Rstudio

epoxy: Super Glue for Data-driven Reports and Shiny Apps - posit::conf(2023)

Presented by Garrick Aden-Buie R Markdown, Quarto, and Shiny are powerful frameworks that allow authors to create data-driven reports and apps. But truly excellent reports require a lot of work in the final steps to get numerical and stylistic formatting just right. {epoxy} is a new package that uses {glue} to give authors templating superpowers. Epoxy works in R Markdown and Quarto, in markdown, LaTeX, and HTML outputs. It also provides easy templating for Shiny apps for dynamic data-driven reporting. Beyond epoxy’s features, this talk will also touch on tips and approaches for data-driven reporting that will be useful to a wide audience, from R Markdown experts to the Quarto and Shiny curious. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Elevating your reports. Session Code: TALK-1155

Garrick Aden-Buie

Quarto Shiny Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

Dynamic Interactions: webR to Empower Educators & Researchers with Interactive Quarto Docs

Presented by James Balamuta Full talk title: Dynamic Interactions: Empowering Educators and Researchers with Interactive Quarto Documents Using webR Traditional Quarto documents often lack interactivity, limiting the ability of students and researchers to fully explore and engage with the presented topic. In this talk, we propose a novel approach that utilizes webR, a WebAssembly-powered version of R, to seamlessly embed R code directly within the browser without the need for a server. We demonstrate how this approach can transform static Quarto documents into dynamic examples by leveraging webR’s capabilities through standard Quarto code cells, enabling real-time execution of R code and dynamic display of results. Our approach empowers educators and researchers alike to harness the power of interactivity and reproducibility for enhanced learning and research experiences. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Quarto (1). Session Code: TALK-1073

Quarto Quarto Rmd Rmarkdown Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Posit Python ML

duckplyr: Tight Integration of duckdb with R and the tidyverse - posit::conf(2023)

Presented by Kirill Müller The duckplyr R package combines the convenience of dplyr with the performance of DuckDB. Better than dbplyr: Data frame in, data frame out, fully compatible with dplyr. duckdb is the new high-performance analytical database system that works great with R, Python, and other host systems. dplyr is the grammar of data manipulation in the tidyverse, tightly integrated with R, but it works best for small or medium-sized data. The former has been designed with large or big data in mind, but currently, you need to formulate your queries in SQL. The new duckplyr package offers the best of both worlds. It transforms a dplyr pipe into a query object that duckdb can execute, using an optimized query plan. It is better than dbplyr because the interface is “data frames in, data frames out”, and no intermediate SQL code is generated. The talk first presents our results, a bit of the mechanics, and an outlook for this ambitious project. Materials: https://github.com/duckdblabs/duckplyr/ Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Databases for data science with duckdb and dbt. Session Code: TALK-1100

dbplyr dplyr duckplyr tidyverse Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

dplyr 1.1.0 Features You Can’t Live Without - posit::conf(2023)

Presented by Davis Vaughan Did you enjoy my clickbait title? Did it work? Either way, welcome! The dplyr 1.1.0 release included a number of new features, such as: Per-operation grouping with.by An overhaul to joins, including new inequality and rolling joins New consecutive_id() and case_match() helpers Significant performance improvements in arrange() Join me as we take a tour of this exciting dplyr update, and learn how to use these new features in your own work! Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Lightning talks. Session Code: TALK-1162

Davis Vaughan

dplyr Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Diversify Your Career with Shiny for Python - posit::conf(2023)

Presented by Gordon Shotwell A few years ago my company made a sudden shift from R to Python which was quite bad for my career because I didn’t really know Python. The main issue was that I couldn’t find a niche that allowed me to use my existing knowledge while learning the new language. Shiny for Python is a great niche for R users because none of the Python web frameworks can do what Shiny can do. Additionally, almost all of your knowledge of the R package is applicable to the Python one. This talk will provide an overview of the Python web application landscape and articulate what Shiny adds to this landscape, and then go through the five things that R users need to know before developing their first Shiny for Python application. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Data science with Python. Session Code: TALK-1138

Shiny for Python Shiny Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

Developing a Prototyping Competency in a Statistical Science Organization - posit::conf(2023)

Presented by Daniel Woodie The introduction of new tools, methods, and processes can be a struggle within a statistical science organization. Being deliberate and investing in the creation of a prototyping competency can help in accelerating progress. Prototyping allows organizations to quickly experiment with new ideas, reduce the risk of failure, identify potential issues early, and iterate until the desired outcome is achieved. I will highlight the key areas we have focused on accelerating, our framework for developing this competency, how we use Shiny, and the lessons we’ve learned along the way. Developing a prototyping competency is crucial for statistical science organizations that wish to stay competitive and innovative in today’s rapidly changing landscape. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Building effective data science teams. Session Code: TALK-1059

Shiny Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Democratizing Access to Education Data - posit::conf(2023)

Presented by Erika Tyagi Learn how the Urban Institute is making high-quality data more accessible through the Education Data Portal. Every year, government agencies release large amounts of data on schools and colleges, but this information is scattered across various websites and is often difficult to use. To make these data more accessible, the Urban Institute built the Education Data Portal, a freely available one-stop shop for harmonized data and metadata for nearly all major federal education datasets. In this talk, we’ll demonstrate how the portal works and share lessons we’ve learned about making data accessible to users with varying technical skills and preferred programming languages. The Urban Institute’s Education Data Portal: https://educationdata.urban.org Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: End-to-end data science with real-world impact. Session Code: TALK-1145

Automation Humans Python Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

dbtplyr: Bringing Column-Name Contracts from R to dbt - posit::conf(2023)

Presented by Emily Riederer starts_with(language): Translating select helpers to dbt. Translating syntax between languages transports concepts across communities. We see a case study of adapting a column-naming workflow from dplyr to dbt’s data engineering toolkit. dplyr’s select helpers exemplify how the tidyverse uses opinionated design to push users into the pit of success. The ability to efficiently operate on names incentivizes good naming patterns and creates efficiency in data wrangling and validation. However, in a polyglot world, users may find they must leave the pit when comparable syntactic sugar is not accessible in other languages like Python and SQL. In this talk, I will explain how dplyr’s select helpers inspired my approach to ‘column name contracts,’ how good naming systems can help supercharge data management with packages like {dplyr} and {pointblank}, and my experience building the {dbtplyr} to port this functionality to dbt for building complex SQL-based data pipelines. Materials: https://github.com/emilyriederer/dbtplyr https://emilyriederer.com Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Databases for data science with duckdb and dbt. Session Code: TALK-1098

dplyr pointblank tidyverse Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Data Visualization with Seaborn - posit::conf(2023)

Presented by Michael Waskom Seaborn is a Python library for statistical data visualization. After nearly a decade of development, seaborn recently introduced an entirely new API that is more explicitly based on a formal grammar of graphics. My talk will introduce this API and contrast it with the classic seaborn interface, sharing insights about the influence of the grammar of graphics on the ergonomics and maintainability of data visualization software. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Data science with Python. Session Code: TALK-1136

Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

Data Science in Production: The Way to a Centralized Infrastructure - posit::conf(2023)

Presented by Oliver Bracht In this talk, the success story of Covestro’s posit infrastructure is presented. The problem of the leading German material manufacturer was that no common development environment existed. With the help of eoda and Posit, a replicable, centralized development environment for R and Python was created. Although R and Python represent the core of the infrastructure, multiple languages and tools are unified. In addition to the collaboration of Covestro’s data science teams, compliance guidelines could also be better fulfilled. The staging architecture hereby provides developers with a concept for testing and going live with their products. This project presents a best practice approach to a data science infrastructure using Covestro as an example. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Data science infrastructure for your org. Session Code: TALK-1113

Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

CRAN-ial Expansion: Taking Your R Package Development to New Frontiers with R-Universe - posit::conf

Presented by Mo Athanasia Mowinckel Say goodbye to installation headaches and hello to a universe of possibilities with R-Universe! Take your R package development to new frontiers by organizing and sharing packages beyond the bounds of CRAN. R-Universe’s reliable package-building process strengthens installation and usage instructions, resulting in fewer support requests and an easy installation experience for users. With webpages and an API for exploring packages, R-Universe creates a streamlined and tidy ecosystem for R-package constellations. Also, you can build a custom toolchain for your users, relieving your workload and empowering users to help themselves. Join me to learn how to explore the vastness of R-Universe and expand your package development possibilities! Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Managing packages. Session Code: TALK-1080

Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

Connect on Kubernetes: Content-level Containerization - posit::conf(2023)

Presented by E. David Aja, not Kelly O’Briant Running Connect with off-host content execution in Kubernetes is very cool and allows you to enable some powerful and sophisticated workflows. The question is, do you really need it? How do you evaluate and decide? Let’s have a candid conversation about whether Connect content execution on Kubernetes is right for you and your organization. Moving to Kubernetes will introduce complexity, so it’s important to have a strong motivating reason for making the switch. This talk will introduce new Connect features that are made possible by content-level containerization. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Data science infrastructure for your org. Session Code: TALK-1116

Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

Conformal Inference with Tidymodels - posit::conf(2023)

Presented by Max Kuhn Conformal inference theory enables any model to produce probabilistic predictions, such as prediction intervals. We’ll demonstrate how these analytical methods can be used with tidymodels. Simulations will show that the results have good coverage (i.e., a 90% interval should include the real point 90% of the time). Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Tidy up your models. Session Code: TALK-1085

Max Kuhn

tidymodels AI Modelling Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

Commit to Change: How to Increase Accessibility in Your Favorite Open Source Projects - posit::conf

Presented by Rose Franzen Explore accessibility for data scientists by uncovering some common barriers in open source tools with simple fixes that anyone can implement. Dive into the often-overlooked world of accessibility for developers and data scientists! Uncover common accessibility barriers in open source tools, and learn simple steps to address them. Whether you’re a seasoned maintainer or a total novice, you’ll walk away with clear action items to implement right away. Join the movement of individuals championing the next frontier of disability inclusion in technology, shaping a more equitable future for all! Materials: https://github.com/franzenr/commit-to-change Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Package development. Session Code: TALK-1134

Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Combining R and Python for the Belgian Justice Department - posit::conf(2023)

Presented by Thomas Michem We build a great case on how to combine R and Python in a production environment. So the justice department’s back office monitors the smooth processing of all traffic fines in Belgium. They gather that data from all police departments and check if any anomalies occur. The back-office monitors that using a shiny application where they can see traffic signs showing the status of the whole operation and the status is built using Python scripts that perform anomaly detection if the number of fines is in line with what they expect daily. And the results of those checks are delivered to a front-end shiny application with Python flask API. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: R or Python? Why not both!. Session Code: TALK-1122

Shiny Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Coding Tools for Industry R&D – Development Lessons from an Analytical Lab - posit::conf(2023)

Presented by Camila Saez Cabezas Are you considering or curious about developing code-based tools for scientists? Whether you are an experienced developer or a fellow Posit Academy graduate who might be stepping into this role for the first time, the aim of my story is to inspire you and help you navigate this process. While developing custom R functions, packages, and Shiny apps for diverse analytical capabilities and users in R&D, I learned why it’s important to collect certain information at the start before writing any tidying, analysis, visualization, and web application code. In this talk, I will share the essential technical questions that help me define and plan for success. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Lightning talks. Session Code: TALK-1168

Shiny Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

CI/CD Pipelines - Oh, the Places You’ll Go! - posit::conf(2023)

Presented by Trevor Nederlof Data scientists are creating incredibly useful data products at an accelerating rate. These products are consumed by others who expect them to be accurate reliable and timely, often promises unfulfilled. In this talk, we will explore how to use common CI/CD pipeline tools already within reach of attendees to automatically test and deploy their apps, APIs, and reports. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Lightning talks. Session Code: TALK-1166

Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Can I Have a Word? - posit::conf(2023)

Presented by Ellis Hughes Since its release, {gt} has won over the hearts of many due to its flexible and powerful table-generating abilities. However, in cases where office products were required by downstream users, {gt}’s potential remained untapped. That all changed in 2022 when Rich Iannone and I collaborated to add Word documents as an official output type. Now, data scientists can engage stakeholders directly, wherever they are. Join me for an upcoming talk where I’ll share my excitement about the new opportunities this update presents for the R community as well as future developments we can look forward to. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Elevating your reports. Session Code: TALK-1156

Rich Iannone

gt Word Data Science Quarto Databricks Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Posit ML

Building a Flexible, Scaleable Self-Serve Reporting System with Shiny - posit::conf(2023)

Presented by Natalie O’Shea Working in the high-touch world of consulting, our team needed to develop a reporting system that was flexible enough to be tailored to the specific needs of any given partner while still reducing the highly manual nature of populating client-ready slide decks with various metrics and data visualizations. Utilizing the extensive resources developed by the R user community, I was able to create a flexible, scalable reporting system that allows users to populate templated Google slide decks with metrics and professional-grade visualizations using data pulled directly from our database at the time of query. This streamlined approach enables our consultants to spend less time copy-pasting data from one channel to another and instead focus on what they do best: surfacing business-relevant insights and recommendations for our partners. By sharing my approach to customizable self-serve reporting in Shiny, I hope attendees will walk away with new ideas about how to combine parameterized reporting and dashboard development to get the best of both worlds. Additionally, I hope to end by sharing how this project was pivotal in making the business case for procuring Posit products for my broader organization. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Bridging the gap between data scientists and decision makers. Session Code: TALK-1075

Shiny Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Black Hair and Data Science Have More in Common Than You Think - posit::conf(2023)

Presented by Kari Jordan Data science is often difficult to define because of its many intersections, including statistics, programming, analytics, and other domain knowledge. Would you believe it if I told you Black hair and data science have much in common? This talk is for those considering learning about, studying, or pursuing data science. In it, Dr. Kari L. Jordan draws parallels between approaches to caring for Black hair and approaches to learning data science. We start with the roots and end by picking the right tools and products to maintain our coiffure. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: It takes a village: building and sustaining communities. Session Code: TALK-1131

Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Becoming an R Package Author (or How I Got Rich Responding to GitHub Issues) - posit::conf(2023)

Presented by Matt Herman The transition from analyzing data in R to making packages in R can feel like a big step. Writing code to clean data or make visualizations seems categorically different from building robust “software” on which other people rely. In this talk, I’ll show why that distinction is not necessarily true by discussing my personal experience from learning R in graduate school to reporting bugs on GitHub to becoming a co-author of the tidycensus package and a practicing data scientist. The positive and supportive R community on GitHub, Twitter, and elsewhere contributes to why anyone who writes R code can become a package author. I have not actually gotten rich but I did get freelance data work based on my package contributions! Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Package development. Session Code: TALK-1133

Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

Automating the Dutch National Flu Surveillance for Pandemic Preparedness - posit::conf(2023)

Presented by Patrick van den Berg The next pandemic may be caused by a flu strain, and with thousands of patients with the flu in Dutch hospitals annually it is important to have accurate and current data. The National Institute for Public Health and the Environment of the Netherlands (RIVM) collects and processes flu data to achieve pandemic preparedness. However, the flu reporting process used to be very laborious, stealing precious time from epidemiologists. In our journey of automating this data pipeline we learned that collaboration was the most important factor in getting to a working system. This talk will be at the cross-section of data science and epidemiology and will provide you with a valuable opportunity to learn from our experiences. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Leave it to the robots: automating your work. Session Code: TALK-1150

Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

AI and Shiny for Python: Unlocking New Possibilities - posit::conf

Presented by Winston Chang In the past year, people have come to realize that AI can revolutionize the way we work. This talk focuses on using AI tools with Shiny for Python, demonstrating how AI can accelerate Shiny application development and enhance its capabilities. We’ll also explore Shiny’s unique ability to interface with AI models, offering possibilities beyond Python web frameworks like Streamlit and Dash. Learn how Shiny and AI together can empower you to do more, and do it faster. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: I can’t believe it’s not magic: new tools for data science. Session Code: TALK-1153

Winston Chang

Shiny for Python Shiny Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

Adding a Touch of glitr: Developing a Package of Themes on Top of ggplot - posit::conf(2023)

Presented by Aaron Chafetz and Karishma Srikanth Please note, a power issue cut off the first five minutes of the talk. Explore how our team at the US Agency for International Development (USAID) created our own data viz branding R package on top of ggplot2 and how you can too. How do you create brand cohesion across your large team when it comes to data viz? Inspired by the BBC’s bbplot, our team at the US Agency for International Development (USAID) developed a package on top of ggplot2 to create a common look and feel for our team’s products. This effort improved not just the cohesiveness of our work, but also trustworthiness. By creating this package, we reduced the reliance on using defaults and the time spent on each project customizing numerous graphic elements. More importantly, this package provided an easier on-ramp for new teammates to adopt R. We share our journey within a federal agency developing a style guide and aim to guide and inspire other organizations who could benefit from developing their own branding package and guidance. Materials: https://speakerdeck.com/achafetz/adding-a-touch-of-glitr https://usaid-oha-si.github.io/glitr/ https://issuu.com/achafetz/docs/oha_styleguide Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Compelling design for apps and reports. Session Code: TALK-1103

ggplot2 Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

A hacker’s guide to open source LLMs - posit::conf(2023)

Presented by Jeremy Howard In this deeply informative video, Jeremy Howard, co-founder of fast.ai and creator of the ULMFiT approach on which all modern language models (LMs) are based, takes you on a comprehensive journey through the fascinating landscape of LMs. Starting with the foundational concepts, Jeremy introduces the architecture and mechanics that make these AI systems tick. He then delves into critical evaluations of GPT-4, illuminates practical uses of language models in code writing and data analysis, and offers hands-on tips for working with the OpenAI API. The video also provides expert guidance on technical topics such as fine-tuning, decoding tokens, and running private instances of GPT models. As we move further into the intricacies, Jeremy unpacks advanced strategies for model testing and optimization, utilizing tools like GPTQ and Hugging Face Transformers. He also explores the potential of specialized datasets like Orca and Platypus for fine-tuning and discusses cutting-edge trends in Retrieval Augmented Generation and information retrieval. Whether you’re new to the field or an established professional, this presentation offers a wealth of insights to help you navigate the ever-evolving world of language models. (The above summary was, of course, created by an LLM!) For the notebook used in this talk, see https://github.com/fastai/lm-hackers. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Notebooks+LLMs may just be the future of coding. Session Code: KEY-1107

Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

20 questions and AI chat bots - posit::conf(2023)

Presented by Winston Chang Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: I can’t believe it’s not magic: new tools for data science. Session Code: TALK-1153

Winston Chang

Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

{slushy}: A Bridge to the Future - posit::conf(2023)

Presented by Becca Krouse Scaling the use of R can present complications for environment management, especially in regulated industries with a focus on traceability. One solution is controlled (aka “frozen”) environments, which are carefully curated and tested by tech teams. However, the speed of R development means the environments quickly become outdated and users are unable to benefit from the latest advances. Enter {slushy}: a team-friendly tool powered by {renv} and Posit Package Manager. Users can quickly mimic a controlled environment, with the easy ability to time travel between snapshot dates. Attendees will learn how {slushy} bolstered our R adoption efforts, and how this strategy enables tech teams and users to work in parallel towards a common future. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Managing packages. Session Code: TALK-1078

renv Rstudio Data Science Machine Learning Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit Python ML

How the R for Data Science (R4DS) Online Learning Community Made Me a Better Student - posit::conf

Presented by Lydia Gibson Through my participation in R4DS Online Learning Community, I have advanced my R and data science skills, making me a better student than I otherwise would have been through just my studies. As a non-traditional MS Statistics student with an undergraduate background in economics, I had absolutely no experience with the R programming language prior to pursuing my Master’s degree. In July 2021, with hopes of getting a headstart on learning R before beginning my degree program, I joined the R4DS Slack Workspace. Along with helping to improve my programming skills, R4DS has connected me with scholarships, mentorship, and other opportunities, and I think that it would be beneficial for other students to know about this great resource. Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.# Talk Track: Developing your skillset; building your career. Session Code: TALK-1110

Databricks Data Science Rstudio Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Quarto Posit ML

Quarto Dashboards | Charles Teague | Posit

Quarto has a host of exciting new features in release v1.4, with one of the most anticipated being Quarto Dashboards. In a recent internal presentation, Posit’s Charles Teague demonstrated the new capabilities and we wanted to share it with community. Please note that you can use this feature today, but to access it you need to be running on a Quarto prerelease build dated November 6, 2023, or later. We also encourage users to review our pre-release documentation which offers additional information and examples of the dashboard functionality. Quarto Pre-release builds: https://quarto.org/docs/download/prerelease.html Quarto Dashboard Documentation: https://quarto.org/docs/dashboards/

