rstudio::conf 2019 talks

rstudio::conf 2019 in Austin, TX put the spotlight on the use of R in Industry. Joe Cheng opened the conference with the epic keynote address Shiny in Production, Principles, Practices and Tools that set the stage for two days of talks in three parallel tracks with sessions focusing on Interoperability, Production, Distributed Processing, Industry and Org Thinking.

rstudio::conf 2019 talks

rstudio::conf 2019 in Austin, TX put the spotlight on the use of R in Industry. Joe Cheng opened the conference with the epic keynote address Shiny in Production, Principles, Practices and Tools that set the stage for two days of talks in three parallel tracks with sessions focusing on Interoperability, Production, Distributed Processing, Industry and Org Thinking.

Some people may have come to rstudio::conf 2019 just to be seen up near the stage at Austin City Limits listening to Lukas Nelson & the Promise of the Real, but the conference itself was also a pretty cool place to hang out.

The 2019 conference put the spotlight on the use of R in Industry. Joe Cheng opened the conference with the epic keynote address Shiny in Production, Principles, Practices and Tools that set the stage for two days of talks in three parallel tracks with sessions focusing on Interoperability, Production, Distributed Processing, Industry and Org Thinking. Memorable talks included Felienne’s keynote, Explicit direct Instruction in Programming Education, and David Robinson’s Keynote, The unreasonable effectiveness of public work.

Keynotes and Panels

Shiny in production: Principles, practices, and tools

Shiny in production: Principles, practices, and tools

Joe Cheng
Welcome and RStudio Vision

Welcome and RStudio Vision

Tareef Kawaf
Explicit Direct Instruction in Programming Education

Explicit Direct Instruction in Programming Education

Felienne
The unreasonable effectiveness of public work

The unreasonable effectiveness of public work

David Robinson
Panel discussion: Growth and Data Science: Individuals, leaders, organizations and responsibilities

Panel discussion: Growth and Data Science: Individuals, leaders, organizations and responsibilities

Eduardo Arino de la Rubia, Hilary Parker, Karthik Ram, Angela Bassa, Tracy Teal
Welcome to rstudio::conf 2019

Welcome to rstudio::conf 2019

Production

R in production

R in production

Mark Sellors
RStudio Connect Past, present, and future

RStudio Connect Past, present, and future

Jeff Allen
Announcing RStudio Package Manager

Announcing RStudio Package Manager

Sean Lopp
Push straight to prod API development with R and Tensorflow at T-Mobile

Push straight to prod API development with R and Tensorflow at T-Mobile

Heather Nolis, Jacqueline Nolis

Shiny

Reactlog 2.0: Debugging the state of Shiny

Reactlog 2.0: Debugging the state of Shiny

Barret Schloerke
Don’t let long running tasks hang your users Introducing ipc for Shiny

Don’t let long running tasks hang your users Introducing ipc for Shiny

Ian Fellows
Effective use of Shiny modules in application development

Effective use of Shiny modules in application development

Eric Nantz
Integrating React.js and Shiny

Integrating React.js and Shiny

Alan Dipert

Tidyverse

Melt the clock Tidy time series analysis

Melt the clock Tidy time series analysis

Earo Wang
Spatial data science in the Tidyverse

Spatial data science in the Tidyverse

Edzer Pebesma
3D mapping, plotting, and printing with rayshader

3D mapping, plotting, and printing with rayshader

Tyler Morgan-Wall
gganimate live cookbook

gganimate live cookbook

Thomas Lin Pedersen
Solving R for data science

Solving R for data science

Jeffrey Arnold
Working with categorical data in R without losing your mind

Working with categorical data in R without losing your mind

Amelia McNamara
A guide to modern reproducible data science with R

A guide to modern reproducible data science with R

Karthik Ram
Box plots A case study in debugging and perseverance

Box plots A case study in debugging and perseverance

Kara Woo

Interoperability

New language features in RStudio

New language features in RStudio

Jonathan McPherson
Ursa Labs and Apache Arrow in 2019

Ursa Labs and Apache Arrow in 2019

Wes McKinney
Configuration management tools for the R admin

Configuration management tools for the R admin

Kelly O'Briant
Databases using R: The latest

Databases using R: The latest

Edgar Ruiz

Distributed

RStudio Job Launcher Changing where we run R stuff

RStudio Job Launcher Changing where we run R stuff

Darby Hadley
Scaling R with Spark

Scaling R with Spark

Javier Luraschi
Democratizing R with Plumber APIs

Democratizing R with Plumber APIs

James Blair
Introducing mlflow

Introducing mlflow

Kevin Kuo

Industry

R at the ACLU: Joining tables to to reunite families

R at the ACLU: Joining tables to to reunite families

Brooke Watson
R Consortium initiatives in medicine - Joe Rickert

R Consortium initiatives in medicine - Joe Rickert

Joseph Rickert
The Future's Shiny: Dashboards for Pioneering Genomic Medicine in R

