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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. For sure, R and Python are both valuable programming languages for scientists. The R language has its focus on statistical computing whereas Python is a more general purpose language.

R programming

Software

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

R Excel Tutorial: How to Read and Write xlsx files in R

Advanced

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.

Courses

O’Reilly codeschool try R

Books

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

Software/Packages

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

Statistics

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).

Pandas Resources:

Pandas is a great package that makes data manipulation, descriptive statistics, data visualization, amongst other things very easy to perform, Below are some Pandas dataframe tutorials, how to read and write data (e.g., SPSS, Excel, CSV, HTML tables, and JSON files).

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