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

##### 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

#### 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

##### 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

###### Statistics

Think Bayes – **free** introduction to **Bayesian statistics** using Python.

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

### Pandas Resources:

- Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

(Not free; see my review) - Learn how to use Pandas in my Pandas Daframe Tutorial. It covers everything from how to read and write Excel files (i.e., CSV and .xlsx) to a dataframe, subsetting, slicing, and much more manipulation of the dataframe. Check it out!
- Learn how to randomly select rows from a dataframe in the Pandas Sample Tutorial

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