It has always been the mission of R developers to connect R to the “good stuff”. As John Chambers puts it in his book Extending R: One of the attractions of R has always been the ability to compute an interesting result quickly. A key motivation for the original S ...

At long last, we are pleased to announce the release of CVXR! First introduced at useR! 2016, CVXR is an R package that provides an object-oriented language for convex optimization, similar to CVX, CVXPY, YALMIP, and Convex.jl. It allows the user to formulate convex optimization problems in a natural mathematical ...

Of the 182 new packages that made it to CRAN in October, here are my picks for the “Top 40”. They are organized into eight categories: Engineering, Machine Learning, Numerical Methods, Science, Statistics, Time Series, Utilities and Visualizations. Engineering is a new category, and its appearance may be an early signal for ...

Shiny applications are often backed by fluid, changing data. Data updates can occur at different time scales: from scheduled daily updates to live streaming data and ad-hoc user inputs. This article describes best practices for handling data updates in Shiny, and discusses deployment strategies for automating data updates. This post ...

In a previous post, we reviewed how to import daily prices, build a portfolio, and calculate portfolio returns. Today, we will visualize the returns of our individual assets that ultimately get mashed into a portfolio. The motivation here is to make sure we have scrutinized our assets before they get ...

This guide shows how to automate the summary of surveys with R and R Markdown using RStudio. This is great for portions of the document that don’t change (e.g., “the survey shows substantial partisan polarization”). The motivation is really twofold: efficiency (maximize the reusabililty of code, minimize copying ...

It has never been easier to access data from R. Not only does there seem to be a constant stream of new packages that access the APIs of data providers, but it is also becoming popular for package authors to wrap up fairly large datasets into R packages. Below are 44 ...

There were so many interesting ideas among the 222 new packages that made it to CRAN in September that I found it exceptionally difficult to decide on the “Top 40” packages. In the end, I only managed to limit my selection to 40 by avoiding all packages that I would normally classify under “...

The SeaClass R Package The Operations Technology and Advanced Analytics Group (OTAAG) at Seagate Technology has decided to share an internal project that helps accelerate development of classification models. The interactive SeaClass tool is contained in an R-based package built using shiny and other CRAN packages commonly used for binary ...

There are many ways to query data with R. This post shows you three of the most common ways: Using DBI Using dplyr syntax Using R Notebooks Background Several recent package improvements make it easier for you to use databases with R. The query examples below demonstrate some of the ...

A recent paper in nature climate change: Less than 2°C warming by 2100 unlikely (Raftery et al. 2017), concludes that the goal of the Paris Agreement is unlikely to be met. Although the conclusion is disheartening, the paper advances the science of climate modeling by developing a joint Bayesian hierarchical model for ...

August was a relatively slow month for new R packages; “only” 180 new packages stuck to CRAN. Here are my “Top 40” picks organized into seven categories: Data, Machine Learning, Miscellaneous, Science, Statistics, Utilities and Visualizations. Although they have been written for specialized audiences, I have included the three “Science” packages because, ...

With roots dating back to at least 1662 when John Graunt, a London merchant, published an extensive set of inferences based on mortality records, survival analysis is one of the oldest subfields of Statistics [1]. Basic life-table methods, including techniques for dealing with censored data, were discovered before 1700 [2], and in the early ...

Editors Note: It has been heartbreaking watching the images from México City. Teresa Ortiz, co-organizer of R-Ladies CDMX reports on efforts of data scientists to help. Our thoughts are with them, and with the people of México. It has been a hard couple of days around here. In ...

Inside the enterprise, a dashboard is expected to have up-to-the-minute information, to have a fast response time despite the large amount of data that supports it, and to be available on any device. An end user may expect that clicking on a bar or column inside a plot will result ...

In our previous portfolio volatility work, we covered how to import stock prices, convert to returns and set weights, calculate portfolio volatility, and calculate rolling portfolio volatility. Now we want to break that total portfolio volatility into its constituent parts and investigate how each asset contributes to the volatility. Why ...