Python & R resources

Here is a quite extensive  list of useful links for learning  R and Python. Most of them are free, but you will also find good books that I have found useful. R and Python are both valuable programming languages for scientists. R language has its focus on statistical computing and Python is a more general purpose language.

R programming


The Comprehensive R Archive Network – Here you will find a lot of information and pre-compiled binaries for most operation systems.

Rstudio is the IDE (Integrated development environment) that I find most useful.

Free R books and guides

Introduction to R

An Introduction to R (PDF)

Notes on the use of R for psychology experiments and questionnaires (PDF)

Practical Regression and Anova Using R (PDF)

Using R for psychological research

The R guide (PDF)

Quick-R: Accessing the power of R


Advanced R – companion site for the book. Although it is the companion site for the book you can find a lot of information on R. Useful.


O’Reilly codeschool try R


Introduction to Scientific Programming and Simulation Using R (Chapman & Hall/CRC The R Series) – not free

Advanced R (Chapman & Hall/CRC The R Series) – not free



Python programming language

Integrated Development Environments (IDE)

Scrapy – An easy-to-use open-source (and of course free) tool for extracting data from the web (see my post)

Spyder – a very useful Python IDE. It offers similar functionalities as RStudio. It is a Scientific PYthon Development EnviRonment!

Rodeo – An IDE that is very similar to RStudio.

See my post RStudio-like Python IDEs – Rodeo & Spyder for more information on both Rodeo and Spyder.


Experiment building software

PsychoPy – Free and Open Source Experiment builder written in Python. With PsychoPy you can create experiments by writing your own Python scripts or using its drag-and-drop graphical interface.

Expyriment is more like a library for making generation of experiments easier than using plain Python.

OpenSesame supports, much like PsychoPy, both Python scripting and a graphical interface for creating experiments. OpenSesame lets you choose which back-end you want use. Therefore, the application offer the same functionality as PsychoPy (back-end “Psycho”), Expyriment (back-end Xpyriment) and more (e.g.m OpenGL).

If you are interested in more about all the above mentioned applications (and more) see my posts: Python apps and libraries for creating experiments and Free & Useful Software – PsychoPy.

Free Python books and guides

Dive Into Python

Learn Python The Hard Way


Think Bayesfree introduction to Bayesian statistics using Python.

Think Stats: Probability and Statistics for Programmersfree introduction to Probability and Statistics. Note that, both Think Bayes and Think Stats can be bought (click on the links).

Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
(Not free; see my review)

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