Quarto Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

webR 0.2: Updates to webR’s developer API | George Stagg | Posit

More from George Stagg on what’s new in the webR 0.2 release series, this time on webR’s developer API. If you’re a JavaScript or TypeScript developer, give webR a try and see what you might use it for! WebR makes it possible to run R code in the browser without the need for an R server to execute the code: the R interpreter runs directly on the user’s machine. It is possible to work entirely within webR and the R graphics devices, but you might also want to integrate webR into external JavaScript or TypeScript frameworks, including visualization packages. Learn about how to do this and more with webR’s developer API, including plotting data from webR using Observable JS, recent performance improvements, better error handling, worker event messages, and neatly terminating a webR session. 00:15 Performance improvements working with JavaScript 02:50 Example: Plotting data from webR using Observable JS 04:35 Type predicate functions and type conversion 07:30 Handling errors with webRError 09:15 Event messages from webr::canvas() 10:25 Safely handling webR termination 12:30 Links to documentation and resources Website and developer documentation: https://docs.r-wasm.org/ Examples of using webR with Observable JS: Loading webR and R data manipulation: https://observablehq.com/d/6936259b898a25ce Bitmap plotting and custom fonts: https://observablehq.com/d/32e2b7e465c0b994

George Stagg

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

webR 0.2: R Packages and Shiny for WebAssembly | George Stagg | Posit

WebR makes it possible to run R code in the browser without the need for an R server to execute the code: the R interpreter runs directly on the user’s machine. But just running R isn’t enough, you need the R packages you use every day too. webR 0.2.0 makes many new packages available (10,324 packages - about 51% of CRAN!) and it’s now possible to run Shiny apps under webR, entirely client side. George Stagg shares how to load packages with webR, know what ones are available, and get started running Shiny apps in the web browser. There’s a demo webR Shiny app too! 00:15 Loading R packages with webR 01:50 Wasm system libraries available for use with webR 05:30 Tidyverse, tidymodels, geospatial data, and database packages available 08:00 Shiny and httpuv: running Shiny apps under webR 11:05 Example Shiny app running in the web browser 12:05 Links with where to learn more Shiny webR demo app: https://shinylive.io/r/examples/ Website: https://docs.r-wasm.org/ webR REPL example: https://webr.r-wasm.org/latest/ Demo webR Shiny app in this video: https://shiny-standalone-webr-demo.netlify.app/ Source: https://github.com/georgestagg/shiny-standalone-webr-demo/ See the overview of what’s new in webR 0.2.0: https://youtu.be/Mpq9a6yMl_w

George Stagg

httpuv Shiny shinylive tidymodels tidyverse Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

webR 0.2 Overview: R in the browser | George Stagg | Posit

WebR is a version of the statistical language R compiled for the browser and Node.js using WebAssembly, via Emscripten. WebR makes it possible to run R code in the browser without the need for an R server to execute the code: the R interpreter runs directly on the user’s machine. Several R packages have also been ported for use with webR, and can be loaded in the usual way using the library() function. George Stagg shares what’s new in the 0.2.0 release! 00:23 About WebR and applications of computing with WebAssembly 02:25 Overview of changes in webR 0.2.0 release 04:10 The webR REPL app 07:28 Improved speed in graphics rendering 08:43 Text rendering in plots, including international and accessible fonts 10:27 Updated support for standard bitmap devices 13:05 Lazy virtual file system allows for decreased download size 15:40 Links with where to learn more Website: https://docs.r-wasm.org/ webR REPL example: https://webr.r-wasm.org/latest/

George Stagg

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

5 Reasons R & Python developers LOVE Posit Connect

Posit Connect makes deployment the easiest step in your workflow. Connect saves data scientists time, accelerates productivity, and maximizes the impact data science teams have within their organization. With Posit Connect, you can automate common recurring data science tasks, like: Sending a daily or weekly report to your boss Updating a machine learning model Extracting new data from an API Loading new data Updating reports that your stakeholders rely on

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Bite-sized tricks for machine learning with tidymodels | Posit

The tidymodels framework is a collection of R packages for modeling and machine learning using tidyverse principles. This video highlights a number of tidymodels features that could improve your modeling workflows. 0:03 Switching modeling engines is easy 0:21 Never lose your tuning results 0:36 Built-in visualizations for modeling objects 1:03 Grouped resampling 1:16 Case weights 1:32 Select variables based on role and type 2:00 Spatial resampling 2:16 Keep your tidymodels objects small Learn more at https://www.tidymodels.org/

tidymodels tidyverse Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

How does Shiny render things? | Gordon Shotwell

Discussion on the Shiny Python Discord channel from Gordon Shotwell. Gordon talks about how Shiny renders things with reactive programming, how other frameworks work, and how Shiny scales for complex applications. 0:00 - How Shiny renders things - reactivity 2:31 - How do other frameworks work 3:51 - Event driven programming, what’s a better way? 6:53 - Runtime tracing 8:25 - Declarative programming 9:20 - Drawing a graph 12:05 - How reactivity scales 13:30 - Reactive calculus 18:45 - Question and answer Shiny for Python: https://shiny.posit.co/py/ Shiny for Python Discord server: https://discord.com/invite/yMGCamUMnS

Shiny for Python Shiny Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

The River is our Relative | The Story of the Penobscot Nation

The Penobscot Nation has been around for millennia. On Indian Island, a river gives the Penobscot people life. “The tribe views the river like its own highway. We look at her as a relative, a sister, someone that gives life. Sea Lamprey, Sturgeon, Striper Bass.” Jan Paul works for the Penobscot Nation in the Department of Natural Resources and Water Quality. She’s using open-source technology, like R and the RStudio IDE, to keep the river healthy, so in turn, it can keep her people healthy. This is Jan’s inspiring story, featured for the first time at posit::conf(2023). Credits: Creative Director: Jason Restivo & Scout Studios Art Director & Illustrator: I-Nu Yeh Animator: Theera (Jay) Keeree Content Producer & Writer: Shannon McGarvey Sound Mixer: Caleb Theimer

rstudio Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

RStudio IDE | Background and Posit Workbench Jobs

This is a great feature for any long running scripts you may have, including, for example, a machine learning training step. It also allows you to run multiple jobs simultaneously. Now the main difference between background jobs and workbench jobs is that background jobs run as a child process within the same session. And workbench jobs run as a new session, either on the local server, or off host if you’re running in a multi server or clustered environment

rstudio Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Teaching the tidyverse in 2023 | Mine Çetinkaya-Rundel

Recommendations for teaching the tidyverse in 2023, summarizing package updates most relevant for teaching data science with the tidyverse, particularly to new learners. 00:00 Introduction 00:46 Using addins to switch between RStudio themes (See https://github.com/mine-cetinkaya-rundel/addmins for more info) 01:40 Native pipe 03:08 Nine core packages in tidyverse 2.0.0 07:15 Conflict resolution in the tidyverse 11:30 Improved and expanded *_join() functionality 22:05 Per operation grouping 27:41 Quality of life improvements to case_when() and if_else() 31:41 New syntax for separating columns 34:51 New argument for line geoms: linewidth 36:08 Wrap up See more in the Teaching the tidyverse in 2023 blog post https://www.tidyverse.org/blog/2023/08/teach-tidyverse-23

Mine Çetinkaya-Rundel

rstudio tidyverse tidyverse.org Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

What does superseded mean? Package development lifecycle process and the meaning of superseded.

