Some Smart and Interesting Operations on Numpy.

What is NumPy?

Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. It is the fundamental package for scientific computing with Python.
Besides its obvious scientific uses, Numpy can also be used as an efficient multi-dimensional container of generic data.

Why Use Numpy ?

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 that 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.

Here are 5 operations on NumPy which are interesting to learn:

np.partition()
np.extract()
np.intersect1d()
np.flip()
np.count_nonzero()

!pip install jovian --upgrade -q

import jovian

jovian.commit(project='numpy-smart-and-interesting-array-operations')

[jovian] Attempting to save notebook..
[jovian] Creating a new project "ashu121343mishra/numpy-smart-and-interesting-array-operations"
[jovian] Uploading notebook..
[jovian] Capturing environment..
[jovian] Committed successfully! https://jovian.ml/ashu121343mishra/numpy-smart-and-interesting-array-operations

'https://jovian.ml/ashu121343mishra/numpy-smart-and-interesting-array-operations'

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