Building DataMind: FREE Online Interactive Learning Plaftorm for R

July 11, 2013
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Building DataMind: FREE Online Interactive Learning Plaftorm for R

DataMind is the first free interactive online learning platform for R. Through an in-browser coding environment we offer exercise-based learning-by-doing. Our goal is to build a fun learning experience for data analysis and R, while allowing anyone to create courses! You can check out an early stage beta version at www.DataMind.org ! With DataMind, we focus on three

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A Julia Meta Tutorial

July 11, 2013
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A Julia Meta Tutorial

If you are thinking about taking Julia, the hot new mathematical, statistical, and data-oriented programming language, for a test drive, you might need a little bit of help. In this blog we round up some great posts discussing various aspects … Continue reading → The post A Julia Meta Tutorial appeared first on Data Community DC.

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TriMatch – useR! 2013 Slides and Version 0.9 Released to CRAN

July 11, 2013
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TriMatch – useR! 2013 Slides and Version 0.9 Released to CRAN

Our presentation on the TriMatch package at the useR! 2013 Conference went fantastically. Thanks for those who attended and the wonderful discussion that followed. The slides can be downloaded from Github as well as the abstract. To coincide with our presentation version 0.9 has been released to CRAN. The package includes a vignette and two demos. install.packages('TriMatch',repos='http://cran.r-project.org') require(TriMatch) vignette('TriMatch') demo(tutoring) demo(nmes)

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A Julia Meta Tutorial

July 11, 2013
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A Julia Meta Tutorial

If you are thinking about taking Julia, the hot new mathematical, statistical, and data-oriented programming language, for a test drive, you might need a little bit of help. In this blog we round up some great posts discussing various aspects of Julia to get you up and running faster. Why We Created Julia If only you...

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Expected Points by Position Rank in Fantasy Football

July 10, 2013
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Expected Points by Position Rank in Fantasy Football

In this post, I calculate the expected fantasy points scored by players based on their position and position rank.  This post is modeled after a post by Chase Stuart (see here and The post Expected Points by Position Rank in Fantasy Football appeared first on Fantasy Football Analytics.

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Expected Points by Position Rank in Fantasy Football

July 10, 2013
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Expected Points by Position Rank in Fantasy Football

In this post, I calculate the expected fantasy points scored by players based on their position and position rank.  This post is modeled after a post by Chase Stuart (see here), where he calculated players' expected fantasy points as a functi...

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UseR! 2013 – Day 1 notes

July 10, 2013
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UseR! 2013 – Day 1 notes

Hadley Wickham presents at the useR! 2013 conference, July 10 2013 Today marked the first day of the 2103 useR! conference, a gathering of more than 350 R users from around the world. The conference has been quite a success so far, kicking off yesterday with a day of tutorials followed by a tapas-fueled welcome party in the center...

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Analyse discriminante linéaire ou Regression logistique

July 10, 2013
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Analyse discriminante linéaire ou Regression logistique

Supposons que l'on dispose d'iris de Paris (en population >100khabts) et qu'on veuille pouvoir les classer selon leurs caractéristiques sociodémos : Population taux de chômage Etudiants CSP etc... Une fois, les iris classés, on se demande si l'on peut transporter cette typologie à une autre grande ville (Lyon) par exemple : Il faudrait alors pouvoir utiliser un modèle d'affectation des iris selon leurs caractéristiques respectives...

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Visualizing a tiny slice of India’s demographics with information from Wikipedia

July 10, 2013
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Visualizing a tiny slice of India’s demographics with information from Wikipedia

This post presents a tiny slice of a complex and diverse India using charts. (Data retrieval from Wikipedia on 9 July, 2013 and the analysis were performed using R; charts were generated using ggplot2, googleVis and wordcloud. More information can be f...

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rCharts version of d3 horizon

July 10, 2013
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rCharts version of d3 horizon

I love horizon plots.  My love shows up throughout my blog, and I have plotted horizon charts in base graphics, xtsExtra, lattice, and ggplot2.  Now with rCharts, we can implement Jason Davies d3.js horizon chart plugin to plot R data in...

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Parallel Random Number Generation using TRNG

July 10, 2013
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Parallel Random Number Generation using TRNG

To my surprise and disappointment, popular scientific libraries like Boost or GSL provide no native support for parallel random number generation. Recently I came across TRNG, an excellent random number generation library for C++ built specifically with parallel architectures in mind. Over the last few days I’ve been trawling internet forums and reading discussions about The post Parallel...

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Please send all comments to /dev/ripley

July 10, 2013
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Please send all comments to /dev/ripley

Trey Causey asks, Has R-help gotten meaner over time?: I began by using Scrapy to download all the e-mails sent to R-help between April 1997 (the earliest available archive) and December 2012. . . . We each read 500 messages and coded them in the following categories: -2 Negative and unhelpful -1 Negative but helpful The post Please...

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Types in lambda.r versus classes in S4

July 10, 2013
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Types in lambda.r versus classes in S4

Here’s a quick example of the power of lambda.r and how it simplifies the programming model. On the r-devel mailing …Continue reading »

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UK dialect maps

July 10, 2013
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UK dialect maps

A few weeks ago Joshua Katz published some awesome dialect maps of the United States with the help of a web interface coded with Shiny. Now we propose a similar setup for the UK data based on our rapporter.net "R-as-a-Service" with some further add-ons, like regional comparison and dynamic textual analysis of the differences: You may...