An important part of the process of package lifecycle and package development is not just adding new functions. It’s is equally important to remove functions. Hadley Wickham shares about the package lifecycle process and what ‘supersede’ means for functions. See the full video about the purrr 1.0 release: https://youtu.be/EGAs7zuRutY More about the package lifecycle stages: https://lifecycle.r-lib.org/articles/stages.html Maintaining the house that tidyverse built: https://youtu.be/izFssYRsLZs

Hadley Wickham

purrr tidyverse Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

What does deprecated mean? Package lifecycle and the process of deprecation.

An important part of the process of package lifecycle and package development is not just adding new functions. It’s equally important to remove functions. Hadley Wickham shares about the package lifecycle process and what ‘deprecation’ means for functions. See the full video about the purrr 1.0 release: https://youtu.be/EGAs7zuRutY More about the package lifecycle stages: https://lifecycle.r-lib.org/articles/stages.html Maintaining the house that tidyverse built: https://youtu.be/izFssYRsLZs

Hadley Wickham

purrr tidyverse Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Posit Cloud Essentials | Ep 1: Getting Started

On the last Tuesday of every month, we host an event – Posit Cloud Essentials – where we explore the ins and outs of Posit Cloud, diving into its key features, valuable tips, and real-world use cases. The event is open to all and hosted on YouTube with a live Q&A during each month’s event. This month, Alex Chisholm, Product Manager for Posit Cloud, walks through how to get started with a free Posit Cloud account. Enabling you to conduct analysis, generate insights, and share findings from your web browser. What is Posit Cloud? Posit Cloud makes it easy to move your entire workflow into a unified online experience, complete with project management and publishing capabilities. Use your favorite coding languages and environments and share your work seamlessly with others, all from the comfort of your own web browser. No registration is required to join the events. Simply add the event to your calendar using the link below. Create a free Posit Cloud account → https://posit.cloud/ Explore the source code used in this demo → https://posit.cloud/spaces/394911/join?access_code=v-iZm0epL-n-vNHpht4JAfH47gmqWdg0cM6hyll7 Add future Posit Cloud Essential events to your calendar → http://evt.to/adahaeuow Q&A from this demo can be found here → https://app.sli.do/event/q2aLBPfVRAvUCFryNs9YuL

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

What Exactly Is Digital Transformation? | Posit + PING

Doug Linsmeyer, VP of Digital Technology at PING, clarifies how he thinks about digital transformation, adopting new technologies, and how Posit Connect helps data scientists at PING continue to innovate. Read and watch the full story here: https://posit.co/about/customer-stories/ping/ Learn more about Posit Connect: https://posit.co/products/enterprise/connect/

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Why RStudio is now Posit (J.J. Allaire | Posit CEO) - KNN Ep. 158

Today, I had the pleasure of interviewing J.J. Allaire. J.J. is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown publishing ecosystem including rmarkdown, flexdashboard, learnr, and distill, and also worked extensively on the R interfaces to Python, Spark, and TensorFlow. J.J. is now leading the Quarto project, which is a new Jupyter-based scientific and technical publishing system. In this episode, we learn about why RStudio has now repositioned itself as Posit, how it maximizes its open-source nature as a B Corp, and how J.J. as an open-source advocate views the private nature of many LLMs. I really enjoyed this conversation, and I hope you will as well! Posit - https://posit.co/ Podcast Sponsors, Affiliates, and Partners: Pathrise - http://pathrise.com/KenJee | Career mentorship for job applicants (Free till you land a job) Taro - http://jointaro.com/r/kenj308 (20% discount) | Career mentorship if you already have a job 365 Data Science (57% discount) - https://365datascience.pxf.io/P0jbBY | Learn data science today Interview Query (10% discount) - https://www.interviewquery.com/?ref=kenjee | Interview prep questions Listen to Ken’s Nearest Neighbors on all the main podcast platforms! On Apple Podcasts: https://podcasts.apple.com/us/podcast/kens-nearest-neighbors/id1538368692 (Please rate if you enjoy it!) On Spotify: https://open.spotify.com/show/7fJsuxiZl4TS1hqPUmDFbl On Google: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5idXp6c3Byb3V0LmNvbS8xNDMwMDQxLnJzcw?sa=X&ved=0CAMQ4aUDahcKEwjQ2bGBhfbsAhUAAAAAHQAAAAAQAQ MORE DATA SCIENCE CONTENT HERE: My Twitter - https://twitter.com/KenJee_DS LinkedIn - https://www.linkedin.com/in/kenjee/ Kaggle - https://www.kaggle.com/kenjee Medium Articles - https://medium.com/@kenneth.b.jee Github - https://github.com/PlayingNumbers My Sports Blog - https://www.playingnumbers.com ️ 66DaysOfData Discord Server - https://discord.com/invite/4p37sy5muZ

flexdashboard learnr Quarto rmarkdown rstudio tensorflow Ken Jee Ken Jee Podcast Kjp Podcast Data Science Data Science Podcast Knn Ken's Nearest Neighbors Knn Podcast Ken's Nearest Neighbors Podcast Jj Allaire Jj Allaire Interview Rstudio Posit Coding Languages Programming Language Wars Founder R Markdown Quarto Jupyter Open Source Llms Open Ai Sports Data Bill James Open Source Software

Python support in Posit Connect

Posit Connect: Deploy everything you create in R & Python, including interactive applications (Shiny, Streamlit, Dash), documents, notebooks, and dashboards. Learn more at https://posit.co/products/enterprise/connect/

Shiny Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Live Q&A Session - Ep 3. Scheduling a Quarto Doc (with custom branding) on Posit Connect

Live Q&A Session for the End-to-End Workflow Demo on June 28th *Please note this was the live Q&A portion of the event. You can view the demo recording here: https://youtu.be/V82BBU9ldcM Ep 3. Scheduling a Quarto Doc (with custom branding) on Posit Connect | End-to-end workflows Follow-up links: Demo recording: https://youtu.be/V82BBU9ldcM Posit Team: https://posit.co/products/enterprise/team/ Talk to us directly: https://posit.co/schedule-a-call/?booking_calendar__c=RST_YT_Demo Follow-along blog post: To be added Source code for example: To be added Posit Team demo resources: pos.it/demo-resources

Quarto Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Open Source in Drug Development | Thomas Nietmann and Posit

