Rstudio::conf 2020
Total Tidy Tuning Techniques
February 12, 2020
Many models have structural parameters that cannot be directly estimated from the data. These tuning parameters can have a significant effect on model performance and require some mechanism for...
Of Teacups, Giraffes, & R Markdown
February 6, 2020
How do you make your R Markdown lessons feel friendly for learners you’ll never meet? How do you make it engaging so they sit and stay a while?
Not So Standard Deviations Episode 100
February 6, 2020
In episode 100 of Not So Standard Deviations, the first ever episode prepared in advance, Hilary and Roger discuss creativity, its role in data science, & how it can be fostered through conversation.
Data Science Education in 2022
February 6, 2020
More people are learning data science every day, and there are more ways for them to learn than ever before.
Branding and Packaging Reports with R Markdown
February 6, 2020
The creation of research reports and manuscripts is a critical aspect of the work conducted by organizations and individual researchers. Most often, this process involves copying and pasting output...
Data, visualization, and designing AI
February 6, 2020
Recent progress in machine learning has raised a series of urgent questions: How can we train and debug deep learning models? How can we understand what is going on inside a neural network?
Technical Debt is a Social Problem
February 5, 2020
Technical debt is a big problem for the R community. Even though R has excellent support for testing, documentation and packaging code it has the reputation that it is not suitable for production...
renv: Project Environments for R
February 5, 2020
The renv package helps you create reproducible environments for your R projects. With renv, you can make your R projects more: Isolated...
TidyBlocks: using the language of the Tidyverse in a blocks-based interface
February 4, 2020
Blocks-based coding environments are a popular way to introduce programming to novices. Instead of typing in code, users click blocks together to create loops, conditionals, and expressions.
The Five Principles of Data Science Education
February 4, 2020
In this talk, I will outline a unified philosophy of data science education, and provide tips and tools for implementing these principles in the classroom using R and RStudio.
Spruce up your ggplot2 visualizations with formatted text
February 4, 2020
The ggtext package provides various functions to add formatted text to ggplot2 figures, both in the form of plot or axis labels and in the form of text labels or text boxes inside the plot panel.
Sound annotation with Shiny and wavesurfer
February 4, 2020
We observed a huge improvements of Machine Learning tools but the main effort were to help at post annotated dataset step.
Rproject templates to automate and standardize your workflow
February 4, 2020
Many teams and organizations have tasks and structures that are standard across projects. Lack of consistency and documentation can lead to lost productivity when team members join collaborations...
Peer review in data science courses
February 4, 2020
Peer review enables instructors of large data science classes to provide substantive feedback to students beyond what is feasible with standard code review via automated grading and continuous...
One R Markdown Document, Fourteen Demos
February 4, 2020
R Markdown is a document format based on the R language and Markdown to intermingle computing with narratives in the same document.
Mexican electoral quick count night with R
February 4, 2020
In Mexico the elections take place on a Sunday, and the official results are presented a week later.
Making a tidy dress
February 4, 2020
After at least a year of dreaming about it, I finally produced the #rstats / #Tidyverse dress of my dreams.
livecode: broadcast your live coding sessions from and to RStudio
February 4, 2020
In this talk we will demonstrate `livecode`, a new R package for broadcasting code for live code demonstrations. This package implements a simple webserver (using `httpuv`) to dynamically publishes...
Lessons about R I learned from my cat
February 4, 2020
Forming good development habits for R projects is pretty straight-forward if you follow the lessons I've learned from my cat, whose advice includes "be lazy", "keep your claws sharp", and...
Learning by Teaching: Mentoring at the R4DS Online Learning Community
February 4, 2020
I host a weekly R Office Hour on the R4DS Online Learning Community Slack. By doing so, I have learned more about R than I ever would have thought.
Learn to teach, for goodness sake
February 4, 2020
Even though I’ve completed 4 marathons, you certainly shouldn’t come to me for a training plan on how to achieve your goals for any race you’re about to run.
