Monthly Archives: March 2017

Tutorial: Using R for Scalable Data Analytics

March 31, 2017
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Tutorial: Using R for Scalable Data Analytics

At the recent Strata conference in San Jose, several members of the Microsoft Data Science team presented the tutorial Using R for Scalable Data Analytics: Single Machines to Spark Clusters. The materials are all available online, including the presentation slides and hands-on R scripts. You can follow along with the materials at home, using the Data Science Virtual Machine...

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ggedit 0.2.0 is now on CRAN

March 31, 2017
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ggedit 0.2.0 is now on CRAN

Jonathan Sidi, Metrum Research Group We are pleased to announce the release of the ggedit package on CRAN. To install the package you can call the standard R command install.packages('ggedit') The source version is still tracked on github, which has been reorganized to be easier to navigate. To install the dev version: devtools::install_github('metrumresearchgroup/ggedit') What is … Continue...

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The 5 Most Effective Ways to Learn R

March 31, 2017
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Whether you’re plotting a simple time series or building a predictive model for the next election, the R programming language’s flexibility will ensure you have all the capabilities you need to get the job done. In this blog we will take a look at ...

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Delaporte package: The SPARCmonster is sated

March 31, 2017
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Delaporte package: The SPARCmonster is sated

Finally, finally after months of pulling out my hair, the Delaporte project on CRAN passes all of its checks on Solaris SPARC. The last time it did that, it was still using serial C++. Now it uses OpenMP-based parallel Fortran 2003. What a relief! One of these days I should write up what I did Read the...

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Easy leave-one-out cross validation with pipelearner

March 31, 2017
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Easy leave-one-out cross validation with pipelearner

@drsimonj here to show you how to do leave-one-out cross validation using pipelearner.  Leave-one-out cross validation Leave-one-out is a type of cross validation whereby the following is done for each observation in the data: Run model on all other observations Use model to predict value for observation This means that a model is fitted, and a...

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#2: Even Easier Package Registration

March 30, 2017
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Welcome to the second post in rambling random R recommendation series, or R4 for short. Two days ago I posted the initial (actual) post. It provided context for why we need package registration entries (tl;dr: because R CMD check now tests for it, and because it The Right Thing to do, see documentation in the posts). I...

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Take your data frames to the next level.

March 30, 2017
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Take your data frames to the next level.

  While finishing up with R-rockstar Hadley Wickham’s book (Free Book – R for Data Science), the section on model building elaborates on something pretty cool that I had no idea about – list columns. Most of us have probably seen the following data frame column format: df <- data.frame("col_uno" = c(1,2,3),"col_dos" = c('a','b','c'), "col_tres" … Continue...

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March ’17 Tips and Tricks

March 30, 2017
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March ’17 Tips and Tricks

This month’s Tips and Tricks focus is on file navigation. Many of these tips are straightforward - more tip than trick - but they can save quite a bit of time and frustration. Open Recent Please don’t spend time navigating through your folder structure to find a recent project or file. Go to File/Function RStudio automatically indexes...

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March ’17 Tips and Tricks

March 30, 2017
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March ’17 Tips and Tricks

This month’s Tips and Tricks focus is on file navigation. Many of these tips are straightforward - more tip than trick - but they can save quite a bit of time and frustration. Open Recent Please don’t spend time navigating through your folder stru...

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Who is old? Visualizing the concept of prospective ageing with animated population pyramids

March 30, 2017
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Who is old? Visualizing the concept of prospective ageing with animated population pyramids

This post is about illustrating the concept of prospective ageing, a relatively fresh approach in demography to refine our understanding of population ageing. This visualization was created in collaboration with my colleague Michael Boissonneault: ...

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