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Flotsam 13: early July links

July 9, 2013
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Man flu kept me at home today, so I decided to do something ‘useful’ and go for a linkathon: Ed Yong discusses the effect of subject expectations in psychology experiments Nice Results, But What Did You Expect? At the beginning there was another article on The placebo phenomenon, and another one on The placebo defect.

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2013-7 Advanced SVG Graphics from R

July 9, 2013
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The gridSVG package has recently provided an interface for some more advanced SVG graphics features: gradient fills and pattern fills, clipping paths, masks, and filters. This report describes a simple test case for some of these advanced graphics features and … Continue reading →

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A Sudoku Puzzle Solver – attempt 1

July 9, 2013
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A Sudoku Puzzle Solver – attempt 1

I have programmed up a R based Sudoku problem solver for Sudoku puzzles of that only require simple inference.  In these puzzles a solution can be found using only first order inference.  This solver can be found at the end of the code locate...

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%in%

July 9, 2013
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I just stumbled across a really useful infix function in R: %in%. It compares two vectors and returs a logical vector if there is a match or not for its left operand. Let us look at some examples: > 1:10 %in% c(1,3,5,9) TRUE FALSE TRUE...

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user2013: The caret tutorial

July 9, 2013
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user2013: The caret tutorial

This afternoon I went to Max Kuhn’s tutorial on his caret package. caret stands for classification and regression (something beginning with e) trees. It provides a consistent interface to nearly 150 different models in R, in much the same way as the plyr package provides a consistent interface to the apply functions. The basic usage

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user2013: The Rcpp tutorial

July 9, 2013
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user2013: The Rcpp tutorial

I’m at user 2013, and this morning I attended Hadley Wickham and Romain Francois’s tutorial on the Rcpp package for calling C++ code from R. I’ve spent the last eight years avoiding C++ afer having nightmares about obscure pointer bugs, so I went into the room slightly skeptical about this package. I think the most

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X+1 uses Revolution R Enterprise for Marketing Optimization

July 9, 2013
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X+1 uses Revolution R Enterprise for Marketing Optimization

In a recent article at Statistics View, Lillian Pierson describes how the X+1 Origin Digital Marketing Hub helps companies like JP Morgan Chase and Verizon optimize their marketing efforts. Back in 2011, X+1 saw the need to update their analytics platform to deal with increasing data sizes and to serve the increasingly sophisticated needs of their marketing clients: What...

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A Rough Guide to Data Science

July 9, 2013
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A Rough Guide to Data Science

If Big Data was last year's buzzword, Data Science may reach the same level of hype this year. There's no shortage of discussion about the high demand for data scientists, the term's usefulness as a designation, and even declarations of its "sexiness" as a career. And as with many terms that reach a critical mass on social media, data...

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For faster R use OpenBLAS instead: better than ATLAS, trivial to switch to on Ubuntu

July 9, 2013
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R speeds up when the Basic Linear Algebra System (BLAS) it uses is well tuned. The reference BLAS that comes with R and Ubuntu isn't very fast. On my machine, it takes 9 minutes to run a well known R benchmarking script. If I use ATLAS, an optimized BLAS that can be easily installed, the

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For faster R use OpenBLAS instead: better than ATLAS, trivial to switch to on Ubuntu

July 9, 2013
By

R speeds up when the Basic Linear Algebra System (BLAS) it uses is well tuned. The reference BLAS that comes with R and Ubuntu isn’t very fast. On my machine, it takes 9 minutes to run a well known R … Continue reading →

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Exploratory Data Analysis: Conceptual Foundations of Histograms – Illustrated with New York’s Ozone Pollution Data

Exploratory Data Analysis: Conceptual Foundations of Histograms – Illustrated with New York’s Ozone Pollution Data

Introduction Continuing my recent series on exploratory data analysis (EDA), today’s post focuses on histograms, which are very useful plots for visualizing the distribution of a data set.  I will discuss how histograms are constructed and use histograms to assess the distribution of the “Ozone” data from the built-in “airquality” data set in R.  In

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Unicode Tips in Python 2 and R

July 9, 2013
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Unicode Tips in Python 2 and R

Most of time, I don’t need to deal with different encodings at all. When possible, I use ASCII characters. And when there is a little processing in Chinese characters or other Unicode characters, I use .Net languages or JVM languages, in which every string is Unicode and of course when the characters are displayed they are displayed as characters...

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googleVis tutorial at useR!2013

July 9, 2013
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googleVis tutorial at useR!2013

Today Diego and I will give our googleVis tutorial at useR!2013 in Albacete, Spain.googleVis Tutorial at useR! 2013We will cover:Introduction and motivationGoogle Chart ToolsR package googleVisConcepts of googleVisCase studiesgoogleVis on shiny

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A possibility for use R and Hadoop together

July 8, 2013
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(This article was first published on Milano R net, and kindly contributed to R-bloggers) As mentioned in the previous article, a possibility for dealing with some Big Data problems is to integrate R within the Hadoop ecosystem. Therefore, it’s necessary to have a bridge between the two environments. It means that R should be capable of handling data the...

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Modeling Residential Electricity Usage with R – Part 2

July 8, 2013
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Modeling Residential Electricity Usage with R – Part 2

(This article was first published on Commodity Stat Arb, and kindly contributed to R-bloggers) I can’t believe it has been nearly 6 months since I last posted.  Given the sustained heat it seemed like a good idea to finish off this subject. As hinted at in my last post, temperature is the missing variable to make sense of Residential...

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