Save an ocean of time

Danielle Dempsey

Summary:

My organization currently has over 250 oceanographic sensors deployed around the coast of Nova Scotia, Canada. Together, these generate around 4 million rows of …

Good practices for applied machine learning

Julia Silge

Max Kuhn

Summary:

The tidymodels framework is a collection of R packages for modeling and machine learning using tidyverse principles. Whether you are just starting out today or …

WTF AITA: What they forgot to teach you about industry transitions from academia

Travis Gerke

Summary:

This talk presents a gathering of resources from the RStudio community for industry job-seekers who are transitioning from academia. Examples include packages …

Literate Programming With Quarto

Hamel Husain

Summary:

Jupyter Notebooks play a critical role in in the workflow of many users. Notebooks are used to document existing code, to quickly prototype and iterate on …

Mobile, Low-Bandwidth and Low-Tech

Aleksander Dietrichson

Summary:

This talk discusses how we used R to solve some of the challenges we faced when all classes were emergency onlined as a result of COVID. Instructors improvised …

A touch of R in Robotics

Eric Wanjau

Ian Muchiri

Summary:

Over the years, the R community has experienced an increase in the number, diversity and domain background of users. However, incorporation of R in the field of …

The Past and Future of Shiny

Joe Cheng

Summary:

Shiny is a package that makes it easy to create interactive web apps using R. It's hard to believe, but it's been ten whole years since the launch of Shiny! …

Accelerating geospatial computing using Apache Arrow

Dewey Dunnington

Summary:

The ‘arrow’ R package and wider Apache Arrow ecosystem provide an end-to- end solution for querying and computing on in-memory and bigger-than-memory data sets …

It's about time

Davis Vaughan

Summary:

Dealing with date-times is hard. Dealing with date-times without the proper tooling is even harder! clock is an R package that aims to provide comprehensive and …

Creating a data input platform using tidyverse

Hezi Buba

Summary:

The Belmaker lab fieldwork involves underwater surveys where we document the observed marine species. Historically, Microsoft’s Access was used for data input. …

Yes, you can use Python with RStudio Team!

Gagandeep Singh

Xu Fei

Summary:

Are you a bilingual data scientist who wants to use Python in RStudio products? Or do you have colleagues who use Python for data science? In this talk, we will …

Cross-Industry Anomaly Detection Solutions with R and Shiny

Tanya Cashorali

Summary:

This session highlights two anomaly detection use cases in production: identification of problematic life sciences manufacturing units and identification of …

Building Accessible Lessons with R and Friends

Zhian N. Kamvar

Summary:

The Carpentries is a global community of volunteers who collaboratively develop and deliver lessons to build capacity in data and coding skills to researchers …

Comparing package versions with Diffify

Colin Gillespie

Summary:

Even when we run the simplest of R scripts, we are using dozens of R packages. We use packages for data cleaning, writing reports, graphics and modelling. One …

Exploratory Spatial Data Analysis in the tidyverse

Josiah Parry

Summary:

R has come quite a long way to enable spatial analysis over the past few years. Packages such as sf have made spatial analysis and mapping easier for many. …

Sometimes you just need words

Lewis Kirvan

Summary:

This talk will trace the evolution of a report from a mostly text free dashboard into a text heavy R markdown report with dynamic text blocks. The report in …

Cultivating Your Own R Ecosystem as a Solo Contributor

Meghan Hall

Summary:

It can be daunting to start using R when no one else in your office is! Using a case study from an administrative higher education office, learn how you can …

Designing for people is hard

Greg Swinehart

Summary:

Shiny users can prototype an app in minutes, but... What if it also looked better almost immediately? In this talk, we'll walk through a new look for Shiny's …

censored - Survival Analysis in tidymodels

Hannah Frick

Summary:

tidymodels is extending support for survival analysis and censored is a new parsnip extension package for survival models. It offers various types of models: …

Everything I learned about community building from growing up in a restaurant

Rachael Dempsey

Summary:

