TL:DR: If you are new to ggplot, welcome! If you are used to base R, its probably going to take awhile for you to get the hang of the syntax, but trust me, it’s worth it. GGplot is the tidyverse package for making graphics and you can control ...

Daniel Hanson is a full-time lecturer in the Computational Finance & Risk Management program within the Department of Applied Mathematics at the University of Washington. In the previous post in this series, we looked at how to write interface files using Rcpp to call functions and instantiate classes in standard and ...

A researcher reached out to me the other day to see if the simstudy package provides a quick and easy way to generate data from a truncated distribution. Other than the noZeroPoisson distribution option (which is a very specific truncated distribution), there is no way to do this directly. You ...

Intro This post is a supplementary material for an assignment. The assignment is part of the Augmented Machine Learning unit for a Specialised Diploma in Data Science for Business. The aim of the assignment is to use DataRobot for predictive modelling. Exploratory data analysis and feature engineering will be done ...

In the video linked below we discuss how to convert your R code into an API using the awesome plumber package! Learn more by clicking here or by following the links below. The plumber package allows you to convert R functions into API calls. For example, rather than launching R ...

I started my career in finance in 2007. For about a year I thought “this is great!” Then 2008 hit and I thought “this is terrible!” After 2008, I had one fundamental question that I wanted answered: how much can you lose in an investment portfolio before you’ve lost too much? After ...

In our data science teaching, we present the ROC plot (and the area under the curve of the plot, or AUC) as a useful tool for evaluating score-based classifier models, as well as for comparing multiple such models. The ROC is informative and useful, but it’s also perhaps overly ...

Previously we discussed how to measure accuracy of point forecasts and performance of prediction intervals in different cases. Now we look into the question how to tell the difference between competing forecasting approaches. Let’s imagine the situation, when we have four forecasting methods applied to 100 time series with accuracy ...

Defining big data Big data is one of the buzziest words in the data space. But just how big is big? One way to think about it is in terms of volume, or the amount of data you have. Based on volume, we can define big data as data that ...

The second COVID-19 Data Forum, co-sponsored by the Stanford Data Science Institute and the R Consortium, was held August 13, 2020. This series of forums brings together experts working to... The post Thank you to our Speakers and Participants – COVID-19 Data Forum II appeared first on R Consortium.

Photo by Marvin Meyer on UnsplashLoops are, by definition, repetitive tasks. Although it is not part of the definition, loops also tend to be boring. Luckily for us, computers are good at performing repetitive tasks, and they never complain about boredom.When the tasks are complex, or if the number ...

I just posted an interesting look at the growth of the labor force by decade. Given that I used R to produce it, I thought it interesting to share the R code and method. Just for reference, here is the chart: First, we will need the following libraries The quantmod ...

TL;DR Nobody wants to use a slow dashboard. At Appsilon, we frequently hear this complaint from clients: “We’ve built a fantastic Shiny dashboard, but it’s incredibly slow and no one wants to use it.” No matter how complicated they are, Shiny dashboards do not have to be ...

Just a little post about sharing code and skills with the unknown. After posting about covidfrance app, I exchanged with github users wanting to reproduce the app for their country.. I just want to say here that it was really a pleasure to exchan...