Understanding The Numpy Mindset • Numerical Python

A concise course to master the NumPy fundamentals

What you'll learn

Learn the fundamentals of Python's NumPy package

Understand the mindset needed to work with NumPy

Learn to create and use NumPy's ndarray object

Use NumPy in real-world examples

Requirements

You should be familiar with Python fundamentals such as control statements, defining functions, using data structures such as lists

Description

This is a concise course that covers the fundamentals of Python's NumPy package. Most students who learn NumPy for the first time say that it feels different from the core Python they learnt. And they're right.NumPy requires a different mindset. There's a reason why NumPy does things differently and if you understand why things are the way they are in NumPy, the rest of your NumPy journey will be easier.This course doesn't try to cover everything in the NumPy package. That's impossible and not desirable. Instead, I designed this course to be concise and to focus on what really matters:Understanding the core topics in NumPyUnderstanding the NumPy mindsetThis course covers the following topics:NumPy's main data structure, the ndarrayVectorisation in NumPyArrays in higher dimensionsThe basics of broadcastingFiltering NumPy arrays using Boolean operations and Boolean indexingReading external data using NumPyRepresenting equations with NumPyAnd of course, throughout the whole course you'll get familiar with the NumPy mindset.–-About me, your instructorI've been teaching Python and NumPy for a decade. Before that, I worked as a physicist and used numerical and scientific programming in my research work for over a decade.My focus is on communicating clearly, in a friendly and relaxed manner. I'm the author of the The Python Coding Book (you can ask Google for a "python book" and you'll find this book as one of the first entries) and I have taught Python to individuals and corporations around the world.And I'm approachable. You can ask me questions and I'll always reply, whether here on social media or anywhere else you can find me!

Overview

Section 1: On the Road to NumPy

Lecture 1 What's This Course About?

Lecture 2 Let's Start With Lists. Yes, Lists

Lecture 3 The Lesser-Known Array

Section 2: Understanding NumPy's `ndarray` Data Type

Lecture 4 Installing NumPy

Lecture 5 Finally, Say Hello to `ndarray`

Lecture 6 Looking Ahead to Some Other `ndarray` Features

Section 3: Vectorisation • A Fancy Word For NumPy's "Superpower"

Lecture 7 Performing Operations Element-by-Element in NumPy • Vectorisation

Lecture 8 Comparing Loops With Lists, List Comprehensions, and NumPy Vectorisation

Lecture 9 Let's Race • Timing The Three Versions

Lecture 10 A Glimpse At NumPy's Documentation

Section 4: Multiple Dimensions in NumPy Arrays

Lecture 11 More Than One Dimension

Lecture 12 Creating Arrays of Random Numbers • The Five-Player Three-Round Game

Lecture 13 Broadcasting • A Brief Introduction

Lecture 14 Another Glimpse At NumPy's Documentation

Lecture 15 Let's Add One More Dimension • 3D Arrays

Section 5: Boolean Operations, Boolean Indexing, Filtering, And More

Lecture 16 Boolean Operations on NumPy Arrays

Lecture 17 Boolean Indexing and Filtering

Lecture 18 There's Lots More in NumPy's API

Lecture 19 Views and Copies • A Brief Introduction

Section 6: The Met Office Temperature Dataset

Lecture 20 Reading The Data From a CSV File to a NumPy Array

Lecture 21 Remove What We Don't Need From The Array

Lecture 22 Finding the Minimum, Maximum, and Mean Temperatures

Lecture 23 Grouping Temperatures Using a Histogram

Lecture 24 Grouping Temperatures Using a Histogram • Plotting the Data

Section 7: Representing Equations Using NumPy

Lecture 25 From an Equation on Paper to An Equation on Computer • `np.arange()` and `np.lin

Lecture 26 Plotting The Equation

Lecture 27 Final Words

Python programmers who are keen to learn about Python's key numerical programming package: NumPy