Blog Archives

5 New R Packages for Data Scientists

August 20, 2015
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5 New R Packages for Data Scientists

by Joseph Rickert One great beauty of the R ecosystem, and perhaps the primary reason for R’s phenomenal growth, is the system for contributing new packages. This, coupled to the rock solid stability of CRAN, R’s primary package repository, gives R a great advantage. However, anyone with enough technical knowhow to formulate a proper submission can contribute a package...

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Using Azure as an R datasource, Part 4 – Pulling data from SQL Server to Linux

August 18, 2015
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Using Azure as an R datasource, Part 4 – Pulling data from SQL Server to Linux

by Gregory Vandenbrouck Software Engineer, Microsoft This post is the fourth in a series that covers pulling data from Microsoft SQL Server or MySQL/MariaDB on Azure to an R client on Windows or Linux. In the previous posts, we covered pulling data from SQL Server to Windows and from MySQL/MariaDB to both Windows and Linux. This time we’ll be...

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R News From JSM 2015

August 13, 2015
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R News From JSM 2015

by Joseph Rickert We can declare 2015 the year that R went mainstream at the JSM. There is no doubt about it, the calculations, visualizations and deep thinking of a great many of the world's statisticians are rendered or expressed in R and the JSM is with the program. In 2013 I was happy to have stumbled into a...

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How do you know if your data has signal?

August 11, 2015
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How do you know if your data has signal?

by Nina Zumel Data Scientist Win-Vector LLC Image by Liz Sullivan, Creative Commons. Source: Wikimedia An all too common approach to modeling in data science is to throw all possible variables at a modeling procedure and "let the algorithm sort it out." This is tempting when you are not sure what are the true causes or predictors of the...

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A simple statnet model of CRAN

August 6, 2015
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A simple statnet model of CRAN

by Joseph Rickert In a recent post on creating JavaScript network graphs directly from R, my colleague and fellow blogger, Andrie de Vries, included a link to a saved graph of CRAN. Here, I will use that same graph (network) to build a simple exponential random graph model using functions from the igraph package, and the network and ergm...

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A Short Introduction to Bioconductor

August 4, 2015
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A Short Introduction to Bioconductor

by Peter Hickey (@PeteHaitch) One of the keys to R's success as a software environment for data analysis is the availability of user-contributed packages. Most useRs will be familiar with (and very grateful for) the Comprehensive R Archive Network (CRAN). The packages available on CRAN, nearly 7000 at last count, cover common data analysis tasks, such as importing data...

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MRAN’s Packages Spotlight

July 30, 2015
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MRAN’s Packages Spotlight

by Joseph Rickert New R packages just keep coming. The following plot, constructed with information from the monthly files on Dirk Eddelbuettel's CRANberries site, shows a plot of the number of new packages released to CRAN between January 1, 2013 and July 27, 2015 by month (not quite 31 months). This is amazing growth! The mean rate is about...

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Efficient Accumulation in R

July 28, 2015
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Efficient Accumulation in R

by John MountData Scientist, Win-Vector LLC R has a number of very good packages for manipulating and aggregating data (plyr, sqldf, RevoScaleR, data.table, and more), but when it comes to accumulating results the beginning R user is often at sea. The...

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Sunbelt XXXV, Social Network Analysis, Statnet and R

July 23, 2015
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Sunbelt XXXV, Social Network Analysis, Statnet and R

by Joseph Rickert The XXXV Sunbelt Conference of the International Network for Social Network Analysis (INSNA) was held last month at Brighton beach in the UK. (And I am still bummed out that I was not there.) A run of 35 conferences is impressive indeed, but the social network analysts have been at it for an even longer time...

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Using Azure as an R datasource Part 3: Pulling data from MySQL/MariaDB to Linux

July 21, 2015
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Using Azure as an R datasource Part 3: Pulling data from MySQL/MariaDB to Linux

by Gregory Vandenbrouck Software Engineer, Microsoft This post is the third in a series that covers pulling data from Microsoft SQL Server or MySQL/MariaDB on Azure to an R client on Windows or Linux. In the previous two, we covered pulling data from SQL Server and MySQL/MariaDB to an R client on Windows. This time we’ll be pulling data...

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