Computational Linguist's Lair

Computers. Linguistics. Lots of R. Maybe some Python. ... Definitely still work in progress, open for ideas (submit below).

[things-about-r]

If you read some of my last blog post you may notice that R got a new companion called Tableau. Tableau is an easy to use and mighty BI toolbox for visualizing all kinds of data and I suggest everybody to give it a trial.

[compling-blog-blog]

As I’m more or less an autodidact when it comes to statistics, I have a weak spot for books that try to introduce statistics in an accessible and pedagogical way. I have therefore collected what I believe are all books that introduces statistics using comics (at least those written in English). What follows are highly subjective reviews of those four books: ...

[datajournalismlinks]

This post outlines a 7-step Dataviz Design Process. My goal is to give you a behind-the-scenes look into the design process so that you feel armed and ready to begin editing your own charts", by Ann K. Emery

[compling-blog-blog]

Lots of graphics and other kinds of examples.

From a comment:

This is one of the clearest process pieces I’ve seen regarding dataviz design.

[compling-blog-blog]

Collaborative data science in the cloud based on R - Statace.com

StatAce is an easy-to-use online data science platform that saves you time and effort. Use point-and-click, work with large data, or use it from your tablet. StatAce facilitates collaboration and tracks the changes to your files.

Very modern, has multiple features, (only) the private "environment" is free (max. 1GB RAM).

Excerpt from a testimonial:

Teaching in R

After switching to StatAce, a university professor saw that students became more engaged with her introduction to R course. They like our interface and the fact that they can access StatAce from any device without installing software.

[datajournalismlinks]

Resources - both online and books - that have helped the most while learning R (- a book review article -):

R for Everyone: Advanced Analytics and Graphics – Jared P. Lander

The R Book - Michael J. Crawley

An Introduction to Statistical Learning: with Applications in R - Gareth James et al.

Machine Learning with R - Brett Lantz

R and Data Mining: Examples and Case Studies – Yanchang Zhao

Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!) - Graham Williams

ggplot2: Elegant Graphics for Data Analysis (Use R!) – Hadley Wickham

The Art of R Programming : A Tour of Statistical Software Design - Norman Matloff

Code School : Try R

Coursera : R Programming - Roger D. Peng

Lynda.com : R Statistics Essential Training  – Barton Poulson

UCI Machine Learning Repository

(Read more...)

[compling-blog-blog]

The mission of OpenIntro is to make educational products that are free, transparent, and lower barriers to education.

OpenIntro Labs promote the understanding and application of statistics through applied data analysis.

OpenIntro creates publically available resources for statistics learners, e.g. R courses (mostly pdf + acompanying files), whole textbooks, such as the main 'OpenIntro Statistics' book, videos, data sets, teaching material and more.

Looks terrific, really can't say why I don't already know this.

[compling-blog-blog]

www.R-fiddle.org is an early stage beta that provides you with a free and powerful environment to write, run and share R-code right inside your browser. It even offers the option to include packages. Since a couple of days it’s gaining more and more traction, and was mentioned on the frontpage of Hacker News.

(Read more.)

Sandboxes like these have been proven to be extremely helpful for other programming languages - as soon as R-Fiddle is fully developed, it will become an essential assistant to all who want to share R code online in order to give others a chance to try it out themselves.

Here is what you can expect and do (from lsauer.com):

Collaborative Editing

Save

Embed: Graphs can be shown along with a console and are render live so to speak

Share

Run (but obviously not install new packages or any of that sorts)

Graph and save the plots

Adapt the editor to your needs

Here is what you cannot expect

No sandboxing or limitations you would entertain on a local R setup

expect everything to work fine

instant execution (they are adding more servers currently)

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Rdocumentation is the fastest and easiest way to search through the documentation and manuals of R packages and functions, ranked by popularity.

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DataCamp is a free online interactive learning platform for data analytics. Think of it as Codecademy, but for data science. Our mission is to provide the world with the data analysts it needs by offering affordable, interactive data analysis training.

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- This is the in-progress book site for "Advanced R development". The book is designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R's quirks and shows how some parts that seem horrible do have a positive side.

One of Hadley Wickham's many fruitful projects, definitely something to keep an eye on!

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Do you know any universities or colleges that offer helpful resources for R users and R learners? (Anyway, I got you some examples to get started.)

Here's what I've found so far:

a multiple hour video "Introduction to R Programming" from Lane Medical Library at Stanford University (Youtube)

the rather comprehensive "R Resources" collection from Weill Cornell Medical College

Slides to the "Introduction to Programming in R" course at The Institute for Quantitative Social Science at Harvard University

Doesn't that look inspiring to you? Or have you already been inspired beforehand and are you already giving R classes at your school/college/university/...? Or do you know any other universities who are sharing their high-quality R resources with the public?

Share your stories and information here, the community will love you for it!

[compling-blog-blog]

60+ R resources to improve your data skills

From books to videos to online tutorials -- most free! -- here are plenty of ideas to burnish your R knowledge.

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Very clean, comprehensive and helpful blog run by a professional.

Are you using R? Do you want write nice R code? By ‘nicer’ we mean code that is easy to write, is easy to read, runs fast, gives reliable results, is easy to reuse in new projects, and is easy to share with collaborators. At the nice R code site, we are trying to help researchers (mostly biologists) get the most out of their code by communicating the elements of work flow and good coding habits that help transform code from messy to nice. (...)

[compling-blog-blog]

The knitr package was designed to be a transparent engine for dynamic report generation with R, solve some long-standing problems in Sweave, and combine features in other add-on packages into one package (knitr ≈ Sweave + cacheSweave + pgfSweave + weaver + animation::saveLatex + R2HTML::RweaveHTML + highlight::HighlightWeaveLatex + 0.2 * brew + 0.1 * SweaveListingUtils + more).

knitr is a relatively new R package for general-purpose dynamic report generation - especially helpful to all those who are used to writing in latex!

[compling-blog-blog]

Visualization is an essential part of a data analyst's toolkit. When you're in the exploratory phase of data analysis, visualizations can help you understand data and find patterns in it. Later, when you want to present the data to others, visualizations are essential for efficiently communicating your findings. In this webcast presented by Winston Chang, author of R graphics Cookbook, you'll learn the basics of how to create data graphics using R and the popular ggplot2 package.

One-hour webcast with Winston Chang, member of the RStudio team and avid R enthusiast.

[compling-blog-blog]

The School of Data aims to make your learning experience as tailored as possible through independent learning modules. Learning modules are all stand-alone and can be taken in any order. To make your learning experience easier, we curated modules into a series of courses - with a focus on data basics as well as specific skills. When you identified the course you're interested in click on "Show Modules" to see all modules you might want to take. - See more at schoolofdata.org

[datajournalismlinks]

The Sunlight Foundation’s Amy Cesal set data visualization style guidelines - which she thinks is better than creating templates: “it’s impossible to pre-design every chart. And by not forcing everyone to adopt the same technology, but allowing them to continue using what they are comfortable with, we’ve had more people accept this system. It’s easier to create things, so we’ve been doing it more often. And our branding is stronger and more recognizable.”