In community conversations at the Data Science Hangout, we’ve talked about misalignment between what recruiters are looking for and who is actually a great fit …

Making Data Pipelines in R

Meghan S Harris

Summary:

When people first learn about R’s capabilities to create fully integrated systems, automated visuals, and seamless data pipelines, the reaction can span from …

dbcooper: Turn any database into an R or Python package

David Robinson

Summary:

The first step of any data analysis is importing data, but for tables in a database this can be a surprisingly challenging step that takes analysts out of their …

WebR: R running in the browser

George Stagg

Summary:

In this talk I introduce webR, a port of R to WebAssembly using Emscripten. WebR brings a full R environment to the browser, enabling R code execution, …

Creating a Design System for Shiny and RMarkdown

Maya Gans

Summary:

A design system is a set of standards to manage design at scale by reducing redundancy while creating a shared language and visual consistency across different …

Demystifying the art of creating custom libraries for your organization

Dan Caley

Summary:

Demystifying the Art of creating custom Libraries for your organization. Imagine a world where a company has its own R library, this stores the most common …

What they forgot to teach you about starting a business with R

David Keyes

Summary:

Lots of people I meet want to start their own business. "I know how to use R," they figure, "so I should be able to go out on my own, find …

Hello Quarto

Mine Çetinkaya-Rundel

Julia Stewart Lowndes

Summary:

What is Quarto? In this talk, in four acts, we will discuss how Quarto unifies and extends the R Markdown ecosystem. Through our work with NASA Openscapes, Duke …

Let your mobile shine: Making shiny apps mobile responsive

Shelmith Nyagathiri Kariuki

Summary:

As shiny developers, we spend a lot of time working on the server side, and less time on the UI/UX part. According to the Engineering Production-Grade Shiny …

Let's start at the beginning - bits to character encoding in R

Alex Farach

Summary:

Attendees will recieve a broad overview of the encoding and decoding process in the human-to-computer loop, how bits are used, and the math that gets us to …

Say Hello! to Multilingual Shiny Apps

Nicola Rennie

Summary:

Multilingual shiny apps are not straightforward to build. Translation affects almost every single aspect of an app. Although there are a few packages designed …

Demystifying MLOps

Isabel Zimmerman

Summary:

Data scientists have an intuition of what goes into training a machine learning model, but building an MLOps strategy to deploy that model can sound daunting …

Oddly Satisfying - Find delight in the mundane

Liz Roten

Summary:

It happens to us all - a request to "just re-run the code" turns into a project nightmare. The materials left to you are poorly documented and …

Websites & Books & Blogs, oh my! Creating Rich Content with Quarto

Devin Pastoor

Summary:

A number of packages have emerged in the R ecosystem to help create websites (hugodown), books (bookdown), and blogs (blogdown). In this talk, I'll show you how …

The worlds smallest R environment? Running R on a $15 computer

Mark Sellors

Summary:

Is it possible to do meaningful work in R on a $35 computer? How about a $15 computer? And what does that mean for education, data science, and computing on …

A Robust Framework for Automated Shiny App Testing

Sydeaka Watson

Summary:

For production-grade Shiny applications, regression testing ensures that the application maintains its core functionality as new features are added to the app. …

R Markdown + RStudio Connect + R Shiny

Kolbi Parrish

Andy Pham

Summary:

R is more than just a tool for data analysis– it can help streamline and automate processes, including managing and monitoring data pipelines. This presentation …

Exploring Query Optimization

Rebecca Hadi

Summary:

If you find yourself waiting hours for your queries to run, this talk is for you. Learn from my query mistakes and avoid crashing your database.
In this talk, …

The Polygons of Another World - realtime interactive rendering in R

Mike Cheng

Summary:

In this talk I want to explore R's capabilities for fast, interactive graphical applications. This exploration is driven by my ongoing port of the 1991 action …

Making awesome automations with GitHub Actions

Beatriz Milz

Summary:

This talk is an introduction to GitHub Actions (GHA), which is a feature from GitHub that allows us to automate several tasks in R. In this presentation, I aim …

