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This is the last part of the mini series Analysing NBA Player data. The first part was concerned with scraping and cleaning player statistics from any NBA season. The second part showed how to use principal component analysis and k means clustering to “revolutionize” player positions. Which kind of failed. ... [Read more...]

In a previous post I have shown you how to setup an AWS instance running the newest RStudio, R, Python, Julia and so forth, where the configuration of the instance can be freely chosen. However, there is quite a lot of possibilities of instance configu... [Read more...]

March Madness is officially upon us as College Basketball teams across the US try to get a few more signature wins on their resume during conference tournaments before Selection Sunday. With only 30 or so games in a given season and around 350 teams in... [Read more...]

Last semester I taught an R programming at MIMUW. My lectures are project oriented, the second project was related to package development. The idea was straightforward: each team of students shall create a package that produces IFS fractals (based on iterated function systems). Each package shall have two generic functions: ... [Read more...]

styler 1.0.1 is now awailable on CRAN. It’s mainly a maintenance release and contains bug fixes and speed improvements. The highlights are: [Read more...]

TL;DR sparklyr maps R data types and data storage types to Scala, but it doesn’t handle all data storage types. This blog post discusses how to generate Scala data storage types from the R side, that are not generated by sparklyr. You can do this by using the ... [Read more...]

styler 1.0.1 is now available on CRAN. It is mainly a maintenance release and contains bug fixes and speed improvements. The highlights are: styler 1.0.1 requires tibble 1.4.2 which was optimized for speed, so if you have it installed, styler runs ... [Read more...]

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styler 1.0.1 is now available on CRAN. It is mainly a maintenance release and contains bug fixes and speed improvements. The highlights are: styler 1.0.1 requires tibble 1.4.2 which was optimized for speed, so if you have it installed, styler runs ~2x as fast as before. We’re now recognizing and respecting more ... [Read more...]

styler 1.0.1 is now available on CRAN. It is mainly a maintenance release and contains bug fixes and speed improvements. The highlights are: styler 1.0.1 requires tibble 1.4.2 which was optimized for speed, so if you have it installed, styler runs ~2x as fast as before. We’re now recognizing and respecting more ... [Read more...]

JAWS Scrape Hall of Fame Inductee Names WAR Values EDA Save Objects Conclusion References @ctrent I’ve always thought that it’d be fun to debate the @Reds HOF like the real one. Set a high , but debatable, bar. Bring on the JAWS— Craig Wales (@C_Dubs1) August 22, 2017 it would ... [Read more...]

Welcome to the LIBD rstats club! A few months ago Carrie Wright and Leonardo Collado-Torres started an R + Journal club where we have been meeting every other week to talk about R packages and discuss journal articles in our field. Some examples of what we covered are tidyverse (Wickham, 2017), BiocStyle (... [Read more...]

In this blog post Leonardo Collado-Torres explains how to contribute posts to the LIBD rstats club. While some parameters are specific to this blog, you could also use this for creating your own community blog. Install necessary tools We first need to get the appropriate tools installed in our computer. 1. ... [Read more...]

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by Antony Unwin, University of Augsburg, Germany There are many different methods for identifying outliers and a lot of them are available in R. But are outliers a matter of opinion? Do all methods give the same results? Articles on outlier methods use a mixture of theory and practice. Theory ... [Read more...]

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