Dario RadečićinAppsilon·1 day agoMember-onlyR data.validator — How to Create Automated Data Quality Reports in R and ShinyBest approaches for automated data quality reporting in R — Every data science project needs a data validation step. It’s a crucial part, especially when feeding data into machine learning models. You don’t want errors or unexpected behaviors in a production environment. Data validation is a way you can check the data before it touches the model and ensures it’s…R7 min readR7 min read
Sam Wirth·2 days agoWhich Spring Training Stats Matter?Introduction It is seemingly impossible not to get caught up in the Spring Training hype that is generated by the flashy young player posting eye-popping stat lines or the pitcher poised for a bounce-back year notching an absurd number of strikeouts. After a long offseason, how can you not obsess over…R6 min readR6 min read
Hans Wedainrond blog·1 day agoAnalysing Dutch municipality dataExploring the aging population — This blog is about retrieving Dutch municipality data, correcting for splitting and merging municipalities, predicting future trends and visualising the result. The blog takes a step-by-step approach with code examples to allow the reader to easily follow along. …R7 min readR7 min read
Tufts Public Opinion Lab·2 days agoA Shiny App tutorial using the Cooperative Election StudyBy Brian Schaffner Shiny Apps are interactive web based tools that allow users to analyze data with a simple point and click interface. These can be built in R studio using R code. …R11 min readR11 min read
Becaye Baldé·15 hours agoThe Loess Curve: Visualize Trends in your Scatter PlotA “locally weighted scatterplot smoothing,” or LOESS curve is a smooth curve that tries to fit the data points. This allows us to better catch the trend in our data. To illustrate this, let’s visualize the number of unemployed people over the years in the USA. We are going to…R2 min readR2 min read
Adrian Joseph, PhD·2 days agoMember-onlyRecursion and backtracking in RPractical examples of recursion and backtracking in R, with performance considerations. Rationale Recursion and backtracking are very well known programming techniques. If you are a Python developer, for example, it is almost certain you’ve come across recursion at some point. Recursion and backtracking are also very popular job interview questions. Despite…R10 min readR10 min read
Marcus CodrescuinDev Genius·1 day agoMake Your R Code Over 10 Times Faster with C++Introduction Does your R code run too slow? Want to learn techniques to maximize your speed? In some cases, you may be able to rewrite R functions in C++ to make them over 10 times faster. I will show you how and when this might make sense. Background On a recent project…R6 min readR6 min read
Dario RadečićinAppsilon·3 days agoMember-onlyR renv: How to Manage Dependencies in R Projects EasilyYou deserve an easy way to manage the dependencies of your R projects. Is the renv package the solution? — How many times has your code unexpectedly stopped working? Even better, how many times did the code work on your machine, but your coworkers couldn’t run it? Both questions share the same underlying problem — R environment. That’s where R renv comes in - a dependency management package that will…R7 min readR7 min read
Cosima Meyer·2 days agoExplainable AI and BERT on Methods BitesUnderstanding Transformer-Based Models and Making Them Accessible — Together with Andreas Küpfer I spent the last months writing and thinking about how to best explain BERT (using huggingface), apply it to a typical social science problem, and show the functionality of explainable AI. …R2 min readR2 min read
Fatih Boyar·2 days agoProbability Framework of the 2008 CrisisNote: This work is mostly from HarvardX: Data Science online courses. I’m aiming to be intuitive with Monte Carlo simulations. You can find the Kaggle notebook and find the R codes on my profile link Central Limit Theorem It’s helpful to remember the central limit theorem before working on this subject. The theorem…R14 min readR14 min read
