greenteapress.com

Green Tea Press is the publisher of free books by Allen B. Downey, including Think Python, Think Bayes, and other titles. The books are released under free licenses that allow you to copy, distribute, and modify the text, so you can adapt them to different needs and help develop new material. They are available in a variety of electronic formats, and some are also for sale in hard copy.

Who runs it and what it publishes

Green Tea Press is the publisher for Allen B. Downey's books. Its catalog is built around teaching computing, statistics, and data analysis through Python and related tools.

The book catalog

Licensing and formats

The books are available under free licenses that let you copy and distribute the text and modify it. This means you can adapt a book to different needs and help develop new material. They come in a variety of electronic formats, and some titles are also sold in hard copy. If you enjoy the free versions, the site suggests considering buying the author a coffee.

Who these books are for

The catalog spans beginner to intermediate levels. Think Python and Elements of Data Science are aimed at people starting out, including those with no programming experience. Other titles, such as Think Bayes, Think DSP, and Astronomical Data in Python, assume more background in their subject area. Several books include Jupyter notebooks so you can read the text, run the code, and work on exercises in the same place.

Think Python is an introductory programming book by Allen B. Downey, published by Green Tea Press. It is explicitly written as an introduction to programming using Python, which the site describes as "one of the best programming languages for beginners" — so yes, it is designed for beginners with no prior programming experience. The current third edition adds guidance for learning to program with virtual assistants like ChatGPT, and the second edition remains available on the site. Like the other Green Tea Press titles, it is released under a free license that lets you copy, distribute, and modify the text.

Who the book is for

The site's own framing answers the suitability question directly: Think Python: How to Think Like a Computer Scientist is "an introduction to programming using Python." That means it assumes no programming background and teaches programming concepts through Python rather than assuming you already know another language.

It is a reasonable starting point if you:

• Have never programmed before and want a language-agnostic introduction to computational thinking
• Want to learn Python as a first language
• Prefer a book that is free to read, copy, and adapt
• Want material that acknowledges modern AI assistants as part of the learning process (third edition)

It is probably not the right fit if you already program comfortably in another language and want a fast Python reference, or if you want a project-heavy, framework-oriented tutorial rather than a foundations text.

Third edition vs. second edition

The practical difference the site calls out is the third edition's added guidance for working with virtual assistants. If you want to use an AI assistant as a study aid, the third edition is the more current choice. If you specifically want the earlier text, the second edition has not been removed.

How to access it

Green Tea Press states that its books "are available under free licenses that allow you to copy and distribute the text," and that you are also free to modify it. The books come in a variety of electronic formats, and some are also for sale in hard copy. The site does not list prices or require login for the free versions, so treat format and hard-copy availability as things to check on the individual book page rather than assuming a specific price or access condition.

If you find the free version useful, the site suggests considering buying the author a coffee — that is a voluntary gesture, not a condition of access.

Where it sits among the Green Tea Press books

Think Python is one of several Python-oriented titles from the same publisher, so if your goal is broader than "learn to program," you can pick a more targeted entry:

• Think Python — first programming book; start here with no background
• Data Structures and Information Retrieval in Python — data structures organized around building a search engine
• Elements of Data Science — data science for people with no programming experience, with Jupyter notebooks
• Think Bayes — Bayesian statistics using simple Python programs
• Think Stats — exploratory data analysis with NumPy, SciPy, Pandas, and StatsModels
• Think DSP — digital signal processing for sound and image processing
• Think Complexity 2e — complexity science, including small-world graphs
• Astronomical Data in Python — working with astronomical data, including SQL joins and Astropy

For a true beginner, Think Python is the intended entry point; the others assume you can already write and run Python code.

A practical way to test whether it suits you

Before committing, read the first chapter and try to run one small program. If the explanations of variables, expressions, and functions make sense without you needing outside help, the book's level matches yours. If you find yourself reaching for a separate Python installation guide more than the book itself, that is normal for a first book — the text teaches programming, not environment setup. The third edition's virtual-assistant guidance is aimed at exactly this kind of moment, where you want to ask a tool a clarifying question while working through an exercise.

Pick by your goal: Think Python if you are new to programming, Elements of Data Science if you want data science without prior coding, Think Stats or Think Bayes if you already write some Python and want statistics, and the specialized titles (Think DSP, Think Complexity, Astronomical Data in Python, Data Structures and Information Retrieval in Python) if you have a specific subject in mind. All of these are published by Green Tea Press under free licenses that let you copy, distribute, and modify the text, and they are available in a variety of electronic formats, with some also sold in hard copy.

Start here if you are new to programming

Think Python: How to Think Like a Computer Scientist is described as an introduction to programming using Python, "one of the best programming languages for beginners." The third edition includes guidance for learning to program with virtual assistants like ChatGPT. The second edition is still available on the site if you prefer it or your course uses it.

Choose this if you have never programmed and want a general foundation before specializing.

Start here if you want data science but have no coding background

Elements of Data Science is an introduction to data science designed for people with no programming experience. It presents a small, powerful subset of Python meant to let you do real work in data science as quickly as possible, and it includes Jupyter notebooks where you can read the text, run the code, and work on exercises.

