I've Read Over 100 Books on Python. Here are the Top 3

Summary

The speaker discusses their experience with over 100 Python books and highlights the importance of picking the right resources as a beginner. They compare learning Python to learning a language, emphasizing gradual practice rather than overwhelming study. Three book recommendations are made: 'Python Crash Course' for hands-on learning, 'Python Programming' for foundational computer science knowledge, and options for specific interests like data analysis or algorithms. The speaker also stresses the value of interactive learning, suggesting Brilliant.org as a tool to enhance understanding through engaging courses.

Takeaways

• 📚 The speaker has read over 100 Python books over the years and wants to share their top three recommendations.
• ❌ The speaker emphasizes avoiding books that are too overwhelming for beginners, with too much vocabulary and grammar.
• 🧠 Learning Python is similar to learning a language: start with the basics and build upon them through practice and projects.
• 📖 The first recommended book is 'Python Crash Course,' which splits learning into two parts: foundational knowledge and project-based applications.
• 👾 In 'Python Crash Course,' the second part includes projects like building a game (Space Invaders), data visualizations, and web apps.
• 💻 The second book recommendation is 'Python Programming' by John Zelle, which introduces the basics of computer science and helps with algorithmic thinking.
• 📝 The speaker suggests approaching 'Python Programming' by doing exercises at the end of each chapter and revisiting sections when stuck.
• 💡 For deeper computer science understanding, the speaker recommends 'Classic Computer Science Problems in Python' and 'Algorithms Illuminated.'
• 📊 If the learner's focus is data analysis, 'Learning Scientific Programming with Python' or 'Python Tools for Scientists' are excellent broad options.
• 🐼 For those specifically interested in learning pandas, the best book is 'Effective Pandas,' which offers in-depth instruction on using the pandas library.

Q & A

Why does the speaker compare learning Python to learning English?

The speaker compares learning Python to learning English to emphasize that just memorizing vocabulary and grammar isn’t sufficient. Instead, one should focus on practical application, practice, and progressively build up knowledge through projects and problem-solving, similar to how one learns to communicate in a new language.

What is the speaker’s first recommended book for learning Python?

The speaker's first recommended book is *Python Crash Course*, which is praised for its clear structure. It teaches the basics of Python in the first part and provides project-based learning in the second part, allowing beginners to apply what they’ve learned through hands-on coding projects.

Why does the speaker discourage using certain books for Python beginners?

The speaker discourages using certain books for beginners because they contain too much vocabulary and grammar, which can overwhelm and discourage new learners. Such books are more suited for intermediate or advanced users.

What type of projects are included in the *Python Crash Course*?

The projects in *Python Crash Course* include building a Space Invaders game, creating data visualizations, working with APIs, and developing a web app using Django. These projects help beginners apply foundational Python concepts to real-world applications.

Why does the speaker recommend *Python Programming* by John Zelle as the second book?

The speaker recommends *Python Programming* by John Zelle because it provides a thorough introduction to computer science principles, helping learners avoid bad programming habits and strengthening their problem-solving and algorithmic thinking skills.

What approach does the speaker suggest for working through John Zelle’s *Python Programming*?

The speaker suggests attempting the exercises at the end of each chapter and referring back to the relevant sections of the chapter when stuck. This iterative learning process helps learners build a solid understanding of computer science concepts.

What books does the speaker recommend for those interested in computer science and algorithms?

The speaker recommends *Classic Computer Science Problems in Python* and *Algorithms Illuminated* for those interested in computer science and algorithms. These books cover search algorithms, technical interview prep, and basic algorithm concepts.

Which books does the speaker recommend for those interested in data analysis with Python?

For data analysis, the speaker recommends *Learning Scientific Programming with Python* and *Python Tools for Scientists* for broad coverage of scientific and data analysis tools. For learners focused specifically on the pandas library, the speaker suggests *Effective Pandas*.

What advice does the speaker give about borrowing books?

