One big advantage of using open-source tools is the fantastic ecosystems that typically accompany them. Being able to tap into a massive open-source community, by way of downloading freely available code is decidedly useful. But, yes, there are downsides to downloads. For one, there are too many packages out there. ...

Learn how to program your own algorithms in R with us on June 22nd! With the 3rd Chapter of our “Introduction to R” learning path we continue our journey towards building strong R programming foundations and skills. With the “Programming R” workshop...

Visualizing spatial data is always more challenging than it seems at first. There are too many moving parts, and the whole thing can quickly slow down your dashboard. Today you’ll learn how to connect Google Earth Engine with R Shiny. We’ll start by signing up for a free ...

In the previous posts we have learned how to compute a supply curve and a demand curve. What do we need to do to derive a competitive equilibrium? Before we answer that directly, lets first define what a competitive equilibrium is so to get everyone on the same page. Def: ...

Learning number 1: make functions fail early When writing your own functions, avoid conversion of types without warning. For example, this function only works on characters: my_nchar

This post on R Views is about… Python! Surprising, I know. Python has several well-written packages for statistics and data science, but CRAN, R’s central repository, contains thousands of packages implementing sophisticated statistical algorithms that have been field-tested over many years. Thanks to the rpy2 package, Pythonistas can take ...

tidyterra provides tidyverse methods for terra objects and geom functions for plotting with ggplot2.

Introduction Since my last blog on Tesseract-OCR I have been playing around casually with it to see what it is possible of doing. Tesseract supports optical character recognition for over 100 languages. That together with straight forward usage for implementing it in R inspired me to try using it for Hebrew ...

The post How to add labels at the end of each line in ggplot2? appeared first on Data Science Tutorials How to add labels at the end of each line in ggplot2?, Using the ggplot2 R library, this article shows how to display the last value of each line as ...

Can you monitor user adoption for R Shiny apps? What is user adoption anyway? We’ll answer these questions and show you how to do it yourself in this article. Put simply, user adoption is the process by which new users become familiar with your product and/or service and ...

A videogame speedrun is a challenge to beat the game as quickly as possible. It’s time attack racing but for a videogame. There are, in my mind, two ways to make a run’s time go faster: Playing better and more smoothly (optimizations, having better luc...

In this blog post we will discuss the derivation of a microfounded supply curve in R. Specifically we are interested in seeing how we can compute the supply curve from our firms objective problem. In this case we will consider solving for the supply curve from the following profit function: ...

Following a question on Stack Overflow trying to replicate a figure from the paper written by Alan Gelfand and Adrian Smith (1990) for The American Statistician, Bayesian sampling without tears, which precedes their historical MCMC papers, I looked at the R code produced by the OP and could not spot an ...