Posit PBC

Real World Applications of Open Source in Public Health with Idaho Southwest Health District, Oregon Health Authority, and Vermont Department of Health ✨ Join us on July 17th at 11 a.m. ET to hear from Public Health professionals about how they leverage Posit Academy and open-source tools to serve their communities! What is Posit Academy? Posit Academy is a mentor-led apprentice program that follows a project-based learning format. Like riding a bike or playing the piano, Posit Academy participants learn by doing with real-world applications. They are placed in small groups under the guidance of a mentor to motivate and support one another throughout their learning journey. Save the date by adding the event to your calendar → https://lnkd.in/gNwyNfj2

Winners of the 2024 Posit Table Contest! Check out the winners and highlights, https://lnkd.in/gzZSGgPx ⬡ Winner, Today’s Top Hits – Spotify Dashboard, By Melissa Van Bussel ⬡ Runners Up 1, Podcast Index Database Dashboard, By Eric Nantz ⬡ Runners Up 2, Transfermarkt Contract Detector Shiny Application, By Ekrem Bayar ⬡ The Outstanding Novice Submission, Top AI Companies Stock Performance, By Arnav Chauhan ⬡ The Best Static Table, Rolling Stone’s Greatest Albums of All Time, By Sukalpo Saha ⬡ The Best Interactive Table, Top Ranked Board Games, By Richard Bamattre ⬡ The Best Tutorial (feat. Tables), Engaging tables with R or Python using {gt}, By Albert Rapp ⬡ The Best Single-Table Example, Arizona Indigenous Tribal Water Rights, By Greg Chism ⬡ The Best Shiny Table, Stock-specific summaries and optimal portfolio weights, By Christoph Scheuch ⬡ The Best {reactable} Table, Create a Interactive Table for Adverse Events Analysis for Clinical Trials, By Bingjun Wang & Yujie Zhao ⬡ The Best {gt} Table, Resumen Sistema Educativo en Córdoba Capital, By Illak Zapata ⬡ The Greatest Great Tables Table, Hourly Transit Service Patterns, By Tiffany Ku ⬡ The Best Table that Uses Polars, Euro NCAP Safety Ratings – 2023, By Jerry Wu ⬡ The Best Sports Table, Scottie Scheffler’s Dominance, By Stephan Teodosescu ⬡ The Best Pharma Table, Complete Clinical Study Report Tables with gtsummary, By Agustin Calatroni & Daniel D. Sjoberg ⬡ The Best Finance Table, Tables for Personal Finance (Ebenezer), By Deepansh Khurana ⬡ The Special Prize for Going Viral with a Table, Carbon Intensity of Electricity Consumption, By Grant Chalmers

Take your R and Python workflows to the next level with Posit Professional Tools. Join our workshops at posit::conf(2024) to explore the possibilities: • DevOps for Data Scientists, led by Rika Gorn: Learn the basic principles and tools of DevOps and get hands-on experience with DevOps workflows in production. • Using Databricks with R, led by Edgar Ruiz Discover the latest methods to connect and interact with Databricks services. • Data Science Workflows with Posit Tools — Python Focus, led by Sam Edwardes and Gagandeep Singh: Build a streamlined, Pythonic data science workflow using Posit’s professional products and open-source tools. • Data Science Workflows with Posit Tools — R Focus, led by Ryan Johnson and Katie Masiello: Enhance your data science workflows using open-source packages and Posit’s professional tools, including Workbench, Connect, and Package Manager. Learn more in the workshop catalog: https://lnkd.in/dscykZMr

Predicting lending rates with Databricks, tidymodels, and Posit Team. 🙌 Machine learning algorithms are reshaping financial decision-making, changing how the industry manages financial risk.   These advanced algorithms can analyze vast amounts of data to deliver predictive insights, which creates new opportunities to drive informed decisions or to expedite client service. During a recent online event, Garrett Grolemund demonstrated how to create a machine-learning model using publicly accessible loan applicant data from LendingClub. The final product? A personalized lending rate prediction model tailored to individual criteria that features the new, seamless experience between Databricks and Posit. 🔗 See the full guide → https://lnkd.in/gGNdaiM2 📹 Watch the event recording → https://lnkd.in/gVXM8aUM