The speaker advises borrowing books from a library first to get a feel for whether or not they are suitable for the learner’s needs, avoiding the need to purchase multiple books before confirming their usefulness.

What is the main benefit of interactive learning, according to the speaker?

The speaker highlights that interactive learning can be up to six times more effective than traditional learning methods because it actively engages the learner in problem-solving and skill-building, rather than passively absorbing information.

Outlines

00:00

📚 Learning Python: The Right Way

The speaker shares their extensive experience with Python books, highlighting the importance of choosing the right material for learning. They emphasize that just like learning English, learning Python should be an iterative process of learning and practicing. The speaker warns against overwhelming beginners with too much information at once, like a dictionary. They recommend 'Python Crash Course' as a great starting point because it covers the basics and then progresses to practical projects, such as building a Space Invaders game, data visualization, working with APIs, and web app development using Django. The book also introduces Git and GitHub and offers advice on text editors and IDEs.

05:00

🔍 Diving Deeper into Python and Computer Science

The speaker discusses the importance of understanding computer science fundamentals when learning Python, regardless of one's specific interests. They recommend 'Python Programming: An Introduction to Computer Science' for its comprehensive introduction to computer science and its role in preventing bad coding habits. The speaker suggests working through exercises at the end of each chapter to solidify understanding. They also provide multiple recommendations for further learning, depending on the learner's interests. For those interested in computer science, they suggest 'Classic Computer Science Problems in Python' and 'Algorithms Illuminated'. For data analysis, they recommend 'Learning Scientific Programming with Python', 'Python Tools for Data Analysis', and 'Effective Pandas'. The speaker also mentions the value of interactive learning and promotes Brilliant.org for its engaging and structured learning approach.

Keywords

💡Python Crash Course

A recommended book for Python beginners, focusing on teaching the fundamentals of Python in an accessible manner. It includes two parts: foundational concepts in the first section and practical projects like creating games, web apps, and data visualizations in the second. This reflects the video’s emphasis on learning by doing.

💡Vocabulary and Grammar

These terms are used metaphorically to describe programming concepts in Python. 'Vocabulary' refers to specific Python syntax and functions, while 'grammar' relates to structuring code correctly. The speaker argues that learning Python is akin to learning a new language—mastering both vocabulary and grammar is crucial but must be accompanied by practice.

💡Interactive Learning

A method of learning that actively engages the learner in problem-solving rather than passively absorbing information. The speaker highlights this concept when recommending Brilliant.org, mentioning that interactive learning can be up to six times more effective than traditional methods. This underlines the importance of hands-on practice in coding.

💡Algorithms

Algorithms are step-by-step procedures for solving problems. The speaker recommends several books focused on algorithms and their importance in both technical interviews and computer science problem-solving. He highlights the role of algorithms in developing algorithmic thinking, a key skill for Python learners.

💡Computer Science Fundamentals

A foundational understanding of how computers work, including topics like data structures, algorithms, and problem-solving techniques. The speaker suggests Python Programming by John Zelle as an essential resource for learning these basics, which are important for effective Python coding and avoiding bad habits.

💡Data Analysis

The process of using programming tools like Python to analyze, interpret, and visualize data. The speaker offers book recommendations for learners interested in using Python for data science or scientific programming, highlighting its widespread use in the field. This concept is central to Python's appeal in the modern data-driven world.

💡Pandas

A popular Python library used for data manipulation and analysis, especially in data science projects. The speaker recommends 'Effective Pandas' as the go-to resource for mastering this library, emphasizing its power and versatility for anyone focusing on data analysis with Python.

💡Practice

Repeated hands-on coding activities to solidify understanding of Python. The speaker stresses that learning Python is an iterative process, much like learning a spoken language. Books like 'Python Crash Course' and interactive platforms like Brilliant.org are recommended for practicing coding skills.

💡Projects

Practical applications of Python concepts learned from books or courses. The speaker emphasizes that Python learning should quickly transition from theory to projects, which help learners apply concepts and build problem-solving skills. Projects mentioned include building games, web apps, and data visualizations.

