# Blog Archives

## Has the NFL Combine’s 40 yard dash gotten faster ?

March 3, 2013
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Last week on one of my favourite podcasts, ESPN’s Football Today, Matt Williamson & Kevin Weidl discussed the standout prospects from the NFL Combine. A lot of the conversation was around how the 40 yard dash times have improved year on year due to better training technique and specific training for the combine activities. I

## More visualisation of 2012 NFL Quarterback performance with R

February 12, 2013
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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

## Visualising 2012 NFL Quarterback performance with R heat maps

February 3, 2013
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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

## Speed up for loops in R

January 30, 2013
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Are your for loops too slow in R ? Are loops that should take seconds actually taking hours ? As I found out recently, how you structure your code can make a huge difference in execution times. Fortunately making a few small changes to your code can speed up these loops by several orders of

## Heat maps using R

January 12, 2013
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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

## tolower() – error catching unmappable characters

January 6, 2013
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The tolower() function returns an error where it can’t map to the Unicode character set of the input data – a common occurrence when analysing social media data with emoticons. Emoticons are those symbols that are commonly used on mobile phones but aren’t always recognised on all platforms. For example, when converting tweets to @delta

## Joining 2 R data sets with different column names

December 22, 2012
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Joining or merging two data sets is one of the most common tasks in preparing and analysing data. In fact a Google search returns 253 million results. However most examples assume that the columns that you want to merge by have the same names in both data sets which is often not the case. For example: