Python

Quarto

Open-source scientific and technical publishing system built on Pandoc

pointblank

Data validation toolkit for assessing and monitoring data quality

Positron

Positron, a next-generation data science IDE

chatlas

Your friendly guide to building LLM chat apps in Python with less effort and more clarity

Great Tables

Make awesome display tables using Python

plotnine

A Grammar of Graphics for Python

shinychat

Chat UI component for Shiny

querychat

Chat with your data in R and Python

Shiny for Python

Easy interactive web applications with Python

orbital

Turn SciKitLearn pipelines into SQL

brand-yml

Unified branding with a single YAML file

pins-python

py-shiny-templates

Templates for Shiny for Python

shiny-assistant

Chat assistant for Shiny

py-shinyswatch

Bootswatch themes for py-shiny

rsconnect-python

The Posit Connect command-line interface

gt-extras

A Collection of Helper Functions for the great-tables Package

py-shinylive

Python package for deploying Shinylive applications

py-shinywidgets

Render ipywidgets inside a PyShiny app

vetiver-python

Version, share, deploy, and monitor models

Recreating Septa Transit Timetables in Python

Learn to build complex table layouts in Great Tables: vertical text, column spanners, and zebra striping

Michael Chow, Rich Iannone

PDF Accessibility and Standards

Quarto 1.9 brings PDF accessibility and standards support, building on new tagging features in LaTeX and Typst

Gordon Woodhull

Where Questions Become Queries: Meet querychat

querychat is a multilingual drop-in component for Shiny that allows you to chat with your data using natural language queries. No more clicking, no more limited filters, just you and your questions!

Shiny Talks from posit::conf(2025)

A curated playlist and overview of all Shiny-focused sessions from posit::conf(2025), along with workshop materials and links

posit::conf(2025) Quarto talks

Videos of talks from posit::conf(2025) are posted, and you can find them all here!

Andrew Holz

Tool Calling UI in shinychat

Rich tool calling displays are now available in shinychat!

Garrick Aden-Buie, Carson Sievert, Barret Schloerke

Python Open-Source Developer

Posit is hiring a Python open-source developer to create more data analysis tools

Max Kuhn

posit::conf(2025) Quarto workshop materials

At posit::conf(2025) we hosted two Quarto workshops: Branded Websites, Presentations, Dashboards, and PDFs with Quarto; and Extending Quarto. The materials from both workshops are freely available for anyone to learn from or use in their own teaching

Charlotte Wickham

Quarto Wizard 1.0.0: Democratising Quarto Extension Management

Introducing a game-changing extension for VS Code and Positron that transforms Quarto extensions management with an intuitive GUI for extensions and templates

Quarto 1.8

Quarto 1.8 improves brand support, introduces brand extensions, adds HTML accessibility checks, and gives access to execution context

Charlotte Wickham

Build Your First LLM App with Shiny for Python or R

In the third and final part of The Shiny Side of LLMs, we’ll bring everything together in a polished Shiny app. From covering async, optimizing conversations, to handling loading and errors smoothly. Both Python and R!

Shiny at posit::conf(2025)

Find Shiny talks and workshops at posit::conf(2025) in Atlanta

Shiny Team

Talking to LLMs: From Prompt to Response

In this second part of The Shiny Side of LLMs we get into the fun of actually talking to an LLM. From crafting prompts that get the responses you want, to turning messy outputs into something useful, giving models extra powers with tools, and figuring out what all the chatter really costs

mall 0.2.0

The mall 0.2.0 update for R and Python introduces support for external LLM providers like OpenAI and Gemini. This version also features parallel processing for R users, the ability to run NLP on string vectors in Python, and a brand new cheatsheet

Edgar Ruiz

What LLMs Actually Do (and What They Don’t)

Welcome to The Shiny Side of LLMs: a blog series explaining large language models in plain English, without the fancy and difficult buzzwords. In this first part: what LLMs are, how they work, what they’re good at, and why they don’t magically solve all your problems

From One Notebook to Many Reports: Parameterized reports with the jupyter engine

Learn how to transform a single Jupyter notebook into a parameterized report generator that automatically creates customized outputs for different scenarios

Charlotte Wickham

Great Tables v0.18.0: Easy Column Spanners and More!

New in Great Tables v0.18.0: automatic column spanners with tab_spanner_delim(), boolean formatting, and rotated labels

Rich Iannone

Posit at SciPy 2025

Catch up on the Shiny team’s talks and tutorials from SciPy 2025

Shiny Team

Adding Plots to Great Tables

Add sparklines and small charts to your Great Tables using svg.py, HTML, or plotnine

Jules Walzer-Goldfeld, Michael Chow

Great Tables + marimo = Interactive Tables

Make your Great Tables interactive with marimo’s reactive widgets

Rich Iannone, Jerry Wu

Data Validation Libraries for Polars (2025 Edition)

Choosing a data validation library for Polars? We compare Pandera, Patito, Pointblank, Validoopsie, and Dataframely

Rich Iannone

C’mon C’mon: Let’s Do a Pointblank Workshop!