Dissecting the quick fix

Sigrid Keydana

Summary:

Machine learning models, applied in the real world, can have unanticipated, harmful side effects. Recommended counter-measures include structured documentation …

Building Impactful Shiny Dashboards at NIH

Jon Nye

Summary:

It can be difficult for small teams to make an impact in large organizations. In this talk I will discuss how my small team, at the National Institute of …

How to be a pollinatoR

Weihuang Wong

Kiegan Rice

Summary:

R users are part of data ecosystems comprising both statistical and non- statistical applications. We may work with SAS or Stata datafiles; non-R users may help …

The tidysynthesis R package

Aaron R. Williams

Summary:

Society benefits when leaders make more evidence-based decisions, but growing privacy concerns hamper researchers’ ability to understand and improve the world. …

Saving 1,000 hours with RStudio

Tiger Tang

Summary:

There are many benefits to using R and no lack of packages that help you solve technical difficulties, but you may still get stuck at selling it to …

Digging a Pit of Success for Your Organization

Aaron Chafetz

Summary:

How does a US federal agency analyze tens of millions of records across 30,000 sites in over 50 countries analyze these data efficiently and effectively? Five …

Tidyverse and Power BI

Ryan E Wade

Summary:

Power BI is a multi-faceted business intelligence tool with built-in data ingestion, transformation, and visualization features. The learning curve for Power BI …

Remote Content Execution with RStudio Connect and Kubernetes

Kelly O'Briant

Summary:

This summer the RStudio Connect team will announce a feature which has been over two years in the making: “Remote” off-host content execution with launcher in …

Building a ggplot2 rollercoaster

Tyler Morgan-Wall

Summary:

Have you ever had so much fun building a data visualization that it felt like a thrill ride? What if your dataviz actually WAS a thrill ride—a 3D virtual …

The Future of missing data

Nicholas Tierney

Summary:

If you do data analysis, you encounter missing data. Missing data upsets data analysis workflow because you have to make decisions on how to deal with it - do …

R Shiny - From Conception to the Cloud

Ivonne Carrillo Dominguez

Summary:

I will share how we published an R Shiny application to AWS, the decisions we made, and what we learned in the process.

One challenge we faced was figuring out …

Publishing Customer Facing Products with RStudio Connect

Benjamin Braun

Summary:

Benjy Braun, Chief Architect for 202 Group, shows why he and the 202 Group team decided to use RStudio Connect to build customer facing applications and secure …

Running Shiny without a server

Winston Chang

Summary:

Shiny for Python has the ability to be deployed without a server that runs Python. These applications can be served by any web hosting service. They are easily …

What they forgot to teach you about becoming an open source contributor

Nic Crane

Summary:

Getting involved in open source is an amazing learning experience and helps you grow your skills as a developer, but to a new contributor there are so many …

dm: Analyze, build and deploy relational data models

Kirill Müller

Summary:

dm bridges the gap in the data pipeline between standalone data frames and relational databases. Implementing a "grammar of joined tables", it …

I made an entire e-commerce platform on Shiny

Jacqueline Nolis

Summary:

E-commerce requires passing data between many components like managing a shopping cart, taking payment, fulfilling orders, and sending emails. I've successfully …

The Benefit of Talking to the "Non-Datas"

Caro Buck

Summary:

Data literacy is a tool to build understanding- of the world and ourselves. Data, AI and tech are sometimes portrayed as scary and unknowable; however, data can …

A Journey to Data Science

Ileana Fenwick

Summary:

Data suggests that less than 3% of data scientists are women of color. My journey and that of many other women who fall at the intersection of being …

You should be using renv

E. David Aja

Summary:

Dependencies don't have to be hell. In this talk we'll discuss how renv makes it easier to diagnose problems, move projects between environments, and …

Optimal allocation of COVID-19 vaccines in west Africa

Anubhuti Mishra

Summary:

In 2022, African countries need to vaccinate most of their population against COVID-19. With an influx of millions of doses, countries need to plan in near …