How Rmarkdown changed my life
February 4, 2020
Over the last few years, Rmarkdown seems to have taken over my life, or at least my written communication.
Extending your ability to extend ggplot2
February 4, 2020
The ggplot2 package continue to be one of the most used frameworks for producing graphics in R. While being extremely flexible, the package itself can be constrained by the different types of...
Every voice matters: An analysis of @WeAreRLadies
February 4, 2020
As a rotating curation, @WeAreRLadies is a twitter account that has a different curator (i.e., tweeter) each week with a mission to highlight female and minority genders and their work in R.
Datasets in Reproducible Research with 'pins'
February 4, 2020
Open source code is an essential piece in making science reproducible. Tools like 'rmarkdown' and GitHub facilitate running and sharing outcomes with colleagues and with the broad scientific community
Data Science for Software Engineers: busting software myths with R
February 4, 2020
Is agile development really the secret to success? Do some languages actually cause more defects than others? This talk describes a series of meaningful lessons that...
Course Material Creation in the R Ecosystem
February 4, 2020
In this talk, I will introduce a suite of three packages designed to aid course material creation in R: {demoR} for displaying code in knitted R Markdown with custom highlighting and formatting...
Becoming an R blogger
February 4, 2020
Blogging is an excellent way to learn, improve your communication skills, and gain exposure in the R and data science communities.
A high school student’s journey to bring R into the classroom
February 4, 2020
My 8th grade capstone project introduced me to R. The project was a data visualization about breakfast tacos. I used R and other web based tools.
Open Source Software for Data Science
February 1, 2020
Open-source software is fundamentally necessary to ensure that the tools of data science are broadly accessible, and to provide a reliable and trustworthy foundation for reproducible research.
UnicoRns are real
January 31, 2020
Common advice from experienced data scientists to job-seekers is to avoid job postings that describe a "data science unicorn": someone who has experience performing an unrealistically large array...
The little package that could: Taking visualizations to the next level with the scales package
January 31, 2020
Precise axes, proper data transformation, and informative visual data mappings are critical components to any polished visualization.
Stochastic Block Models with R: Statistically rigerous clusting with rigorous code
January 31, 2020
Often a machine learning research project starts with brainstorming, continues to one-off scripts while an idea forms, and finally, a package is written to disseminate the product.
Small Team, Big Value: Using R to Design Visualizations
January 31, 2020
Many R users can feel isolated due to the prevalence of Python or Tableau at their institutions.
Shiny New Things Using R Bridge the Gap in Electronic Medical Record Reporting
January 31, 2020
Electronic Medical Records (EMRs) are a treasure trove of information, but tend to fall disappointingly short when it comes to visualizing and reporting data in a user friendly and intuitive manner.
RStudio 1.3 Sneak Preview
January 31, 2020
RStudio 1.3, currently available as a preview release, includes a number of new capabilities that will help you be more productive in R. It's also more configurable, accessible, and flexible.
RMarkdown Driven Development
January 31, 2020
RMarkdown enables analysts to engage with code interactively, embrace literate programming, and rapidly produce a wide variety of high-quality data products such as documents, emails, dashboards...
Platelet Transfusion Management using R and the Tidyverse
January 31, 2020
Development of a web-based clinical decision support application for platelet transfusion management using R and the Tidyverse Blood product transfusion is a high risk and costly medical procedure.
Panel: Career Advice for Data Scientists
January 31, 2020
This panel will be focused on how you build a career around R! Our panelists are all passionate about R and have each taken a different path to build a career around that passion.
Object of type ‘closure’ is not subsettable
January 31, 2020
Your first “object of type ‘closure’ is not subsettable” error message is a big milestone for an R user. Congratulations, if there was any lingering doubt, you now know that you are officially...
Neural Networks for Longitudinal Data Analysis
January 31, 2020
Longitudinal data (or panel data) arise when observations are recorded on the same individuals at multiple points in time.
