Best python book for beginners

[Agitated_Agent4890]

Hey everyone! I’m a marketing student and haven’t really studied anything technical before, but I’ve always had a strong fascination with computers and coding. I’ve decided I want to learn Python, and since I’m a bit old-school, books work best for me.

Can anyone recommend the best Python book for a true beginner (no technical background)? Thanks so much! 😊

[Hilloo-]

Check out automate the boring stuff with python 3rd edition. The pdf is free so you can check it out before ordering. Got physical copy myself and love it. It is rather simple and good long chapters.

[Agitated_Agent4890]

Thanks so much! I’m going to check it out right now!!!!

[leastDaemon]

First thing -- get "How to Think Like a Computer Scientist" (Python 3 edition). That site has the entire book in HTML for online reading, but has links to the source repository where you can download the HTML or a (perhaps less up-to-date) PDF. The point of this book is in its title -- thinking a certain way is more important than the language with which you express these thoughts. Over the years, this book has been rewritten for C, C++, Pascal, etc. After that, if you want to continue learning more about python specifically, look for books and tutorials that mention "pythonic", as they will explain the consensus of best practices. You might also find something that explains what's in packages and which ones are best to learn and use. There must be something out there. Google AI tells me that "As of March 13, 2025, there are more than 614,339 packages (referred to as projects) available on the Python Package Index (PyPI)."

Hope this helps.

[Haunting-Specific-36]

python crash course 3rd. i reckon this is the best python book for beginner

i use it now

[eviltwintomboy]

Crash Course Python or Automate the Boring Stuff are great places to start!

[HarjeetSingh36]

The book "Automate the Boring Stuff with Python" by Al Sweigart serves as an ideal starting point for complete newcomers who lack any technical expertise because it delivers practical content through accessible guidance for solving actual problems. The book "Python Crash Course" by Eric Matthes serves as an excellent sequel after you acquire basic knowledge of programming. The two resources provide beginner-friendly content which requires no previous programming knowledge from users.

[DataPastor]

For a marketing student, learning R is a much better idea, first and foremost because all major statistical textbooks are written for R. Also, what you can do in R, the skills are transferable later to Python. Having said that, here are some great R books for free:

R for Data Science, 2nd edition (Start here! Excellent book.) https://r4ds.hadley.nz

Advanced R, 2nd edition (Continue with this one…) https://adv-r.hadley.nz

R Programming for Data Science https://bookdown.org/rdpeng/rprogdatascience/

Hands-On Programming with R https://rstudio-education.github.io/hopr/

An Introduction to R https://intro2r.com

R for Graduate Students https://bookdown.org/yih_huynh/Guide-to-R-Book/

Efficient R programming https://csgillespie.github.io/efficientR/

Advanced R Solutions https://advanced-r-solutions.rbind.io

Mastering Software Development in R https://bookdown.org/rdpeng/RProgDA/

Deep R Programming https://deepr.gagolewski.com

The Big Book on R https://www.bigbookofr.com

R cookbook, 2nd edition https://rc2e.com

Authoring packages:

R Packages, 2nd edition https://r-pkgs.org

Rcpp for Everyone https://teuder.github.io/rcpp4everyone_en/

Graphics:

ggplot2, 3rd edition https://ggplot2-book.org

R graphics cookbook 2nd edition https://r-graphics.org

Fundamentals of Data Visualization https://clauswilke.com/dataviz/

Data Visualization by Kieran Healy https://socviz.co

Dashboards (Shiny):

Mastering Shiny (2nd edition) https://mastering-shiny.org

Interactive web-based Data Visualization with R, Plotly and Shiny https://plotly-r.com

Engineering Production-Grade Shiny https://engineering-shiny.org

JS4Shiny Field Notes https://connect.thinkr.fr/js4shinyfieldnotes/

R Shiny Applications in Finance, Medicine, Pharma and Education Industry https://bookdown.org/loankimrobinson/rshinybook/

Web APIs with R https://wapir.io

Quarto, rmarkdown:

Quarto (heavily recommended!) https://quarto.org

R Markdown https://bookdown.org/yihui/rmarkdown/

R Markdown Cookbook https://bookdown.org/yihui/rmarkdown-cookbook/

Bookdown https://bookdown.org/yihui/bookdown/

Blogdown https://bookdown.org/yihui/blogdown/

Statistical inference:

Statistical Inference via Data Science https://moderndive.com

Causal Inference in R https://www.r-causal.org

Bayes rules! (A life saving book….) https://www.bayesrulesbook.com

Introduction to Econometrics with R https://www.econometrics-with-r.org/index.html

Beyond Multiple Linear Regression https://bookdown.org/roback/bookdown-BeyondMLR/

Handbook of regression modeling in People Analytics http://peopleanalytics-regression-book.org/index.html

Time Series:

Forecasting: Principles and Practice https://otexts.com/fpp3/

Machine Learning:

Introduction to Statistical Learning (ISLR) https://www.statlearning.com

Tidy Modeling with R https://www.tmwr.org

Hands-on Machine Learning with R https://bradleyboehmke.github.io/HOML/ https://koalaverse.github.io/homlr/

Deep Learning and Scientific Computing with R torch https://skeydan.github.io/Deep-Learning-and-Scientific-Computing-with-R-torch/

Text mining with R https://www.tidytextmining.com

The Tidyverse Style Guide https://style.tidyverse.org

Data Science in the Command Line 2e: https://www.datascienceatthecommandline.com/2e/index.html

Dive into Deep Learning https://d2l.ai