💡Algorithmic Thinking

A mindset focused on creating efficient solutions to problems by breaking them down into clear, logical steps. The speaker suggests that algorithmic thinking is crucial for Python learners, especially when preparing for technical interviews, and recommends resources to develop this skill.

Highlights

The speaker has read over 100 Python books over several years and shares their top three recommendations.

A dictionary is used as an analogy to explain that just learning Python vocabulary and grammar isn't enough to master it; practice is essential.

The speaker emphasizes that beginners should choose their first book carefully, as some books overwhelm with too much information.

Recommendation 1: 'Python Crash Course' teaches the basics quickly and transitions into practical projects, such as a Space Invaders game, data visualization, and web apps using Django.

Part 1 of 'Python Crash Course' teaches foundations, while part 2 focuses on building projects, making it an ideal beginner's book.

Recommendation 2: 'Python Programming' by John Zelle introduces the basics of computer science and helps develop problem-solving skills.

The speaker advises using 'Python Programming' by attempting the exercises and reading the sections that explain the questions.

The book also helps learners develop algorithmic thinking and avoid bad coding habits.

Recommendation 3: For those interested in computer science and algorithms, 'Classic Computer Science Problems in Python' is recommended.

An alternative to dive deeper into algorithms is 'Algorithms Illuminated', which uses pseudocode to explain various algorithms.

For data analysis, the speaker recommends 'Learning Scientific Programming with Python', which covers tools needed for data analysis and scientific programming.

'Python Tools for Scientists' is another recommended book for those interested in data analysis.

If the focus is solely on learning pandas, the speaker recommends 'Effective Pandas', which covers everything you need to know about working with pandas.

The speaker emphasizes the importance of choosing a book based on personal learning goals and suggests borrowing books from libraries first to see if they are suitable.

Interactive learning, such as that offered by Brilliant.org, can be up to six times more effective than traditional methods.

Transcripts

I've read over a hundred books on python

I mean not all at once and that would be

ridiculous but over the course of years

I've read at least a 100 books on Python

and I want to share my three favorites

with you so these are some of the books

that I've read I don't know you might

recognize a few of those but before I

share with you my three favorites

there's something else that I want to

tell you that I think is even more

important than the three books that I'm

about to recommend so here it

is oh uh I can't actually find the thing

I want to show you in order to

demonstrate this so I'm going to have to

go and get one just bear with me when I

do

[Music]

