2023 Posit Year in Review
From exciting product updates to insightful discussions in our weekly hangouts, the past year has been filled with growth and learning. Join us as we revisit significant highlights for our community over the last 12 months.
In September, we concluded the first posit::conf. Whether you attended online or in person in Chicago, we’re glad you were part of it.
- Check out the talk recordings and workshop materials.
We’ve kept the momentum going with our weekly Data Science Hangouts series, gaining valuable insights from industry leaders. Additionally, we introduced a new series called End-to-End Data Science Workflows, demonstrating the creation of analytic platforms that facilitate open-source data science. Watch three reasons you should join the event.
2023 was a year of celebration of the adoption of R in the pharmaceutical industry, from webinars with Roche and Novo Nordisk to the marking of five years of R/Pharma. We had the opportunity to share several success stories, such as Eric Nantz, Director of the Statistical Innovation Center at Eli Lilly and Company, discussing how he has seen Shiny create value in the clinical trials process.
Our cheatsheets are short, handy guides summarizing important concepts, functions, and syntax for popular Posit tools. Now, each cheatsheet comes with an HTML version, and we’ve launched a dedicated cheatsheet website. Learn more about cheatsheets!
The gt package, used for crafting attractive, customized tables in R, brought forth many new features in v0.9.0, including but not limited to: New formatting functions, summary rows, font stacks and Markdown improvements, text functions, color coding data, column customization, and interactive tables. And that’s not even counting the new features in v0.10.0!
Beautiful display tables aren’t exclusive to R – explore the Great Tables package for Python!
Deep Learning and Scientific Computing with R torch was released in April, which explores how to dive into deep learning using the R programming language. There were updates to several packages in the mlverse, such as torch and safetensors. Tomasz Kalinowski also shared a walkthrough of LLaMA, a Large Language Model, in R with TensorFlow and Keras. There are many more articles on LLMs on the AI Blog.
- Code annotations
- Multi-format publishing
- Confluence publishing
The 1.4 release introduces even more exciting updates:
- Quarto dashboards: a new format for creating interactive dashboards. Watch a walkthrough on Quarto dashboards, presented by Charles Teague.
- Quarto manuscripts: a new project type for scholarly articles, where notebooks are both the source of the article and part of the published record. Watch a video on Quarto manuscripts, presented by J.J. Allaire.
- Typst format: Typst is a new open-source markup-based typesetting system that is designed to be as powerful as LaTeX while being much easier to learn and use. Watch a posit::conf talk on Typst, presented by
- Email, Shiny for Python, lightbox treatment, and more.
Stay tuned for the 1.4 announcement on the Quarto blog!
RStudio Desktop (the free IDE) had a fantastic year, introducing new user guides, enhanced auto-completion and accessibility features, and more. Additionally, AI-related tools like GitHub Copilot support in the IDE and the chattr package, offering an interface to Large Language Models (LLMs), are now available.
Shiny is a tool for making web apps with R or Python, no web development skills required. Shiny for R received many exciting updates, including dark mode, tooltips, and popovers. The ShinyUiEditor has also transitioned out of alpha, making it easier for you to design your Shiny UI.
Last year, we announced Shinylive, a tool for running Shiny for Python directly in the browser. Thanks to the magic of webR (more on webR below), Shinylive is also available in R. That means R users can also run Shiny apps in the browser, no server necessary! Watch Joe Cheng’s posit::conf(2023) video on Shinylive for R and see examples on the Shinylive website.
Shiny for Python entered General Availability and is ready for use in production. It comes with user guides, examples, and numerous features. Explore all the details on the Shiny blog, and read insights into “Why Shiny for Python?“
The tidymodels framework is a collection of R packages for modeling and machine learning using tidyverse principles. Every quarter, the team releases a roundup of their updates. This year saw speed improvements, updated warnings, and better error messages, as well as a host of new and updated packages. See the updates for Q1, Q2, Q3, and Q4.
If you are new to tidymodels, check out these bite-sized tips for getting started!
The tidyverse is an opinionated collection of R packages designed for data science. Numerous tidyverse packages, such as tidyr and dbplyr, received a wave of updates. We have five posts on the updates to dplyr! Dive into the details on the tidyverse blog.
Check out our latest releases for mastering data science in R:
- The second edition of R for Data Science is now out! Discover how to bring your data into R, wrangle it effectively, make changes, and create visualizations.
- The second edition of R Packages has also been released! Learn how to create a package, the fundamental unit of shareable, reusable, and reproducible R code.
MLOps are a set of practices to deploy and maintain machine learning models in production. Isabel Zimmerman shares some considerations for assessing whether your team needs MLOps.
The vetiver package provides fluent tooling to version, share, deploy, and monitor a trained model in R and Python. Julia Silge shares how it now provides fluent support for deploying models to Amazon SageMaker.
Have you heard about webR? This amazing tool allows you to use R in the browser – no server needed! Users can interact and experiment with R code without switching between a web browser and an R console or dealing with copying and pasting example code. George Stagg, developer of webR, showcases the tool in several intro videos.
Databricks and Posit are partnering to help professional data teams do more with the power of their favorite data science tools seamlessly integrated with Databricks. We’ve already made significant improvements to open source and enterprise, such as updates to sparklyr and the addition of a Databricks Pane in RStudio Pro. Check out our recent webinar to learn more!
RStudio is now available in Amazon SageMaker, helping R users scale development environments and take advantage of their organization’s data on AWS.
Posit Cloud, our online platform to do and share data science, makes it simple for multiple projects and people to access external databases with Data Connections. In addition, you can now create custom project templates in Posit Cloud to start coding faster by automating recurring workflows.
Alex Chisholm showcases tips, features, and use cases during our Posit Cloud Essentials series.
Posit Connect is a publishing platform for your R and Python data products. Posit Connect’s support for off-host content execution in Kubernetes is now in General Availability, enabling your content to be built and executed in remote containers.
Starting this year, Posit Connect can host Voilà and Jupyter Widgets for adding interactive elements to a Jupyter Notebook.
Posit Connect also supports publishing Python apps and dashboards built with frameworks like Shiny, Streamlit, Dash, Bokeh, and Voilà on all license types.
Posit Package Manager
Posit Package Manager is a repository management server to organize and centralize R and Python packages across your organization. The Package Manager Team reached a significant milestone, compiling a whopping ten million pre-built R package binaries for efficient package management.
This year, Package Manager enabled the creation of curated repositories for Python packages from PyPI. Additionally, it preserved access to historical CRAN package snapshots, aiding users in transitioning from Microsoft R Application Network (MRAN).
Most recently, Package Manager added vulnerability scanning based on the osv.dev database, as well as the ability to easily block all packages with known vulnerabilities.
Posit Workbench is the development environment for data science, where your teams can access RStudio, Jupyter, and VS Code in a secure, collaborative place. Alongside the enhancements mentioned in RStudio Desktop, Posit Workbench introduces several improvements in Slurm, Launcher, performance, load balancer, and other areas.
When accessing data in AWS, Azure, or Databricks, Workbench users can now take advantage of pass-through authentication, eliminating the need for users to manage complex authentication workflows or manually refresh their credentials.
Posit has partnered with Altair to integrate Workbench with Altair Grid Engine (AGE), enabling the execution of Workbench sessions on AGE-based HPC clusters.
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