Thomas Neitmann, Associate Director at Denali Therapeutics, sat down with Posit to talk about open source in clinical trials, his work at Roche, the creation of admiral, career beginnings, and his future predictions for data science in the pharma space. Posit’s work in Pharma: https://posit.co/solutions/pharma/

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Roche Roche Clinical Trials Thomas Neitmann

RStudio + Amazon SageMaker | Build Beyond Your Laptop

Did you know that you can use RStudio, the best IDE for R and Python users, with Amazon Sagemaker? RStudio on Amazon SageMaker makes it easy for R users to quickly and easily get started coding in RStudio on AWS from their browser, no server setup required, by using a new integration with Posit Workbench. In this webinar, Posit team members will show you how to get started with RStudio on Amazon SageMaker to analyze your organization’s data in S3 and train ML models. As a fully managed offering on Amazon SageMaker, this release makes it easy for DevOps teams and IT Admins to administer, secure, and scale their organization’s centralized data science infrastructure with familiar AWS tools and frameworks. Learn more at: https://posit.co/products/cloud/sagemaker/ Talk to us about using RStudio and SageMaker: https://posit.co/schedule-a-call/?booking_calendar__c=Sagemaker

rstudio Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Posit Presents: A Game of Numbers with PING

The innovators at PING use Posit solutions such as Posit Connect to impact how golf data is analyzed and shared with golfers worldwide. High-level data, once only available to professional players, is now in the hands of everyday golfers thanks to public-facing apps like Ballnamic, which allows golfers to choose the golf ball that best suits their game. Through the use of Shiny apps, Posit Workbench APIs, and Posit Connect, the team at PING can now innovate faster, accelerate product development, and advance the democratization of golf data. Learn more at https://posit.co/about/customer-stories/ping/

Shiny Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss PING PING Golf

Python made easier with Posit

Tom Mock, Workbench Product Manager at Posit, discusses our commitment to Python from open-source projects to enterprise support. Specifically, Tom discusses Posit Team, the all-in-one solution for your data science team to build, share and maintain your R & Python data products. Posit Team comprises our three professional products, Posit Workbench, Connect, and Package Manager. Posit Workbench give your data scientists access to their favorite development tools in a centralized environment. Enabling them to work in the language they prefer, all while sharing IT resources and collaborating to find actionable insights. Posit Connect is where your team can securely host all of their data products and share them with the push of a button. Schedule reports to update automatically and give users access to only the insights they need. Posit Package Manager allows your team to deliver reproducible data science without the burden of manual package management. Organize and centralize R and Python packages across your team, department, or organization. Posit Team: https://posit.co/products/enterprise/team/ Posit Workbench: https://posit.co/products/enterprise/workbench/ Posit Connect: https://posit.co/products/enterprise/connect/ Posit Package Manager: https://posit.co/products/enterprise/package-manager/

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Quarto for Academics | Mine Çetinkaya-Rundel

This video highlights some of Quarto’s features that are especially useful for academics, as educators and as researchers. 00:00 Introduction 01:06 Linking to documentation from code with code-link 02:27 Informative YAML errors and YAML completion 03:41 Creating Quarto slides with revealjs 04:20 PDF export of HTML slides 05:03 Annotating slides with chalkboard 06:40 Advancing slides for your audience with multiplex 07:38 Revealing code in slides with echo 08:16 Highlighting code with code-line-numbers 09:37 Customizing output location with output-location 10:42 Showing code chunk fences with echo: fenced 12:03 Code annotation 14:11 Authoring manuscripts with Quarto templates 16:49 Inserting citations from Zotero or from a DOI with the RStudio Visual Editor 19:59 Wrap up and learning resources

Mine Çetinkaya-Rundel

Quarto revealjs rstudio Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Posit Connect | Provide Authenticated Access to Your Data Products

Posit Connect is all about getting your data products into the hands of stakeholders and collaborators. Here, we demonstrate how to provide authenticated access to a Dash application. For more information about Posit Connect, go to: https://posit.co/products/enterprise/connect/

Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Get started with Quarto | Mine Çetinkaya-Rundel

This video walks you through creating documents, presentations, and websites and publishing with Quarto. The video features authoring Quarto documents with executable R code chunks using the RStudio Visual Editor ( https://quarto.org/docs/visual-editor/). 00:00 Introduction 00:34 Authoring a document with Quarto 01:13 Using the RStudio visual editor 04:13 Code chunks and chunk options 06:31 Inserting cross references to figures and tables ( https://quarto.org/docs/authoring/cross-references.html ) 08:56 Adding a citation from a DOI ( https://quarto.org/docs/visual-editor/technical.html#citations ) 10:10 Seamlessly switching between output formats 10:58 Creating Quarto presentations ( https://quarto.org/docs/presentations/ ) 14:36 Customizing the output location of code in presentations ( https://quarto.org/docs/presentations/revealjs/#output-location ) 16:09 Creating a website from scratch ( https://quarto.org/docs/websites/ ) 19:19 Creating multi-format documents ( https://quarto.org/docs/output-formats/html-multi-format.html ) 20:22 Publishing the website to QuartoPub ( https://quarto.org/docs/publishing/quarto-pub.html )

Mine Çetinkaya-Rundel

Quarto revealjs rstudio Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

Why Shiny for Python? - Posit PBC

Learn how Shiny for Python’s design philosophy sets it apart from Streamlit, Dash, and traditional web development frameworks. With Shiny for Python out of alpha as of April, many have wondered how it stacks up against other popular alternatives. In this video, Gordon Shotwell – developer advocate on the Shiny team at Posit – explores the design philosophy behind Shiny for Python and how it compares to other frameworks for developing data science web applications. If you are a data scientist working mostly in Python, we hope this motivates you to take a serious look at Shiny for Python. Learn more on Posit blog, https://posit.co/blog/why-shiny-for-python/ 00:00 What is Shiny for Python? 03:05 What is Reactivity? 04:19 How does Shiny compare to Streamlit? 05:14 What are the main differences between Streamlit and Shiny for Python? 07:05 Why should I prefer Shiny over Streamlit? 09:09 How does Shiny compare to Dash? 10:22 What is the difference between a stateless and a stateful application? 12:19 Why consider Shiny for Python over Dash? 13:37 Shiny for Python’s Design Philosophy

Shiny Team

Shiny for Python Shiny Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

posit::conf(2023) Workshop:Enhancing Communication & Collaboration with Quarto and Jupyter Notebooks