We’re extremely pleased to announce the release of nanoparquet 0.3.0. nanoparquet is a new R package that reads Parquet files into data frames and writes data frames to Parquet files. Parquet is a file format for storing data on disk. It is specifically designed for large data sets, read-heavy workloads, and data analysis. Although Parquet is well supported by modern languages, today the complexity of the Parquet format often outweighs its benefits for smaller data sets. Many tools that support Parquet are typically used for larger, out-of-memory data sets, so there is a perception that Parquet is only for big data. These tools typically take longer to compile or install, and often seem too heavy for in-memory data analysis. With nanoparquet, we wanted to have a smaller tool that has no dependencies and is easy to install. Our goal is to facilitate the adoption of Parquet for smaller data sets, especially for teams that share data between multiple environments, e.g. R, Python, Java, etc. Learn more on the tidyverse blog: https://lnkd.in/g59pE8aK

posit::conf(2024) ❤️ R users! Join us for workshops designed for R programming enthusiasts of all skill levels. • R in Production, led by Hadley Wickham: Master writing reliable R code for production environments, with a focus on ease of debugging when issues arise. • Package Development: The Rest of the Owl, led by Jenny Bryan: Discover the nuances of writing R code for packages, distinguishing it from script-based coding. • Introduction to Data Science with R and Tidyverse, led by the Posit Academy Team: Build a solid foundation in R for data science through a hands-on, mentor-led apprenticeship for working professionals. • What They Forgot To Teach You About R, led by Shannon Pileggi, PhD and E. David Aja: Enhance your debugging skills and personal R administration as an experienced R programmer. • From R User to R Programmer, led by Emma Rand and Ian Lyttle: Sharpen your R programming skills and minimize code duplication. More details are available in the workshop catalog: https://lnkd.in/dscykZMr

Machine learning and modeling are key skills in data science, and the field is always evolving. At posit::conf(2024), we are offering five workshops specifically for R and Python users eager to deepen their knowledge: • Causal Inference in R, led by Malcolm Barrett and Travis Gerke, ScD:  Learn to answer causal questions using causal diagrams, propensity score modeling, and more. • Introduction to machine learning in Python with Scikit-learn, led by Tiffany Timbers and Trevor Campbell: Discover machine learning with tabular data using Python's Scikit-learn framework. • Intro to MLOps with vetiver, led by Isabel Zimmerman: Explore the vetiver framework in Python and R for efficient versioning, deployment, and monitoring of machine learning models in production. • Introduction to tidymodels, led by Hannah Frick and Simon P. Couch: Learn machine learning with tabular data using the tidymodels framework. • Advanced Tidymodels, led by Max Kuhn: Take an advanced class to optimize models, conduct feature engineering, and perform other advanced tasks using tidymodels. For more details, visit our workshop catalog: https://lnkd.in/dscykZMr

We’re excited to announce our partnership with Talk Python Training to offer a free Shiny for Python course. We’d love for you to check it out! If you've struggled (or just wondered) how to publish and share your data science projects and results in an interactive and live web app, then this course is 100% for you. Here are a few things covered in the course: • Learn how to build full-featured web applications in Shiny • Understand how Shiny uses transparent reactive programming to efficiently update your application • Learn how to use reactive calculations to automatically cache shared calculations • Build dynamic user interfaces that respond to user actions • Layout and style your application to create beautiful dashboards Get started here: https://lnkd.in/g-h3rYPn

Thanks to tools like Quarto, {ggplot2}, {gt}, and Great Tables, there are endless possibilities for communicating data results in engaging ways. We're excited to announce five workshops at posit::conf(2024) to boost your communication skills: • Making Tables with gt and Great Tables, led by Richard Iannone and Michael Chow: Create publication-quality tables. • Effective Data Visualization with ggplot2, led by Claus O. Wilke: Enhance your figure design skills with advanced tips. • Introduction to Quarto, led by Andrew Bray: Author diverse documents. • Quarto Websites, led by Charlotte Wickham and Emil Hvitfeldt: Build a website from scratch. • Build-a-Dashboard Workshop, led by Mine Çetinkaya-Rundel: Design sleek dashboards with Quarto. For more details, visit our workshop catalog: https://lnkd.in/dscykZMr

We're excited to announce Posit Academy's newest course: Intro to Shiny for R! Intro to Shiny for R will cover the following topics: ⭐️ Building your first app: Learn to create a simple interactive application from scratch with Shiny for R's basic structure. 📊 Reactive programming: Reactivity is at the heart of Shiny. We'll cover reactive expressions, observers, events, isolation, and more. You'll learn how to create responsive, dynamic applications that update automatically as users interact with them. Understanding reactivity will allow you to build more complex and efficient apps. ✨ UI components: A great Shiny app is functional, visually appealing, and user-friendly. Explore the various UI components available in Shiny and how to customize them to build an engaging user interface. 💡 Workflow: Efficient workflow management is crucial for maintaining and scaling your Shiny for R applications. ✅ Deploying apps: We'll cover how to deploy your Shiny for R applications so users can access them anywhere. Discover the full course summary and how to join the course by reading our most recent blog post featuring Joe Cheng! 🔗 https://lnkd.in/g_dWZGwg