What we're about

R is an open source programming language for statistical computing, data analysis, and graphical visualization. R has an estimated one million users worldwide, and its user base is growing. While most commonly used within academia, in fields such as computational biology and applied statistics, it is gaining currency in commercial areas such as quantitative finance and business intelligence.

Among R's strengths as a language are its powerful built-in tools for inferential statistics, its compact modeling syntax, its data visualization capabilities, and its ease of connectivity with persistent data stores (from databases to flatfiles).

In addition, R's open source nature and its extensibility via add-on "packages" has allowed it to keep up with the leading edge in academic research.

For all its strengths, though, R has an admittedly steep learning curve; the first steps towards learning and using R can be challenging.

To this end, the Bay Area R Users Group is dedicated to bringing together area practitioners of R to exchange knowledge, inspire new users, and spur the adoption of R for innovative research and commercial applications.

(Tags: rstats, BARUG, RUG)

Upcoming events (1)

"Official" May 2019 BARUG Meetup

Instacart HQ

Dear Attendees: Building security requires your full name for check in prior to the event. Upon check in, you will also be asked to sign an NDA. Agenda: 6:30: Food, drink and Networking 7:00: Welcome to Instacart 7:05: Announcements 7:10: Robert Horton: (Lightning talk): TBD 7:25: Jingjie Xiao: A/B testing for logistics with R 7:50: Peter Li (Lightning Talk) keeping score (:-/) with 'packageRank 8:05: Steve Dahlke: Applied Optimization in R - Energy Markets and Policy ***************** Robert Horton Finding the acronym definitions in unstructured text This will be an introductory presentation focusing on how to use parentheses and backreferences in regular expressions. I programmatically construct a set of regular expressions matching acronym definitions of different lengths, and collect all the results into a table. ****************** Jingjie Xiao, Senior Data Scientist, Instacart A/B testing for logistics with R Instacart's fulfillment dispatching engine is constantly changing—storms, unexpected traffic, shift cancellations, and more can all affect a system that is dynamic, interdependent, and noisy. In this talk, Instacart Senior Data Scientist, Jingjie Xiao will walk you through how controlled experiments and multivariate regression are used to continuously improve the grocery delivery engine @ Instacart. ****************** Peter Li keeping score (:-/) with 'packageRank Building on the efforts of the 'cranlogs' package, 'packageRank' puts the raw counts of package downloads into greater perspective. Numerically, it computes a package's rank percentile among all downloads. Visually, it locates a package' position in the distribution of downloads. Currently, these snapshot are available for individual days (cross-sectionally), and in more limited fashion over time (longitudinally). Along the way, I'll show how I use the 'memoise' package to cache the downloading of log files. ******************* Steve Dahlke is PhD candidate in applied economics enrolled at the Colorado School of Mines Applied Optimization in R - Energy Markets and Policy Steve is building an electricity market model to study the impact of carbon policy on the U.S. electricity sector. In this talk he will explain the method for setting up an optimization model in R to study a particular energy policy and show how to use the LPSolve package: to solve it.

Past events (138)

"Official" April 2019 BARUG Meetup

23andMe

Photos (141)