Publications by Sascha W.
The "golden age" of a football player
It’s been some time since my last post on football. And we’re talking about european soccer here.So I finally managed to write some functions which allow me to extract player stats from www.transfermarkt.de. The site tracks lots of stats in the world of soccer. For each player, there is information about the dominant foot, height,...
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"I don’t wanna grow up": Age / value relationships for football players
Let’s get back to the age-value relationship from my last post. I did some more plotting to see on which position this inversed U-shaped relationship is strongest. Please note, that I use a dataframe called eu.players throughout this post, which holds downloaded football player information from transfermarkt.de.But first, let us get...
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Peace through Music. Country clustering using R and the last.fm API
last.fm is an internet radio and music suggestion service. Registered users can also use last.fm to ‘scrobble’ tracks they’ve been listening to. last.fm then keeps track of a user’s statistics in terms of top artists, albums and tracks.Luckily, last.fm also has an API which is accessible as soon as you get a key for it. Thanks to this API...
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TeXing R tables: Save yourself a lot of typing…
I want to share a function I wrote for my dissertation. The function is useful for putting up to two R tables into one TeX table.You have to load the package ‘languageR’ to have the dataset ‘dative’ available.Let’s suppose you have two tables, one with means and another one with standard deviations. Of course, these two tabl...
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Funky music in funky months: Does my taste of music change over the year?
I already introduced some stuff I did with the last.fm API. But did you ever wonder if your taste of music changes over the year? Sunny music in the sunny months and dark music in darker months? Well, I did. And I want to check it out with the RLastFM package and some additional functions.First, we load the package and assign an API k...
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The rbinding race: for vs. do.call vs. rbind.fill
Which function rbinds dataframes together fastest?First competitor: classic rbind in a for loop over a list of dataframesSecond competitor: do.call(“rbind”, )Third competitor: rbind.fill() from the plyr packageThe job:– rbinding a list of dataframes with 4 columns each, one column is the splitting factor, the other 3 hold norm...
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XML in R – A (German) tutorial / XML in R – ein Tutorial auf Deutsch
I used knitr to hack together a very short tutorial about XML in R.It’s in German. And it’s not very long. But, hey, it’s free 🙂I hope it can be of help to someone who wants to get started with XML processing in R.Please feel free to post or send any comments about the thing. If it is actually of use to someone I’ll conside...
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No surprises: More people tweet more. Visualizing twitter counts during election day.
As if the R world needed another example of Twitter visualizations, right? Well, here we go anyway.At the beginning of 2013, Pablo Barberá released the first version of his R package ‘streamR‘ (CRAN link). With this package, you can tap into the streaming capabilities of the Twitter API. I did so for 10 consecutive days. Luckily,...
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The ‘Deutsche Bahn’ (German Railway Corp.) is always late!!1! Or is it? And if, why?
The biggest German railway company, the ‘Deutsche Bahn’, is subject of frequent emotional discussions about being late all the time. A big German newspaper, the Süddeutsche Zeitung built the so-called ‘train monitor’ (Zugmonitor). The data is (or was) made available in cooperation with OpenDataCity: http://www.opendatacity.de/zugmonitor-...
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The ‘Deutsche Bahn’ (German Railway Corp.) is always late!!!! Or is it? And if, why?
The biggest German railway company, the ‘Deutsche Bahn’, is subject of frequent emotional discussions about being late all the time. A big German newspaper, the Süddeutsche Zeitung built the so-called ‘train monitor’ (Zugmonitor). The data is (or was) made available in cooperation with OpenDataCity: http://www.opendatacity.de/zugmonitor-...
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