Choose this over Think Python if your end goal is analyzing data rather than general programming, and you would rather learn a focused slice of Python than the whole language.

If you already write some Python and want statistics

Two books split this ground:

• Think Stats: Exploratory Data Analysis — an introduction to exploratory data analysis that emphasizes simple computational tools for exploring real data. It includes regression, time series analysis, and survival analysis, and presents basic use of NumPy, SciPy, Pandas, and StatsModels.
• Think Bayes: Bayesian Statistics in Python — an introduction to Bayesian statistics using simple Python programs instead of complicated math.

Choose Think Stats if you want to describe and explore data you already have. Choose Think Bayes if you specifically want the Bayesian approach and are comfortable enough with Python that the programming will not slow you down.

If you have a specific subject in mind

How to access and use the books

The books are available under free licenses that allow you to copy and distribute the text, and you are also free to modify it, so you can adapt the books to different needs and help develop new material. They come in a variety of electronic formats, and some are also for sale in hard copy. If you are enjoying the free versions, the site suggests considering buying the author a coffee.

A practical way to decide: open the free electronic version of your top candidate, check whether the first chapter matches your current level, and only then commit. If the first chapter assumes more Python than you have, step back one title — for example, from Think Bayes to Think Python, or from Think Stats to Elements of Data Science.

Green Tea Press publishes books by Allen B. Downey, including Think Python, Think Bayes, and others, under free licenses that let you copy, distribute, and modify the text. You can access them in a variety of electronic formats, and some titles are also sold in hard copy. If you want to adapt a book for a course, translate it, or build new material from it, the license already permits that — you do not need to request permission first.

What the free license allows

According to the site, the books are available under free licenses that allow you to:

• Copy the text
• Distribute it
• Modify it, so you can adapt the books to different needs
• Help develop new material based on them

This is broader than "read online for free." It means you can reuse and remix the content, which is useful if you teach a course, run a study group, or want to extend a chapter with your own examples.

How to access the books

The books are offered in a variety of electronic formats. The site does not list a single download page in the material provided, so the practical path is to start from the Green Tea Press homepage and follow the link for the specific title you want.

Some titles are also for sale in hard copy. That means you have two options for the same book: a free electronic version, and a paid physical version if you prefer paper.

Titles available

The homepage groups the books mainly by topic. The titles named on the site include:

The second edition of Think Python is also still available on the site.

A practical way to use them

If you are learning on your own, a workable approach is:

1. Pick the title that matches your goal — for example, Think Python if you are new to programming, or Think Stats if you already write some Python and want to work with real data.
2. Open the electronic version and check whether it includes Jupyter notebooks. Elements of Data Science and Astronomical Data in Python both do, which means you can read the text, run the code, and do exercises in the same place.
3. If you plan to teach or adapt the material, note that the license already covers modification, so you can reorganize chapters or replace examples without seeking separate approval.

Supporting the project

The site asks readers who enjoy the free versions to consider buying the author a coffee. This is optional and separate from the license — the books remain free to copy, distribute, and modify regardless.

What is not stated

The provided material does not specify prices for the hard-copy editions, which electronic formats are offered for each title, or whether any content requires a login. Treat those details as unconfirmed until you check the individual book page.

Two Green Tea Press titles explicitly include Jupyter notebooks: Elements of Data Science and Astronomical Data in Python. In both cases the notebooks are designed so you can read the text, run the code, and work on exercises in the same environment. Other Green Tea Press books are available in a variety of electronic formats, but the site does not state that they ship with notebooks.

Books with Jupyter notebooks

Elements of Data Science

This book is aimed at readers with no programming background. It presents a small, powerful subset of Python intended to let you do real data science work quickly. The notebooks are the delivery mechanism for that approach: instead of reading code in isolation, you run it and then attempt the exercises.

Topics in the astronomical title give a sense of the level of the hands-on material: SQL queries with complex joins, Astropy and Pandas, coordinates and other quantities with units, and visualizing data.

Astronomical Data in Python

This one assumes you want to apply Python to a specific domain rather than learn programming from scratch. The notebook format matters here because the exercises involve real data operations — joins, coordinate handling, and plotting — that are easier to understand by executing them than by reading about them.

What the notebooks let you do

• Read the explanatory text alongside the code
• Run the code cells and see output immediately
• Work on exercises to practice what you just read

That combination is the main reason to prefer these two titles if your goal is practice rather than reference reading.

What about the other books?

Green Tea Press publishes Think Python, Think Bayes, Think Stats, Think DSP, Think Complexity, Data Structures and Information Retrieval in Python, and others. The site says these books are available in a variety of electronic formats, and some are also for sale in hard copy. It does not claim that they include Jupyter notebooks, so treat notebook support as specific to the two titles above unless you confirm otherwise on the individual book pages.

How to get started

1. Go to greenteapress.com and open the page for Elements of Data Science or Astronomical Data in Python.
2. Download the electronic version offered there.
3. Open the notebook files in a Jupyter environment and run the cells as you read.
4. Attempt the exercises before moving to the next section.

If you have no programming experience, start with Elements of Data Science. If you already write Python and work with scientific or astronomical data, Astronomical Data in Python is the more direct fit.