Monthly Archives: March 2013

metvurst now a package, repository moved to GitHub

March 3, 2013
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metvurst now a package, repository moved to GitHub

Inspired by a post on PirateGrunt, I finally managed to pack metvurst up and turn it into a proper R-Package (the fact that I’m on holiday and have some time also helped). As a side-effect of this, the repository has been moved from … Continue reading →

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resizing plot panels to fit data distribution

March 3, 2013
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resizing plot panels to fit data distribution

I am a big fan of lattice/latticeExtra. In fact, nearly all visualisations I have produced so far make use of this great package. The possibilities for customisation are endless and the amount of flexibility it provides is especially valuable for … Continue reading →

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visualising diurnal wind climatologies

March 3, 2013
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visualising diurnal wind climatologies

In this post I want to highlight the second core function of the metvurst repository (https://github.com/tim-salabim/metvurst): The windContours function It is intended to provide a compact overview of the wind field climatology at a location and plots wind direction and … Continue reading →

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visualising large amounts of hourly environmental data

March 3, 2013
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visualising large amounts of hourly environmental data

It is Sunday, it's raining and I have a few hours to spend before I am invited for lunch at my parents place. Hence, I thought I'd use the time to produce another post. It has been a while since … Continue reading →

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reading raster data using library(parallel)

March 3, 2013
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reading raster data using library(parallel)

Recently, I have been doing some analysis for a project I am involved in. In particular, I was interested what role pacific sea surface temperatures play with regard to rainfall in East Africa. I spare you the details as I … Continue reading →

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Download Fantasy Football Projections from ESPN.com using R

March 3, 2013
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Download Fantasy Football Projections from ESPN.com using R

In this post, I will demonstrate how to download fantasy football projections from ESPN.com using R.  Having projections allows us to do many different analyses to determine our best possible fantasy team.  The projections on ESPN.com are currently from last year—they haven't been updated yet for the upcoming season.  ESPN will update them closer to the start of...

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Tips and Tricks for HTML and R

March 3, 2013
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Over the past two months I have tried to convert completely to HTML5 slides, HTML reports and R + knitr. The switch from Sweave came with a few frustrations but I think overall it is way better - it is incredibly efficient and while some flexibility on...

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renaming data frame columns in lists

March 3, 2013
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renaming data frame columns in lists

OK, so the scenario is as follows: we have a list of 2 elements which in turn are again lists with 2 elements (each of which is a data frame). None of the elements in question carry names (neither the … Continue reading →

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RMark: Parallel fast merging

March 3, 2013
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Last time we looked at a different method of merging multiple files via fast mergin g. I highly recommend checking the fast merging function before we will translate it to a parallel solution. Parallel programming in this case means we are using more t...

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All That Glitters

March 3, 2013
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All That Glitters

"The law itself follows Gold" Sextus Propertius.But what about stocks, bonds and real estate? Do they follow Gold too? Using the correlation data from my previous post, The Financial Crisis on Tape Part I, this question is easy to investigate. Indeed, ...

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