In this python tutorial, you will learn about **What is NumPy in python** and, also we will check**:**

- What is NumPy?
- Why NumPy is used?
- Where is NumPy used?
- Operations using NumPy
- How to install NumPy in Python?
- Python NumPy version
- How to Import NumPy?
- How to import NumPy in Python 2.7
- Python NumPy example
- Advantages of using NumPy
- What makes NumPy better than the python list?

**Table of Contents**show

## What is NumPy in Python?

**NumPy**is the fundamental package for scientific computing in python.**NumPy**stands for Numerical Python. It is open-source and we can use it freely.**NumPy**is a python library that is used for working with arrays.**Python NumPy**also contains random number generators. It also has functions for working in the domain of linear algebra, Fourier transforms, and matrices, etc.

Python Numpy is a popular library used to deal with arrays. Arrays can be single, double, or multiple dimensional. Numpy is widely used for performing scientific calculations, matrix operations, and is the major component of Machine Learning and Data Science.

Read: Check if NumPy Array is Empty in Python

## What is NumPy in Python used for

**NumPy**is used because it is faster and compact than python lists. In python, we have lists that serve the purpose of arrays, but they are slow.**NumPy**provides an array object that is up to 50x faster than python lists.**NumPy**uses much less memory to store data.- The array object in
**NumPy**is called**ndarray**and it provides a lot of functions that make working with ndarray very easy.

Read: Python NumPy Array

## Where is Python NumPy used?

**NumPy**is used for working with arrays.- It is a python library that provides a multidimensional array object, it also includes mathematical, logical, shape manipulation, sorting, Fourier transforms, basic linear algebra, statistical operations, and much more.

## Operations using NumPy

We can perform the following operations using **NumPy in Python**:-

- Logical operations and mathematical operations on arrays.
- Fourier transforms and routines for shape manipulation.
- NumPy has in-built functions for linear algebra and random number generation.
- We can also perform operations related to linear algebra.

Read: Python NumPy Random + Examples

## How to install NumPy?

If you have **python installed** in your system then you can** install NumPy **very easy with using the simple commands on your terminal:

`pip install numpy`

## Python NumPy version

For checking the **numpy version** the version string is stored under **“__version__”** attribute.

```
import numpy as np
print(np.__version__)
```

## How to Import NumPy?

- Once NumPy is installed successfully, then you need to import it into your applications by adding the
**import**keywords. - We need to use
**import numpy**. - Now,
**numpy**is imported and you can use it.

`import numpy`

**Example :**

```
import numpy
my_arr = numpy.array([10, 11, 12, 13, 14])
print(my_arr)
```

Read: Python NumPy Sum

## How to import NumPy in Python 2.7

To **import NumPy in Python 2.7** use the below import commands to include the NumPy package.

`import numpy`

## Python NumPy example

**NumPy** is usually imported under the np alias. We have created an alias with the keyword while importing. The package can be referred to as np instead of NumPy.

```
import numpy as np
my_arr = np.array([11, 12, 13, 14, 15])
print(my_arr)
```

You can refer to the below screenshot to see the output for **NumPy arrays**.

## Advantages of using NumPy

**Numpy**uses much less memory to store data in Python.**Numpy**arrays take significantly less amount of memory as compared to python lists.- We can perform mathematical operations on NumPy which makes it extremely easy and
**Numpy**provides multiple functions to work in Python. **Numpy**provides the support of highly optimized multidimensional arrays.

## What makes NumPy better than Python list?

**NumPy**consumes**less memory**than the python list.**Python Numpy**is fast and more compact as compared to a python list.**NumPy**is much convenient to use than a python list.**Numpy**is faster as it uses C API and for most of its operation, we don’t need to use any looping operation.

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In this Python tutorial, we have learned about** NumPy in Python **and also** how to install Numpy**. Also, we covered these below topics:

- What is NumPy?
- What is NumPy in python used for?
- Where is NumPy used?
- Operations using NumPy
- How to install NumPy?
- Python NumPy version
- How to Import NumPy?
- How to import NumPy in Python 2.7
- Python NumPy example
- Advantages of using NumPy
- What makes NumPy better than the python list?

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