In this Numpy Tutorial, we will learn how to install numpy library in python, numpy multidimensional arrays, numpy datatypes, numpy mathematical operation on these multidimensional arrays, and different functionalities of Numpy library.
What is Numpy?
Numpy is a Python library that supports multi-dimensional arrays and matrix. It also provides many basic and high-level mathematical functions that can be applied on these multi-dimensional arrays and matrices with less code footprint.
There are many reasons why Numpy package has been used by data scientist and analysts, machine learning experts, deep learning libraries, etc. We will go through some of the most basic advantages of Numpy over regular lists or arrays in Python.
- The code that involves arrays with Numpy package is precise to apply transformations or operations for each element of the multidimensional arrays unlike a Python List.
- Since n-dimensional arrays of Numpy use a single datatype and contiguous memory for storage, they take relatively lesser memory read and write times.
- The most useful features of Numpy package is the compact datatypes that it offers, like unsigned integers of 8 bits, 16 bits size and signed integers of different bit sizes, different floating point precisions, etc.
Basics of Numpy
NumPy Basic Functions
NumPy Mathematical Functions
NumPy String Functions
Numpy char.partition() function