MLOps for R with Azure Machine Learning
January 31, 2020
Azure Machine Learning service (Azure ML) is Microsoft’s cloud-based machine learning platform that enables data scientists and their teams to carry out end-to-end machine learning workflows at scale.
List-columns in data.table: Reducing the cognitive & computational burden of complex data
January 31, 2020
The use of list-columns in data frames and tibbles is well documented (e.g. Bryan, 2018), providing a cognitively efficient way to organize results of complex data (e.g. several statistical models...
Interactivity and Programming in the Tidyverse
January 31, 2020
In Tidyverse grammars such as dplyr you can refer to the columns in your data frames as if they were objects in the workspace. This syntax is optimised for interactivity and is a great fit for data...
Forecasting Platelet Blood Bag Demand to reduce Inventory Wastage at the Stanford Blood Center
January 31, 2020
The Stanford Blood Center collects and distributes blood products to Stanford Hospital. One of these is platelets, a vital clot-forming blood component with a limited shelf life of a few days.
Don’t repeat yourself, talk to yourself! Repeated reporting in the R universe
January 31, 2020
If you’re responsible for analyses that need updating or repeating on a semi-regular basis, you might find yourself doing the same work over and over again.
Data Science in Meatspace
January 31, 2020
The Data Science community is dominated by folks doing amazing work with data that starts in and never leaves cyberspace.
Building a Medical Device with R
January 31, 2020
The InsightRX precision dosing platform tailors in-patient drug doses to individual patients' characteristics and biomarkers, leveraging pharmacological models of drug metabolism and drug effects.
Bridging the Gap between SQL and R
January 31, 2020
Like it or not, SQL is the closest thing we have to a universal language for working with structured data. Celebrating its 50th birthday in 2020, SQL today integrates with thousands of applications...
Best practices for programming with ggplot2
January 31, 2020
The ggplot2 package is widely acknowledged as a powerful, dynamic, and easy-to-learn graphics framework when used in an interactive environment.
Auto-magic Package Development
January 31, 2020
Vega-lite is a high-level grammar of interactive graphics implemented in Javascript; it renders interactive visualizations in the browser based on a JSON specification.
What's new in TensorFlow for R
January 30, 2020
TensorFlow is the most popular open-source platform for machine learning and it's ecosystem is evolving incredibly fast.
We’re hitting R a million times a day so we made a talk about it
January 30, 2020
For the past year, we at T-Mobile have been sludging through production outages, nation-wide product launches, and all of the muck that floods from R models being hit over a million times every day.
vctrs: Creating custom vector classes with the vctrs package
January 30, 2020
The base R types of vectors enable the representation of an amazingly wide array of data types. There is so much you can do with R.
Using R to Create Reproducible Engineering Test Reports
January 30, 2020
Writing scripts in R that create reproducible reports can significantly reduce the time spent by an engineer creating these reports allowing them to do a thorough investigation with a larger scope.
Toward a grammar of psychological experiments
January 30, 2020
Why does a psychological scientist learn a programming language? While motivations are many and varied the two most prominent are data analysis and data collection.
The good, the bad and the ugly: What I learned while consulting across the business as a data scientist
January 30, 2020
A collection of data science stories about current problems that data scientists might face while working in academia, industry, and government.
The Glamour of Graphics
January 30, 2020
I see a lot of ugly charts. This is to be expected as I work with a lot of academics and data scientists, neither of whom have been trained in how to design attractive charts.
Styling Shiny apps with Sass and Bootstrap 4
January 30, 2020
Customizing the style--fonts, colors, margins, spacing--of Shiny apps has always been possible, but never as easy as we’d like it to be.
Simplified Data Quality Monitoring of Dynamic Longitudinal Data: A Functional Programming Approach
January 30, 2020
Ensuring the quality of data we deliver to customers or provide as inputs to models is often one of the most under-appreciated and yet time-consuming responsibilities of a modern data scientist.