that do you want to see what's in the

bag let's have a

look

yes it's a dictionary but how is an

English dictionary relevant to learning

python well I'm coming to that so

imagine if you wanted to learn English

and I said what you need to do is get

yourself a nice big dictionary like this

one that has loads of vocab and there's

a section on grammar too I did not know

that do you know what the collective

noun for Apes is it's a shrewdness of

Apes learn all the vocab learn all the

grammar and then you'll know English

that would be terrible advice it's also

terrible advice for learning python

which is why you have to choose your

first book carefully instead you learn a

little bit of vocab a little bit of

grammar and then you practice you

practice speaking and writing and at

first your facility with the language is

nowhere near enough to be able to

communicate the complexity of your

thoughts so you learn a bit more vocab a

bit more grammar and it becomes an

iterative process until you can

communicate exactly what it is that you

want to say and eventually if you're

lucky your ability with language

develops to the point where it helps you

come up with original thoughts and ideas

and it's exactly the same when learning

py which is why as a beginner there are

certain books you should avoid so as

well as giving you three book

recommendations I want to show you how

to recognize what makes a good book for

a

beginner let's start by looking at a

book that's bad for beginners this book

isn't very good for beginners there's

too much vocab too much grammar it's

overwhelming and it's more likely to put

you off that's not to say that it's a

bad book it's just not well suited to

someone that's new to programming and

new to python what you want is something

that gives you enough of the basics the

vocab and the grammar to get you started

on projects as quickly as possible which

is why I like this book what I like

about python crash course is that it's

split into two parts Part One teaches

you the foundations it teaches them

thoroughly but it doesn't linger too

long on them and part two takes what

you've learned and uses it to create

projects part one is that thick that's

all the python you need to know in order

to be able to work on the projects so

you learn the foundations of python in a

few pages and then you start doing

interesting things in part two which is

where all the projects are and the first

project you do is a game and um it's

pretty good actually it's Space Invaders

so you'll be building something like

that you'll also build an interactive

data visualization learn how to work

with apis and build a web app using

Django it'll introduce you to git and

GitHub and give you advice on text

editors and idees so you spend a lot of

time learning how to apply what you've

learned in part one to building projects

which is the whole point of coding in

the first place this really is an

absolutely excellent book for beginners

and it's my first recommendation book

two becomes a little bit more difficult

because learner needs diverge I don't

know why you want to Learn Python maybe

you want to do data analysis maybe you

want to develop web apps and that would

influence the choice of the second book

but this second book I think would be

useful for

everyone whether you want to Learn

Python to do data analysis or whether

you want to do web apps or whether you

want to go into computer science you

should have an understanding of at least

the basics of computer sence because

that will be very useful to you when

you're trying to problem solve further

down the line and that's why I would

recommend this book Python Programming

by John zel gives a very thorough

introduction ction to the basics of

computer science it will help to ensure

that you don't develop any really bad

habits as you teach yourself to code in

Python and it will help you to

understand why things should be done in

a particular way and as you work through

it you'll develop your algorithmic

thinking and problem solving skills and

I think that's an essential step for

anyone that's teaching themselves and

the way I would approach this book

especially if you've already started

with python crash course is go to the

end of each chapter

and attempt the exercises and when you

get stuck go to the section in the

chapter that explains that question or

helps to explain that question go

through every chapter that way and you

will get an overview and a foundation of

computer science that I think will stand

you in very good stead this book

actually is a very old version it even

talks about python one in here somewhere

there's a much newer

Edition the choice for book is well it's

trickier still because it really will

now depend on where your interests lie

so what I'm going to do is I'm going to

recommend more than one book but I'm not

suggesting you get them all just choose

the book depending on what it is that

you want to use Python for so if you

want to carry on in the same vein as

this book with exploring computer

science a bit further I would suggest

this it's called classic computer

science problems in Python and it's the

sort of things that you might get in a

technical interview search algorithms

that kind of thing and if you're

interested in computer science I really

think you'll like this book there is

another one as well if you want to go

down the algorithm route and explore

those algorithms illuminated this is an

excellent introductory book on

algorithms it's not actually in Python

it uses pseudo code to explain the

algorithms maybe you want to use Python

for data analysis and if that's the case

then there really are lots of books to

choose from in fact the choice is so

great that it can be paralyzing but I'm

going to give you three options for this

that won't disappoint so the first two

that give a sort of broad overview of

data science or to use Python for data

analysis are these two learning

scientific programming with python now I

know this says that it's covering

scientific programming but actually what

is covered in here are all the tools

that you would need in order to be able

to use Python for data and analysis so

that's a really good sort of broad book

on the subject and then there's this one

python tools for scientists which is

quite similar really it covers all of

the tools that you would need uh for

science but also for doing data analysis

and uh I really like these two books

although they don't say data analysis or

data science in the title they're

actually very good for learning the

skills that you need to do that however

if it's just pandas that you want to

learn then the best book on pandas that

I have seen is this one effective pandas

this will teach you how to do pretty

much anything you can imagine in pandas

it is a superb pandas book in fact this

is the first edition I think there is

now a second edition so check that

before you get it but if it's pandas

that you want to learn and you're not

interested in learning the other aspects

of data analysis then you don't need to

think twice about it this is the book to

get oh yeah one last thing it's always a

good idea if you can borrow the book

from a library first so you can get a

feel for whether or not it's right for

you did you know that Interactive

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