Want a free Pointblank workshop for your data team? Here’s how to set one up

Rich Iannone

Overhauling Pointblank’s User Guide

Pointblank’s revamped user guide: spiral learning, clearer examples, and full API coverage

Rich Iannone, Michael Chow

How to use GitHub Codespaces to simplify your Quarto workshops

In this post, I’ll teach you the basics of GitHub Codespaces and how to use them to make it easier to teach using Quarto

Level Up Your Data Validation with Actions and FinalActions

Automate responses to bad data with Pointblank’s Actions and FinalActions

Rich Iannone

Quarto 1.7

Quarto 1.7 brings big improvements to dark mode along with updates to Typst, Pandoc, a new version shortcode, and improvements to the julia engine

Charlotte Wickham

Great Tables: Becoming the Polars .style Property

How Great Tables became Polars’ DataFrame.style—a look at open source collaboration

Michael Chow

Shiny 1.4 brings bookmarking and Generative AI docs

Shiny v1.4 is now available on PyPI! This release includes bookmarking, new Generative AI documentation, and more

Shiny Team

Introducing Pointblank

Get started with Pointblank for data validation using Polars, Pandas, or DuckDB

Rich Iannone

How We Used Great Tables to Supercharge Reporting in Pointblank

See how Great Tables powers Pointblank’s beautiful, shareable validation reports

Rich Iannone

Creating Responsive Layouts in Shiny with layout_columns()

Learn how to use Shiny’s layout_columns() to build adaptive web apps that look great on any screen size

Shiny Team

Level Up Your Shiny Forms: Accordions + Dynamic Goodness

Mastering Shiny Forms: Dynamic Updates with Accordion Panels

Shiny Team

Style Table Body with mask= in loc.body()

Style table cells conditionally using Polars expressions with loc.body(mask=)

Tip - use Positron to choose colors for your project brand

Use Positron’s integrated color picker for an easy way to choose colors for your next project’s _brand.yml

Carlos Scheidegger

Great Tables v0.15.0: Flags, Icons, and Other Formatting Goodies

New in Great Tables v0.15.0: country flag icons with fmt_flag(), Font Awesome icons, and accounting notation

Rich Iannone

Contributing to Public Transit Data Analysis and Tooling

Working on transit data? Let’s collaborate on open source tools and standards

Michael Chow

Rendering images anywhere in Great Tables

Add images anywhere in your Great Tables with fmt_image() and vals.fmt_image()

Use meta + include to customize reusable content

The “Includes” feature in Quarto lets you efficiently reuse content across multiple files. Combined with the “meta” shortcode, it enables you to set precise, file-specific values

Quarto website video series

Build a personal website with Quarto by following this four-part video series on YouTube

Charlotte Wickham, Mine Çetinkaya-Rundel

Quarto 1.6

Quarto 1.6 supports unified branding across formats, updates to RevealJS, a new shortcode to reorder content, a landscape page block, and more. There are also a couple of breaking changes that will affect a small number of users

Charlotte Wickham

Branded theming for Shiny for Python apps

Unified theming via brand.yml is now available in Shiny for Python

Garrick Aden-Buie

Quarto dashboards video series

Learn how to build a Quarto dashboard with a three-part video series

Charlotte Wickham, Mine Çetinkaya-Rundel

Great Tables: Generating LaTeX Output for PDF

Create publication-ready PDF tables by exporting Great Tables to LaTeX

Rich Iannone

posit::conf(2024) Shiny talks

There were many great talks given at posit::conf(2024) about Shiny and they are now available on YouTube

Andrew Holz

Version 0.14.0

Plotnine v0.14.0: requires Python 3.10+, removes print() for rendering, and improves IDE support for scales

posit::conf(2024) Quarto talks

Videos of talks from posit::conf(2024) are posted, we’ve compiled a playlist of Quarto talks for you!

Shiny for Python 1.2.0

Shiny’s @render.data_frame has a new integration with narwhals, gaining support for multiple data frame types!

Shiny Team

Introducing mall for R…and Python

We are proud to introduce the {mall} package. With {mall}, you can use a local LLM to run NLP operations across a data frame. (sentiment, summarization, translation, etc). {mall} has been simultaneously released to CRAN and PyPi (as an extension to Polars)

Edgar Ruiz

Testing Shiny Apps in Python

The shiny add test command simplifies the process of creating test files for Shiny apps, allowing developers to easily generate and run robust tests using built-in UI testing controllers for various components

Shiny Team

posit::conf(2024) Quarto workshop materials

Back in August, we hosted three Quarto workshops at posit::conf(2024); the materials from those workshops are available to learn and teach from!

