Python for Data Science | NumPy Tutorial | Creating Array | List | Ones | Zeros | Full | Random #4

What is NumPY:

Before jumping into Numpy, let us understand what was the necessity of Numpy if we have python already. Numpy array are like python inbuilt list type, but Numpy array provide much more efficient storage and data operation as the array grow larger is size.

Python has functionality for common purpose as python are being used for many more use case. But in DS, numbers are very important and lot of number manipulation are there. We need 1D, 2D, 3D and multidimensional data. Python in build list is not sufficient for these kind of data.

Efficient storage and manipulation of numerical arrays is absolutely fundamental process of doing data science.

NumPy is the fundamental package for scientific computing in Python.
It is a Python library that provides a multidimensional array object and various fast operations on arrays, including mathematical, logical, shape manipulation, sorting.