- Learning Roadmap
- Important RStudio Sites
The Latest Resources
RStudio Connect Past, present, and future - Jeff Allen
RStudio Connect is a publishing platform that helps to operationalize the data science work you're doing. We'll review the current state and unveil some exciting new features.
Shiny in production: Principles, practices, and tools - Joe Cheng
Shiny is a web framework for R. As such, Shiny has always faced questions about whether it can or should be used “in production" we will answer these questions in this talk.
Welcome and RStudio Vision - Tareef Kawaf
Working with names and expressions in your tidy eval code - Lionel Henry
In practice there are two main flavors of tidy eval functions: functions that select columns, such as `dplyr::select()`, and functions that operate on columns, such as `dplyr::mutate()`.
Why TensorFlow eager execution matters - Sigrid Keydana
In current deep learning with Keras and TensorFlow, when you've mastered the basics and are ready to dive into more involved applications (such as generative networks, sequence-to-sequence or...
Visualizing uncertainty with hypothetical outcomes plots - Claus Wilke
Uncertainty is a key component of statistical inference. However, uncertainty is not easy to convey effectively in data visualizations. For example, viewers have a tendency to...
vctrs: Tools for making size and type consistent functions - Hadley Wickham
vctrs is a new package that provides tools (cognitive and computational) to ensure that functions behave consistently with respect to inputs of varying length and type. The end goal of vctrs is...
Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition - Matt Dancho
An organization that loses 200 high-performing employees per year has a lost productivity cost of about $15M/year. This cost is massive, yet many organizations don’t know it exists.
pagedown: Creating beautiful PDFs with R Markdown and CSS - Yihui Xie
Explicit Direct Instruction in Programming Education - Felienne
In education, there is and has always been debate about how to teach. One of these debates centers around the role of the teacher: should their role be minimal, allowing students to find and...
Melt the clock Tidy time series analysis - Earo Wang
Time series can be frustrating to work with, particularly when processing raw data into model-ready data. This work presents two new packages that address a gap in existing methodology for...
The unreasonable effectiveness of public work - David Robinson
In this talk, I'll lay out the reasons that blogging, open source contribution, and other forms of public work are a critical part of a data science career.
The resilient R champion - Tonya Filz
Merriam-Webster defines resilience as the ability to recover from or adjust easily to misfortune or change. As a Customer Success Representative who works alongside data scientists using RStudio’s...
The next million R users - Carl Howe
Many students believe that R is obscure, complex, and difficult to write. However, data from a new large-scale survey of R users conducted by RStudio shows that new R users are taking...
The lazy and easily distracted report writer: Using rmarkdown and parameterised reports - Mike K Smith
My brain is lazy, shallow and easily distracted. Learn how I use notebooks to keep my present-self organised, my future-self up to speed with what I was thinking months ago, and also how I use...
The Future's Shiny: Dashboards for Pioneering Genomic Medicine in R - Nic Crane
Shiny’s expanding capabilities are rapidly transforming how it is used in an enterprise. This talk details the creation of a large-scale application, supporting hundreds of concurrent users, making...
Teaching R using inclusive pedagogy: Practices and lessons learned from over 700 Carpentries workshops - Tracy Teal
The Carpentries is an open, global community teaching researchers the skills to turn data into knowledge. Since 2012 we have taught 700+ R workshops & trained 1600+ volunteer instructors.
Teaching data science with puzzles - Irene Steves
Of the many coding puzzles on the web, few focus on the programming skills needed for handling untidy data. During my summer internship at RStudio, I worked with Jenny Bryan to develop...
Spatial data science in the Tidyverse - Edzer Pebesma
Package sf (simple feature) and ggplot2::geom_sf have caused a fast uptake of tidy spatial data analysis by data scientists. Important spatial data science challenges are not handled by...
Solving the model representation problem with broom - Alex Hayes