Register now: http://pos.it/conf Instructor: Hamel Husain Workshop Duration: 1-Day Workshop This workshop is for you if you: • have some experience with Python and Jupyter and want to learn how Quarto can support and enhance your workflows • want to learn about turning your notebooks to websites and publications • want to learn how to write python packages with Jupyter notebooks and Quarto with the help of nbdev The workshop will assume some prior experience with Python and Jupyter Notebooks. Sharing knowledge through writing is a critical aspect of scientific activity, including data science. It allows researchers to communicate their findings and insights to a wider audience, build upon existing work, and collaborate with others in their field. However, until recently, there have been limited options for publishing long-form writing and expository analyses authored in Jupyter Notebooks, a popular medium for data scientists. Enter Quarto - an innovative, open-source scientific and technical publishing system compatible with Jupyter Notebooks and other popular mediums. Quarto provides data scientists with a seamless way to publish their work in a high-quality format that is easily accessible and shareable. With Quarto, researchers can turn their Jupyter Notebooks into professional-looking publications in a variety of formats, including web pages, books, and slides. In this workshop, we will demonstrate how Quarto enables data scientists to turn their work products into professional, high-quality publications, websites, blog posts, and other shareable artifacts. As a bonus, we will also discuss how you can create and document Python packages using Jupyter notebooks and Quarto with the help of nbdev. The learning outcomes for the workshop include: • examine case studies where sharing scientific knowledge has greatly improved the efficacy of data science teams • author documents in plain text markdown or Jupyter notebooks with equations, citations, crossrefs, figure panels, callouts, and advanced layouts • learn how to author content in IPython/Jupyter and the Quarto VS Code extension • leverage Quarto for creating different types of publications, including personal blogs, knowledge management for teams, notes, books, websites, and presentation slides • extend Quarto with notebook filters and extensions • host websites and publications on platforms like GitHub Pages, QuartoPub, and Netlify • test notebooks and documentation with Quarto’s execution options • create and document Python packages with nbdev and Quarto

Quarto Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

posit::conf(2023) Workshop: What They Forgot to Teach You About R

Register now: http://pos.it/conf Instructors: Shannon Pileggi and David Aja Workshop Duration: 1-Day Workshop This course is for you if you answer yes to these questions: • Have you been using R for a while and feel there might be better ways to organize your R life, but don’t know what they are? • Do you want to put programming on pause and learn about actionable programming-adjacent workflows for streamlining analysis in R? • Are you willing to feel a bit of (git) pain to leverage the benefits of version control for collaboration and time travel? This 1-day What They Forgot (WTF) To Teach You About R workshop is for experienced R and RStudio users who want to (re)design their R lifestyle via project-oriented workflows and version control for data science (Git/GitHub). At the conclusion of the workshop, you will have strategies for organizing data science projects and workflows, employing robust file paths, constructing human and machine-readable file names, and facilitating collaboration with yourself or others via version control

rstudio Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

posit::conf(2023) Workshop: Web Design for Shiny Developers

Register now: http://pos.it/conf Instructors: Maya Gans and David Granjon This course is for you if: • you are an R developer with basic Shiny knowledge • you want to quickly test new business ideas • you want to increase the reach of your apps and websites Website design and development is one of the most critical factors contributing to whether the user has a good or poor experience while browsing your site, directly influencing the overall impression of your brand. Besides, bad design decisions can significantly impact app performances. By exposing you to common governing rules of design, this course will walk you through the entire design process, from ideation to execution. These rules will help you to become a better collaborator to design teams, and enable you to create beautiful front-end experiences for Shiny

Shiny Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

posit::conf(2023) Workshop: Tidy time series and forecasting in R

Register now: http://pos.it/conf Instructor: Rob J Hyndman Workshop Duration: 2-Day Workshop This course is for you if you: • already use the tidyverse packages in R such as dplyr, tidyr, tibble and ggplot2 • need to analyze large collections of related time series • would like to learn how to use some tidy tools for time series analysis including visualization, decomposition and forecasting It is common for organizations to collect huge amounts of data over time, and existing time series analysis tools are not always suitable to handle the scale, frequency and structure of the data collected. In this workshop, we will look at some packages and methods that have been developed to handle the analysis of large collections of time series. On day 1, we will look at the tsibble data structure for flexibly managing collections of related time series. We will look at how to do data wrangling, data visualizations and exploratory data analysis. We will explore feature-based methods to explore time series data in high dimensions. A similar feature-based approach can be used to identify anomalous time series within a collection of time series, or to cluster or classify time series. Primary packages for day 1 will be tsibble, lubridate and feasts (along with the tidyverse of course). Day 2 will be about forecasting. We will look at some classical time series models and how they are automated in the fable package, and we will explore the creation of ensemble forecasts and hybrid forecasts. Best practices for evaluating forecast accuracy will also be covered. Finally, we will look at forecast reconciliation, allowing millions of time series to be forecast in a relatively short time while accounting for constraints on how the series are related

dplyr ggplot2 lubridate tibble tidyr tidyverse Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

posit::conf(2023) Workshop: Teaching Data Science Masterclass

Register now: http://pos.it/conf Instructor: Dr. Mine Çetinkaya-Rundel Workshop Duration: 1-Day Workshop This course is for you if you: • you want to learn / discuss curriculum, pedagogy, and computing infrastructure design for teaching data science with R and RStudio using the tidyverse and Quarto • you are interested in setting up your class in Posit Cloud • you want to integrate version control with git into your teaching and learn about tools and best practices for running your course on GitHub This masterclass is aimed primarily at participants teaching data science in an academic setting in semester-long courses, however much of the information and tooling we introduce is applicable for shorter teaching experiences like workshops and bootcamps as well. Basic knowledge of R is assumed and familiarity with the tidyverse and Git is preferred. There has been significant innovation in introductory statistics and data science courses to equip students with the statistical, computing, and communication skills needed for modern data analysis. Success in data science and statistics is dependent on the development of both analytical and computational skills, and the demand for educators who are proficient at teaching both these skills is growing. The goal of this masterclass is to equip educators with concrete information on content, workflows, and infrastructure for painlessly introducing modern computation with R and RStudio within a data science curriculum. In a nutshell, the day you’ll spend in this workshop will save you endless hours of solo work designing and setting up your course. Topics will cover teaching the tidyverse in 2023, highlighting updates to R for Data Science (2nd ed) and Data Science in a Box as well as present tooling options and workflows for reproducible authoring, computing infrastructure, version control, and collaboration. The workshop will be comprised of four modules: • Teaching data science with the tidyverse and Quarto • Teaching data science with Git and GitHub • Organizing, publishing, and sharing of course materials • Computing infrastructure for teaching data science Throughout each module we’ll shift between the student perspective and the instructor perspective. The activities and demos will be hands-on; attendees will also have the opportunity to exchange ideas and ask questions throughout the session. In addition to gaining technical knowledge, participants will engage in discussion around the decisions that go into developing a data science curriculum and choosing workflows and infrastructure that best support the curriculum and allow for scalability. We will also discuss best practices for configuring and deploying classroom infrastructures to support these tools