The Future's Shiny: Dashboards for Pioneering Genomic Medicine in R

Nic Crane
Building an A/B testing analytics system with R and Shiny

Building an A/B testing analytics system with R and Shiny

Emily Robinson

Kaleidoscope

R qtl2: Rewrite of a very old R package

R qtl2: Rewrite of a very old R package

Karl Broman
Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition

Using R, the Tidyverse, H2O, and Shiny to reduce employee attrition

Matt Dancho
Empowering a data team with RStudio addins

Empowering a data team with RStudio addins

Hao Zhu
Getting it right: Writing reliable and maintainable R code

Getting it right: Writing reliable and maintainable R code

Amanda Gadrow

Organizational Thinking

Putting empathy in action Building a 'community of practice' for analytics in a global corporation

Putting empathy in action Building a 'community of practice' for analytics in a global corporation

JD Long
The resilient R champion

The resilient R champion

Tonya Filz
Cultivating creativity in data work

Cultivating creativity in data work

Hilary Parker
Data science as a team sport

Data science as a team sport

Angela Bassa

Publication

pagedown: Creating beautiful PDFs with R Markdown and CSS

pagedown: Creating beautiful PDFs with R Markdown and CSS

Yihui Xie
R Markdown: The bigger picture

R Markdown: The bigger picture

Garrett Grolemund
The lazy and easily distracted report writer: Using rmarkdown and parameterised reports

The lazy and easily distracted report writer: Using rmarkdown and parameterised reports

Mike K Smith
Introducing the gt package

Introducing the gt package

Rich Iannone

Modeling

Solving the model representation problem with broom

Solving the model representation problem with broom

Alex Hayes
Visualizing uncertainty with hypothetical outcomes plots

Visualizing uncertainty with hypothetical outcomes plots

Claus Wilke
Why TensorFlow eager execution matters

Why TensorFlow eager execution matters

Sigrid Keydana
parsnip: A tidy model interface

parsnip: A tidy model interface

Max Kuhn

Programming

vctrs: Tools for making size and type consistent functions

vctrs: Tools for making size and type consistent functions

Hadley Wickham
Working with names and expressions in your tidy eval code

Working with names and expressions in your tidy eval code

Lionel Henry
A preview of Rtools 4.0

A preview of Rtools 4.0

Jeroen Ooms
It depends: A dialog about dependencies

It depends: A dialog about dependencies

Jim Hester
Lazy evaluation

Lazy evaluation

Jenny Bryan
Learning and using the Tidyverse for historical research

Learning and using the Tidyverse for historical research

Jesse Sadler
Our colour of magic: The open sourcery of fantastic R packages

Our colour of magic: The open sourcery of fantastic R packages

Miles McBain
pkgman: A fresh approach to package installation

pkgman: A fresh approach to package installation

Gábor Csárdi

Teaching

R4DS online learning community Improvements to self-taught data science & the critical need for diversity, equity, and inclusion

R4DS online learning community Improvements to self-taught data science & the critical need for diversity, equity, and inclusion

Jesse Mostipak
RStudio Cloud for education

RStudio Cloud for education

Mel Gregory
Teaching data science with puzzles

Teaching data science with puzzles

Irene Steves
Teaching R using inclusive pedagogy: Practices and lessons learned from over 700 Carpentries workshops

Teaching R using inclusive pedagogy: Practices and lessons learned from over 700 Carpentries workshops

Tracy Teal
The next million R users

The next million R users

Carl Howe
Catching the R wave: How R and RStudio are revolutionizing statistics education in community colleges (and beyond)

Catching the R wave: How R and RStudio are revolutionizing statistics education in community colleges (and beyond)

Mary Rudis
Introductory statistics with R: Easing the transition to software for beginner students

Introductory statistics with R: Easing the transition to software for beginner students

Kelly Nicole Bodwin
Learning from eight years of data science mistakes

Learning from eight years of data science mistakes

Caitlin Hudon