133 search results for "heatmap"

Analyse Quandl data with R – even from the cloud

March 10, 2013
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Analyse Quandl data with R – even from the cloud

I have read two thrilling news about the really promising time-series data provider called Quandl recently: Quandl: A Wikipedia for Time Series DataQuandl package released to CRANWith the help of the Quandl R package* (development version...

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Visualizing Risky Words — Part 2

March 9, 2013
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Visualizing Risky Words — Part 2

This is a follow-up to my Visualizing Risky Words post. You’ll need to read that for context if you’re just jumping in now. Full R code for the generated images (which are pretty large) is at the end. Aesthetics are the primary reason for using a word cloud, though one can pretty quickly recognize what

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More visualisation of 2012 NFL Quarterback performance with R

February 12, 2013
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More visualisation of 2012 NFL Quarterback performance with R

In last week’s post I used R heatmaps to visualise the performance of NFL Quarterbacks in 2012. This was done in a 2 step process, Clustering QB performance based on the 12 performance metrics using hierarchical clustering Plotting the performance clusters using R’s pheatmap library An output from the step 1 is the cluster dendrogram

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Visualising 2012 NFL Quarterback performance with R heat maps

February 3, 2013
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Visualising 2012 NFL Quarterback performance with R heat maps

With only 24 hours remaining in the 2012 NFL season, this is a good time to review how the league's QBs performed during the regular season using performance data from KFFL and the heat mapping capabilities of R. #scale data to mean=0, sd=1 and convert to matrix QBscaled <- as.matrix(scale(QB2012)) #create heatmap and don't reorder

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Heat maps using R

January 12, 2013
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Heat maps using R

One of the great things about following blogs on R is seeing what others are doing & being able to replicate and try out things on my own data sets. For example, some great links on rapidly creating heat maps using R. Drawing Heat Maps in R How to Make a Heatmap – a Quick

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100 most read R posts in 2012 (stats from R-bloggers) – big data, visualization, data manipulation, and other languages

January 2, 2013
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100 most read R posts in 2012 (stats from R-bloggers) – big data, visualization, data manipulation, and other languages

R-bloggers.com is now three years young. The site is an (unofficial) online journal of the R statistical programming environment, written by bloggers who agreed to contribute their R articles to the site. Last year, I posted on the top 24...

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Who Survived on the Titanic? Predictive Classification with Parametric and Non-parametric Models

December 24, 2012
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Who Survived on the Titanic? Predictive Classification with Parametric and Non-parametric Models

I recently read a really interesting blog post about trying to predict who survived on the Titanic with standard GLM models and two forms of non-parametric classification tree (CART) methodology. The post was featured on R-bloggers, and I think it's worth a closer look. The basic idea was to figure out which of these three

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Working with geographical Data. Part 1: Simple National Infomaps

December 21, 2012
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Working with geographical Data. Part 1: Simple National Infomaps

There is a popular expression in my country called “Gastar polvora en chimangos”, whose translation in English would be “spending gunpowder in chimangos”. Chimango is a kind of bird whose meat is useless for humans. So “spending gunpowder in chimangos” … Continue reading →

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NHS Winter Situation Reports: Shiny Viewer v2

December 18, 2012
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NHS Winter Situation Reports: Shiny Viewer v2

Having got my NHS Winter sitrep data scraper into shape (I think!), and dabbled with a quick Shiny demo using the R/Shiny library, I thought I’d tidy it up a little over the weekend and long the way learn a few new presentation tricks. To quickly recap the data availability, the NHS publish a weekly

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Follow-up: So … daylight savings time does not minimize variance in sunrises

December 3, 2012
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Follow-up: So … daylight savings time does not minimize variance in sunrises

Last week we posted a nice theory about daylight savings time, in particular, that its dates were chosen to reduce variance in the time of sunrise. It looked plausible from the graph.We were talking to our Microsoft Research colleague Jake Hofman who suggested "why don't you just find the optimal dates to change the clock by one hour?" So...

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