Rpanda trading simulation - from an idea to a multi-user shiny app
January 30, 2020
As energy trading professionals working in the industry, we had developed insights around how to make risk/reward market calls, and what skills make someone an exceptional commodities trader.
Reproducible Shiny apps with shinymeta - Dr. Carson Sievert
January 30, 2020
Shiny makes it easy to take domain logic from an existing R script and wrap some reactive logic around it to produce an interactive webpage where others can quickly explore different...
R: Then and Now
January 30, 2020
R has changed a lot since the meetup was founded 10 years ago. Back then we were using base graphics (or lattice) and the apply family of functions and we didn't have pipes.
R for Graphical Clinical Trial Reporting
January 30, 2020
Interactive graphical reports go a step further and allow the most important information to be presented by default, while inviting the reviewer to drill down to see other details.
R + Tidyverse in Sports
January 30, 2020
There are many ways in which R and the Tidyverse can be used to analyze sports data and the unique considerations that are involved in applying statistical tools to sports problems.
Putting the Fun in Functional Data: A tidy pipeline to identify routes in NFL tracking data
January 30, 2020
Currently in football many hours are spent watching game film to manually label the routes run on passing plays.
Professional Case Studies
January 30, 2020
The path to becoming a world-class, data-driven organization is daunting.
Production-grade Shiny Apps with golem
January 30, 2020
Shiny is an amazing tool when it comes to creating web applications with R. Almost anybody can get a small Shiny App in a matter of minutes, provided they have a basic knowledge of R.
Practical Plumber Patterns
January 30, 2020
Plumber is a package that allows R users to create APIs out of R functions. This flexible approach allows R processes to be accessed by toolchains and frameworks outside of R.
Parallel computing with R using foreach, future, and other packages
January 30, 2020
Steve Weston's foreach package defines a simple but powerful framework for map/reduce and list-comprehension-style parallel computation in R.
Meet You Where You R
January 30, 2020
At RStudio, we wake up and go to bed thinking about the positive impact that open source work and data science has had and can have on the world.
Making better spaghetti (plots): Exploring the individuals in longitudinal data with the brolgar pac
January 30, 2020
There are two main challenges of working with longitudinal (panel) data: 1) Visualising the data, and 2) Understanding the model.
Learning R with humorous side projects
January 30, 2020
What should you name a new dinosaur discovery, according to neural networks? Which season of The Golden Girls should you watch when playing a drinking game?
Journalism with RStudio, R, and the Tidyverse
January 30, 2020
The Associated Press data team primarily uses R and the Tidyverse as the main tool for doing data processing and analysis.
If you build it, they will come...but then what? Facilitating communities of practice in R
January 30, 2020
Why did you learn R? Chances are good that if you're an attendee of rstudio::conf, you've found a community of R coders who are willing to share their knowledge and learn with you.
How Vibrant Emotional Health Connected Siloed Data Sources and Streamlined Reporting Using R
January 30, 2020
Vibrant Emotional Health is the mental health not-for-profit behind the US National Suicide Prevention Lifeline, New York City's NYC Well program, and various other emotional health contact center...
How to win an AI Hackathon, without using AI
January 30, 2020
Once “big data” is thrown into the mix, the AI solution is all but certain. But is AI always needed?
Growth Hacking with R - Product Analytics at Scale using R and RStudio
January 30, 2020
Salesforce is not only a cloud software solution out of the box, but also a highly customizable platform that can be modified for a wide range of use cases.
Getting things logged
January 30, 2020
One of the greatest strength of R is the ease and speed of developing a prototype (let it be a report or dashboard, a statistical model or rule-based automation to solve a business problem...
Future: Simple Async, Parallel & Distributed Processing in R - What's Next?
January 30, 2020
Future is a minimal and unifying framework for asynchronous, parallel, and distributed computing in R.
Flipbooks
January 30, 2020
Good examples facilitate accomplishing new or unpracticed tasks in a programmatic workflow. Tools for communicating examples have improved in recent years.