Highlights of the knitr package from the past two years

Yihui Xie

Summary:

In this talk, I will highlight a few selected new features of the knitr package introduced in the past two years including: 1) the new way to write chunk …

Model Migration

Johnny Breen

Summary:

Many companies within the insurance and financial sector maintain a large number of legacy models in the platform Microsoft Excel. With the advent of data …

Implications of R syntax in intro stats

Amelia McNamara

Summary:

This talk reports on a head-to-head comparison of the formula and tidyverse syntaxes in a full semester introductory statistics course, providing data to help …

leafdown: Interactive multi-layer maps in Shiny apps

Andreas Hofheinz

Summary:

Interactive maps are indispensable tools for exploring spatial datasets because of their real-world context and intuitiveness. For a comprehensive understanding …

Introducing workboots

Mark Rieke

Summary:

Sometimes, we want a model that generates a range of possible outcomes around each prediction. Other times, we just care about point predictions and may opt to …

Achieving a seamless workflow between R, Python and SAS from within RStudio

Melissa Van Bussel

Summary:

Some of my best friends use Python...and all of my coworkers use SAS.

Statistics Canada is the official statistical agency of Canada and employs over 6,000 …

RStudio: 2022 and Beyond

Hadley Wickham

JJ Allaire

Summary:

Garbage Data

Jim Kloet

Summary:

No matter the requirements of the project, data are rarely ready for analysis without some intervention up front, often described as cleaning or tidying up your …

Robust R Deployments

David Maguire

Summary:

R is often maligned as a poor fit for production deployment systems. At dv01 we deploy Plumber API that serves machine learning models to Tape Cracker, a client …

Developing internal tools for multi-lingual teams

Jamie Ralph

Summary:

Internal packages are great for boosting productivity and promoting good practice, but what kinds of challenges do we face when designing solutions for …

Quarto for the Curious

Tom Mock

Summary:

Are you curious about Quarto? Maybe you saw it on Twitter or the RStudio::conf agenda. Perhaps this raised questions like: What exactly is Quarto? What about …

Designing a Socially-Critical Data Science Course

Brian Danielak

Summary:

I'll discuss designing a socially-conscious and socially-critical data science course. This talk will be interesting to anyone who designs or delivers …

R Package Assessment

Becca Krouse

Summary:

As R users, we make choices daily about what packages to use in our work. After discovering a package that may suit our needs, we consider its qualities and …

Scaling and automating R workflows with Kubernetes and Airflow

Isaac Florence

Summary:

During the pandemic, epidemiologists have been forced to adapt to the unprecedented scale of the data and high cadence of reporting.

At the UK Health Security …

Dashboard-Builder

Peter Gandenberger

Summary:

I would like to create (more) Shiny Dashboards, but...

• I don't know how
• I can't write R code
• it's too complex
• I don't have enough time (even though I know how …

ggplot internals with {ggtrace}

June Choe

Summary:

The inner workings of {ggplot2} are difficult to grasp even for experienced users because its internal object-oriented (ggproto) system is hidden from user- …

Introducing Rhino

Kamil Zyla

Summary:

R and Shiny are ready for production use in Enterprise. As Appsilon, we have worked with tens of top global companies on their Shiny projects. Emphasis on UI, …

Building a client portal app with embedded Power BI reports

Thomas Wouters

Joran De Wilde

Summary:

With the Dutch Mortgage Portfolio Management Group we built a client portal for their customers wanting insights into their mortgage investment portfolio. This …

Visualizing distributions and uncertainty using ggdist

Matthew Kay

Summary:

I propose a talk on visualizing distributions and uncertainty using {ggdist}. I will describe how to think systematically about distributional visualization as …

Dive Deep into Metadata with Tplyr

Mike Stackhouse

Summary:

Back in 2020, Atorus first released our package Tplyr. The aim of Tplyr was to build a reusable framework that makes all the data preparation for clinical …

A new way to build your Shiny app's UI

Nick Strayer

Summary:

