Blog Archives

Big data for R

August 5, 2010
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Big data for R

Revolutions Analytics recently announced their "big data" solution for R. This is great news and a lovely piece of work by the team at Revolutions. However, if you want to replicate their analysis in standard R, then you can absolutely do so and we show you how.

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Area Plots with Intensity Coloring

July 13, 2010
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Area Plots with Intensity Coloring

I am not sure apeescape’s ggplot2 area plot with intensity colouring is really the best way of presenting the information, but it had me intrigued enough to replicate it using base R graphics. The key technique is to draw a gradient...

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Employee productivity as function of number of workers revisited

June 22, 2010
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Employee productivity as function of number of workers revisited

We have a mild obsession with employee productivity and how that declines as companies get bigger. We have previously found that when you treble the number of workers, you halve their individual productivity which is mildly scary. We revisit the analysis for the...

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Comparing standard R with Revoutions for performance

June 17, 2010
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Comparing standard R with Revoutions for performance

Following on from my previous post about improving performance of R by linking with optimized linear algebra libraries, I thought it would be useful to try out the five benchmarks Revolutions Analytics have on their Revolutionary Performance pages.

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Faster R through better BLAS

June 15, 2010
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Faster R through better BLAS

Can we make our analysis using the R statistical computing and analysis platform run faster? Usually the answer is yes, and the best way is to improve your algorithm and variable selection. But recently David Smith was suggesting that a big benefit of their (commercial) version of R...

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R: Eliminating observed values with zero variance

March 8, 2010
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R: Eliminating observed values with zero variance

I needed a fast way of eliminating observed values with zero variance from large data sets using the R statistical computing and analysis platform. In other words, I want to find the columns in a data frame that has zero variance. And as fast as possible, because my data sets are large, many, and changing fast....

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Beautiful Data

July 27, 2009
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Beautiful Data

O'Reilly's recent publication Beautiful Data has a chapter by Jeff Jonas which is enough reason in itself for me to recommend it. The chapter, Data Finds Data, is also available as a PDF download.

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Massively parallel database for analytics

July 22, 2009
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Massively parallel database for analytics

This is by far the best description of why traditional parallel databases (like Teradata, Greenplum et al.) is a evolutionary dead end. But much more than a theoretical discussion, they have built a solution which they call HadoopDB. It is based on Hadoop, PostgreSQL, and Hive and is completely Open Source. Alternative, column-based, backends to PostgreSQL...

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The Knapsack Problem

July 10, 2009
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The Knapsack Problem

David posts a question about how to solve this knapsack problem using the R statistical computing and analysis platform. My reply in the comments seems to have disappeared for a while so here is my proposed solution:

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OECD Statistics

July 2, 2009
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OECD Statistics

I am a sucker for good quality data. I wrote about data.gov, the US Government data site before, and now I find OECD Statistics which has some 300 data sets, many of which seems to be readily accessible (though some may require subscription)

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