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This isn't a problem most of us run into every day, but when we do, it sure is nice to know the answer! Here's some helpful information on how to load really large files into R.
The title says it all. If you're using R, you should be using RStudio, too. If you're using RStudio, you may be curious how to offload some processing into the cloud. Read this post to learn how.
mintgene offers advice on use of fixed colors for visualizations -- complete with R code.
An essential tour of the many "do by" functions in the R language.
This is a bare-bones introduction to ggplot2, a visualization package in R. It assumes no knowledge of R and teaches the minimum you’ll need to know.
Demonstrating the law of large numbers with #rstats code
"R-bloggers.com is now two years young. The site is an (unofficial) online R journal written by bloggers who agreed to contribute their R articles to the site.
Advice on how to gather data via web-scrapping to R via notes from a recent Pycon presentation. Helpful links and other resources.
Ever had a list of IP addresses that you want to find the geographic location for? Here's an R wrapper function to a web-service that will provide you with just that!
For Windows OS users who want to run a statistical analysis infrastructure from a portable USB drive... here's what you need to know.
'“Statistics with R” is a great R graphics & stats website. It provides lots of R examples, covering many analytics topics. It is also available as a PDF document to download at the website, as well as the R codes.'
"Fitting distribution with R is something I have to do once in a while.
A good starting point to learn more about distribution fitting with R is Vito Ricci's tutorial on CRAN. I also find the vignettes of the actuar and fitdistrplus package a good read. I haven't looked into the recently published Handbook of fitting statistical distributions with R, by Z. Karian and E.J. Dudewicz, but it might be worthwhile in certain cases, see Xi'An's review. A more comprehensive overview of the various R packages is given by the CRAN Task View: Probability Distributions, maintained by Christophe Dutang.
do you decide which distribution might be a good starting point?"
Read this post to find out.
"I really love the plyr package. Apart from having a progress bar and plyr handeling a lot of the overhead, a very interesting feature is being able to run plyr in parallel mode. Essentially, setting .parallel = TRUE runs any plyr function in parallel. This is under the assumption that a parallel backend was registered. In my case, I use the doSNOW package to register a backend that uses the Simple Network of Workstations (SNOW) package for parallel computing."
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"This is a continuation of the R workshop I'm teaching at the Baruch MFE program. This section discusses the programming model of R in a slightly biased way."
This is probably the single most amazing graphic I've seen produced directly out of R before. Here's a description from the author:
"The above map (and this one) was produced using R and ggplot2 and serve to demonstrate just how sophisticated R visualisations can be. We are used to seeing similar maps produced with conventional GIS platforms or software such as Processing but I hadn’t yet seen one from the R community (feel free to suggest some in the comments). The map contains three layers: buildings, water and the journey segments. The most challenging aspect was to change the standard line ends in geom_segment from “butt” to “round” in order that the lines appeared continuous and not with “cracks” in, see below."
I use R as my primarily tool for data collection, data cleansing, agent-base modeling (simulations), and data analysis. I like findings posts like this with helpful pointers on functions and language I'm unfamiliar with.
Read on for a quick intro to: merge_all, mutate, colwise, and "higher order functions".
I like this post because it shows a catchy way of illustrating an algorithm. Follow the links to grab the code and learn how to create you own animations with rstats.
"Google offers an access to its services with Apps Scripts (JavaScript). That gives you a possibility to connect your spreadsheet to a fascinating variety of tools like geocoder, stock info, language translator, or email.
My java-scripting abilities are rather limited but just playing with tutorial examples I was quickly able to produce a script analyzing time distribution of received emails. It looks through your Gmail for the given contact and record the times of emails sent by it."
"The followings introductory post is intended for new users of R. It deals with the restructuring of data: what it is and how to perform it using base R functions and the {reshape} package.
Example of power of #rstats and ggplot2 - Homicides in Mexico 2010
The followings introductory post is intended for new users of R. It deals with R data frames: what they are, and how to create, view, and update them.
R user Josh Reich, who we've featured here on the blog before, is also the CEO and co-founder of the new user-friendly bank, Simple. (Confidential to Josh -- still waiting on my invite...).
There is a massive mismatch between how money is being spent and the support needed for activities that will create business value from data. The problem is an enduring fetish to store big data without making plans for how it will be used.
"What makes this book different from other books about R is stated clearly by the author Norman Matloff in the introduction:
"This is the first walk-through I have posted. Reading these types of posts has been incredibly helpful as I have been learning R and other useful tools in the Unix universe. Hopefully you find it helpful.
First, I have been watching Google Python Videos the last couple days and they have a coding assignment using Social Security Administration Data Baby Names. Not having the downloads for the course I thought it would be a good python exercise to try to get the same data.
So, my interest in baby names has nothing to do with any impending life decision(or any recent drunken decisions). You can get the python script and the R we are going to use here. Also the csv file we are going to use can also be downloaded here. Also if you are interested in more baby name projects and a web scrapper written in R/Ruby check out Hadley Wickham’s project."
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