Numpy: For faster operations

What is NumPy?

NumPy is a Python library used for working with arrays.
It also has functions for working in domain of linear algebra, fourier transform, and matrices.
NumPy was created in 2005 by Travis Oliphant. It is an open source project and you can use it freely.
NumPy stands for Numerical Python.

Why Numpy?

Numpy arrays offer the following benefits over Python lists for operating on numerical data:

In Python we have lists that serve the purpose of arrays, but they are slow to process.
NumPy aims to provide an array object that is up to 50x faster than traditional Python lists.
The array object in NumPy is called ndarray, it provides a lot of supporting functions that make working with ndarray very easy.
Arrays are very frequently used in data science, where speed and resources are very important.

Five Numpy Operations to upgrade yourself

NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object

numpy.concatenate
numpy.arange
numpy.reshape
numpy.pad
numpy.extract

!pip install jovian --upgrade -q

import jovian

jovian.commit(project='numpy-array-operations', privacy='secret', environment=None)

[jovian] Attempting to save notebook..
[jovian] Updating notebook "tanushagupta4/numpy-array-operations" on https://jovian.ai
[jovian] Uploading notebook..
[jovian] Uploading additional files...
[jovian] Committed successfully! https://jovian.ai/tanushagupta4/numpy-array-operations

'https://jovian.ai/tanushagupta4/numpy-array-operations'

Let's begin by importing Numpy and listing out the functions covered in this notebook.