Shiny helps data scientists create web applications without requiring web development experience. However, there's still a steep learning curve for writing the …

Translating from {tidymodels} and scikit-learn

Kelly Bodwin

Summary:

The friendly competition between R and python has gifted us with two stellar packages for workflow-style predictive modeling: tidymodels in R, and scikit- learn …

tidyclust - expanding tidymodels to clustering

Emil Hvitfeldt

Summary:

This talk marks the grand introduction of tidyclust, a new package that provides a tidy unified interface to clustering model within the tidymodels framework. …

Enterprise-Level Data Science Success

Prabhakar Thanikasalam

Summary:

Enterprise-Level Data Science Success includes many factors beyond the nuts and bolts of core data science work. It is not just about data, databases, data …

{shinyslack}

Jon Harmon

Summary:

Slack is a useful communication tool for communities and businesses. Integrating it with Shiny can make it even more useful. I'll show how my {shinyslack} …

Zero-setup R workshops with GitHub Codespaces

David Smith

Summary:

If you've ever tried to run a workshop using R, you'll be aware of the challenges of getting everyone's laptop set up to able to run your R scripts, Rmarkdown …

Packages and Process

Ellis Hughes

Summary:

Data Scientists have a unique position to drive change and efficiency within organizations workflows. By simplifying workflows to its core expectations, we can …

From summarizing projects to setting tags, uses of parsing R files

Bryan Shalloway

Summary:

I'll walk through a few potential uses of parsing out the functions and packages in projects.

• Creating a reference table: With so many #rstats learning …

Tidy Transit

Hunter Owens

Summary:

California Integrated Travel Project’s mission is to make transit across California simpler and more affordable. As part of this, we created an open source data …

Project Immortality With GitHub

Tan Ho

Summary:

If you've invested a lot of time and energy on a data science project, you might be ready to move on to new and exciting things. Don't let your old projects …

Becoming Creative: Quilting with R

Alice Walsh

Summary:

When someone asks about essential skills for data careers, I often hear responses like R, Python, and machine learning. However, I argue that creativity is an …

Data science training in communities with limited resources and opportunities

Jeff Leek

Summary:

I'm so excited to be back with the data science community at rstudio::conf! Data science is a field that touches nearly every part of our modern lives - from …

An Integrated Workflow

Lawrence Y. Tello

Summary:

The California Department of Public Health’s (CDPH) COVID-19 response has required processing and communicating large amounts of data with quick turnaround …

These are a few of my favorite things (about Quarto presentations)

Tracy Teal

Summary:

Quarto is the next generation of RMarkdown, and comes with a new presentation format, revealjs. In this talk, I’ll show a few of my favorite things about making …

How Anchorage Built Alaska’s Vaccine Finder with R

Ben Matheson

Summary:

In January 2021, Alaska residents seeking a COVID-19 vaccine appointment faced a convoluted maze of websites. The software was made for providers—not for …

An Introduction to the Apple Health Export

John Goldin

Summary:

After a visit to the ER, I discovered an ocean of personal data: more than 3 million rows of data about one of my favorite subjects: me. My watch averages …

An introduction to R7

Hadley Wickham

Summary:

The R7 package is a new OOP system designed to be a successor to S3 and S4. It has been designed and implemented collaboratively by the RConsortium Object- …

{shinytest2}

Barret Schloerke

Summary:

Manually testing Shiny applications is often laborious, inconsistent, and doesn’t scale well. Whether you are developing new features, fixing bug(s), or simply …

R, Python, and Tableau

James Blair

Summary:

Users often want access to more advanced analytic capabilities in their Tableau dashboards. Together we will walk through an example that highlights how new …

We R KaggleRs - At the Intersection of Data Science Communities

Martin Henze

Summary:

In this presentation, I will share my experiences at the intersection of the R and Kaggle communities. As Kaggle's first Notebooks Grandmaster, I will talk …

Advocating for Automation

Hannah Podzorski

Summary:

Increasing quantity and types of available data and the need for more advance analyses are outpacing current tools in environmental science. R allows us to …