Publications by Paul van der Laken
Why Gordon Shotwell uses R
This blog by Gordon Shotwell has passed my Twitter feed a couple of times now and I thought I’d share it here: blog.shotwell.ca/posts/why_i_use_r It in, Gordon present his reasons for using R, describing R’s four unique selling point, and outlining a discussion full of perfectly quotable thoughts and opinions. Do have a look at the original ...
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Learn Julia for Data Science
Most data scientists favor Python as a programming language these days. However, there’s also still a large group of data scientists coming from a statistics, econometrics, or social science and therefore favoring R, the programming language they learned in university. Now there’s a new kid on the block: Julia. Via Medium Advantages & Disadva...
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Simulating data with Bayesian networks, by Daniel Oehm
Daniel Oehm wrote this interesting blog about how to simulate realistic data using a Bayesian network. Bayesian networks are a type of probabilistic graphical model that uses Bayesian inference for probability computations. Bayesian networks aim to model conditional dependence, and therefore causation, by representing conditional dependence by ...
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Solutions to working with small sample sizes
Both in science and business, we often experience difficulties collecting enough data to test our hypotheses, either because target groups are small or hard to access, or because data collection entails prohibitive costs. Such obstacles may result in data sets that are too small for the complexity of the statistical model needed to answer the qu...
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paletteer: Hundreds of color palettes in R
Looking for just the right colors for your data visualization? I often cover tools to pick color palettes on my website (e.g. here, here, or here) and also host a comprehensive list of color packages in my R programming resources overview. However, paletteer is by far my favorite package for customizing your colors in R! The paletteer package o...
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How to standardize group colors in data visualizations in R
One best practice in visualization is to make your color scheme consistent across figures. For instance, if you’re making multiple plots of the dataset — say a group of 5 companies — you want to have each company have the same, consistent coloring across all these plots. R has some great data visualization capabilities. Particularly the g...
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Visualizing decision tree partition and decision boundaries
Grant McDermott develop this new R package I had thought of: parttree parttree includes a set of simple functions for visualizing decision tree partitions in R with ggplot2. The package is not yet on CRAN, but can be installed from GitHub using: # install.packages("remotes") remotes::install_github("grantmcdermott/parttree") Using the familiar...
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Curated Regular Expression Resources
Regular expression (also abbreviated to regex) really is a powertool any programmer should know. It was and is one of the things I most liked learning, as it provides you with immediate, godlike powers that can speed up your (data science) workflow tenfold. I’ve covered many regex related topics on this blog already, but thought I’d combine t...
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Simulating and visualizing the Monty Hall problem in Python & R
I recently visited a data science meetup where one of the speakers spoke about playing out the Monty Hall problem with his kids. The Monty Hall problem is probability puzzle. Based on the American television game show Let’s Make a Deal and its host, named Monty Hall: You’re given the choice of three doors. Behind one door sits a prize:...
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Free Springer Books during COVID19
Book publisher Springer just released over 400 book titles that can be downloaded free of charge following the corona-virus outbreak. Here’s fhe full overview: https://link.springer.com/search?facet-content-type=%22Book%22&package=mat-covid19_textbooks&facet-language=%22En%22&sortOrder=newestFirst&showAll=true Most of these books will normally ...
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