

It is an attribute which can identify the data type of given element

 


SHAPE:

This will return a tuple consisting of array dimensions.

 


It has been 2 dimensions, and each dimension contains 3 elements

 

SLICING:

It will extract the range of elements from the array.

Index starts from “0” in python

 


Random.rand():

This function generates random numbers from a uniform distribution over the interval [0,1].

 

 

Random.randint():

This function generates random integers within a specified range(low,high). Where low is inclusive and high is exclusive.

 

 


 

 


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