Mine Çetinkaya-Rundel

Quarto rstudio tidyverse Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

posit::conf(2023) Workshop: Steal like an Rtist: Creative Coding in R

Register now: http://pos.it/conf Instructors: Ijeamaka Anyene Fumagalli & Sharla Gelfand Workshop Duration: 1-Day Workshop This workshop is for you if you: • are comfortable with R and RStudio, experience with tidyverse and ggplot2 • are interested in applying data visualization skills more creatively, but may not know where to start or how to develop style/inspiration • are an artist interested in exploring code as another medium for creating their work R is a tool for data analysis but also can be used for self-expression. This workshop will be an introduction to creative coding in R in order to make visual art. We will take an inspiration-first approach, using compelling pieces to discuss and learn the techniques that shape the work. This workshop takes guidance from its namesake, the book “Steal Like An Artist” by Austin Kleon - once we have identified and learned to recreate existing works, we will cover how to take this inspiration and transform, remix, or reinterpret it in the pursuit of developing our own work and artistic styles. This workshop is hands-on and will cover color theory and manipulation, a reintroduction of the data frame as the foundation for creating art (instead of just for analyzing data!), using ggplot2 as an artistic canvas, creating basic and specialized shapes, tiling and pattern making, developing your own functions and using iteration. We will also discuss how to use controlled randomness to convert a standalone piece into a generative art system that can produce many distinct outputs. Creative coding may seem a world apart from data analysis, but we see a large overlap and intersection of the skills used in both, not to mention the creative muscles that are already used in data visualization

ggplot2 rstudio tidyverse Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

posit::conf(2023) Workshop: Shiny in Production: Tools and Techniques

Register now: http://pos.it/conf Instructors: Eric Nantz and Mike Thomas Workshop Duration: 1-Day Workshop This course is for you if you: • had a Shiny application work just fine on your machine, but encounters critical issues after deployment • are eager to prospectively apply techniques before deployment to plan for the unexpected • want to know the benefits and trade-offs between various ways of hosting Shiny applications Shiny brings tremendous possibilities to share innovative data science workflows with others inside an intuitive web interface. Many in the Shiny community have shared effective development techniques for building a robust application. Even with the best intentions during application development, a myriad of issues can arise once it leaves the confines of your machine. In this one-day workshop, you will implement core techniques to account for common scenarios that arise once your application is used in production, such as accounting for thousands of simultaneous users, how effective profiling can address performance bottlenecks, and ensuring your application is doing as little as possible to ensure a smooth and responsive experience. This course assumes intermediate knowledge of building Shiny applications in R and prior experience deploying an application to a platform such as the shinyapps.io service or products like Posit Connect

Shiny shinyapps Rstudio Data Science Machine Learning Python Stats Tidyverse Data Visualization Data Viz Ggplot Technology Coding Connect Server Pro Shiny Rmarkdown Package Manager CRAN Interoperability Serious Data Science Dplyr Forcats Ggplot2 Tibble Readr Stringr Tidyr Purrr GitHub Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education RStats Open Source Oss Reticulate

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Rstudio

epoxy: Super Glue for Data-driven Reports and Shiny Apps - posit::conf(2023)

Dynamic Interactions: webR to Empower Educators & Researchers with Interactive Quarto Docs

duckplyr: Tight Integration of duckdb with R and the tidyverse - posit::conf(2023)

dplyr 1.1.0 Features You Can’t Live Without - posit::conf(2023)

Diversify Your Career with Shiny for Python - posit::conf(2023)

Developing a Prototyping Competency in a Statistical Science Organization - posit::conf(2023)

Democratizing Access to Education Data - posit::conf(2023)

dbtplyr: Bringing Column-Name Contracts from R to dbt - posit::conf(2023)

Data Visualization with Seaborn - posit::conf(2023)

Data Science in Production: The Way to a Centralized Infrastructure - posit::conf(2023)

CRAN-ial Expansion: Taking Your R Package Development to New Frontiers with R-Universe - posit::conf

Connect on Kubernetes: Content-level Containerization - posit::conf(2023)

Conformal Inference with Tidymodels - posit::conf(2023)

Commit to Change: How to Increase Accessibility in Your Favorite Open Source Projects - posit::conf

Combining R and Python for the Belgian Justice Department - posit::conf(2023)

Coding Tools for Industry R&D – Development Lessons from an Analytical Lab - posit::conf(2023)

CI/CD Pipelines - Oh, the Places You’ll Go! - posit::conf(2023)

Can I Have a Word? - posit::conf(2023)

Building a Flexible, Scaleable Self-Serve Reporting System with Shiny - posit::conf(2023)

Black Hair and Data Science Have More in Common Than You Think - posit::conf(2023)

Becoming an R Package Author (or How I Got Rich Responding to GitHub Issues) - posit::conf(2023)

Automating the Dutch National Flu Surveillance for Pandemic Preparedness - posit::conf(2023)

AI and Shiny for Python: Unlocking New Possibilities - posit::conf

Adding a Touch of glitr: Developing a Package of Themes on Top of ggplot - posit::conf(2023)

A hacker’s guide to open source LLMs - posit::conf(2023)

20 questions and AI chat bots - posit::conf(2023)

{slushy}: A Bridge to the Future - posit::conf(2023)

How the R for Data Science (R4DS) Online Learning Community Made Me a Better Student - posit::conf

Quarto Dashboards | Charles Teague | Posit

webR 0.2: Updates to webR’s developer API | George Stagg | Posit

webR 0.2: R Packages and Shiny for WebAssembly | George Stagg | Posit

webR 0.2 Overview: R in the browser | George Stagg | Posit

5 Reasons R & Python developers LOVE Posit Connect

Bite-sized tricks for machine learning with tidymodels | Posit

How does Shiny render things? | Gordon Shotwell

The River is our Relative | The Story of the Penobscot Nation

RStudio IDE | Background and Posit Workbench Jobs

Teaching the tidyverse in 2023 | Mine Çetinkaya-Rundel

What does superseded mean? Package development lifecycle process and the meaning of superseded.

What does deprecated mean? Package lifecycle and the process of deprecation.

Posit Cloud Essentials | Ep 1: Getting Started

What Exactly Is Digital Transformation? | Posit + PING

Why RStudio is now Posit (J.J. Allaire | Posit CEO) - KNN Ep. 158

Python support in Posit Connect

Live Q&A Session - Ep 3. Scheduling a Quarto Doc (with custom branding) on Posit Connect

Open Source in Drug Development | Thomas Nietmann and Posit

RStudio + Amazon SageMaker | Build Beyond Your Laptop

Posit Presents: A Game of Numbers with PING

Python made easier with Posit

Quarto for Academics | Mine Çetinkaya-Rundel

Posit Connect | Provide Authenticated Access to Your Data Products

Get started with Quarto | Mine Çetinkaya-Rundel

Why Shiny for Python? - Posit PBC

posit::conf(2023) Workshop:Enhancing Communication & Collaboration with Quarto and Jupyter Notebooks

posit::conf(2023) Workshop: What They Forgot to Teach You About R

posit::conf(2023) Workshop: Web Design for Shiny Developers

posit::conf(2023) Workshop: Tidy time series and forecasting in R

posit::conf(2023) Workshop: Teaching Data Science Masterclass

posit::conf(2023) Workshop: Steal like an Rtist: Creative Coding in R

posit::conf(2023) Workshop: Shiny in Production: Tools and Techniques

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