Great Tables v0.13.0: Applying styles to all table locations

Great Tables v0.13.0 brings styling to all table locations via expanded loc.*() methods

Rich Iannone, Michael Chow

Shiny Assistant

Prototype and build Shiny applications with the help of AI

Winston Chang

Great Tables v0.12.0: Google Fonts and zebra stripes

New in Great Tables v0.12.0: Google Fonts via google_font() and zebra striping with opt_row_striping()

Rich Iannone

Announcing Shiny for Python 1.0

Shiny for Python’s level of quality, runtime stability, API and feature set make it ready for a big announcement

Shiny Team

2024 Plotnine Contest - Last Call

Final call for the 2024 Plotnine Contest—submit your best visualizations by July 26

shinyswatch 0.7.0

Customizable shinyswatch themes and an improved theme picker round out shinyswatch v0.7.0

Garrick Aden-Buie

Quarto 1.5

Quarto 1.5 improves Typst support, has some website enhancements like draft handling and announcement bars, adds a native Julia engine, and adds a couple of shortcodes for generating placeholder content

Charlotte Wickham

Great Tables for Scientific Publishing

Format scientific tables in Great Tables: unit notation, chemical formulas, and scientific notation

Rich Iannone

Seeing Beyond Statistics: Anscombe’s Quartet and the Power of Graphs

Why visualizing data matters: recreating Anscombe’s Quartet with Plotnine and Polars

Jeroen Janssens

Beautiful Tables in Typst

You can use HTML Tables with CSS styling in Typst via Quarto

Gordon Woodhull

Quarto workshops at posit::conf(2024)

On August 12, we’re hosting a day of workshops featuring three dedicated to Quarto at posit::conf(2024) in Seattle

Reintroducing the Shiny Extension for VS Code

The v1.0.0 release of the Shiny extension for VS Code now supports running both Shiny for Python and Shiny for R apps, as well as new ShinyLive features

Garrick Aden-Buie

PyCon 2024: Making Beautiful, Publication Quality Tables is Possible in 2024

Watch our PyCon 2024 talk on building publication-quality tables with Great Tables

Michael Chow

Editable data tables in Shiny for Python 0.9.0

Editable data frames, empowered renderers, browser error console, and more in Shiny for Python 0.9.0

Shiny Team

Great Tables is now BYODF (Bring Your Own DataFrame)

Great Tables v0.5.0 makes Pandas optional—use Polars without pulling in extra dependencies

Michael Chow

Introducing Shiny for Python Templates

Get started quickly with Shiny for Python’s new app templates

Shiny Team

The Design Philosophy of Great Tables

Why tables matter: 5,000 years of table design and how Great Tables solves the modern dilemma

Rich Iannone, Michael Chow

Quarto for Reproducible Medical Manuscripts

R/Medicine webinar on Quarto manuscripts

Mine Çetinkaya-Rundel

Quarto on Hugging Face

You can now host Quarto sites on Hugging Face using the new Quarto Space template

Great Tables v0.4.0: Nanoplots and More

New in Great Tables v0.4.0: nanoplots for tiny, interactive visualizations inside table cells

Rich Iannone

Introducing Component and Layout Galleries for Shiny for Python

Qucikly see and choose Shiny for Python’s Components and Layouts in these new galleries

Great Tables v0.3.0: So Many Style Options!

New in Great Tables v0.3.0: control column widths, style entire tables, and use system fonts

Rich Iannone

Using Polars to Win at Super Bowl Squares

Use Polars and Great Tables to analyze which Super Bowl Squares give you the best odds

Michael Chow

Introducing: Shiny Express

A brand new way to write Shiny apps in Python

Shiny Team

Quarto 1.4

Quarto 1.4 brings new formats for dashboards and Typst, a new manuscript project type, a cross-reference overhaul, Shiny for Python support, and a ton of other updates

Charlotte Wickham

Great Tables v0.2.0: Easy Data Coloring

New in Great Tables v0.2.0: data_color() for automatic cell coloring based on values

Rich Iannone

Great Tables: The Polars DataFrame Styler of Your Dreams

Style Polars DataFrames for presentation using Great Tables and Polars expressions

Michael Chow

Shiny for Python 0.6.1

Templates, an improved debugger, and a sneak peek at Shiny Express

Shiny Team

Quarto Dashboards Demonstration

Video demo of Quarto v1.4’s new dashboard feature with Charles Teague

Andrew Holz

ASA Traveling Courses on Quarto

Series of workshops for learning Quarto with R and RStudio, aimed primarily at R Markdown users

Mine Çetinkaya-Rundel

Shiny for Python 0.6.0

Fewer decorators, new page functions and, many new components

Shiny Team

Shiny for Python 0.5.0

Style tweaks, table filtering, tooltips–and an appearance on the Talk Python podcast!

Joe Cheng

Shiny for Python 0.4.0

Better tables and sidebars!

Winston Chang

Quarto for Academics

A video highlighting some of Quarto’s features that are especially useful for academics, as educators and as researchers

Mine Çetinkaya-Rundel

Get Started with Quarto

A new video for getting started with Quarto using R and RStudio

Mine Çetinkaya-Rundel

AI chat apps with Shiny for Python

The easiest way to build an AI chat app

Winston Chang

Shiny on Hugging Face

Deploy Shiny on Hugging Face with the click of a button

Quarto 1.3

Quarto 1.3 brings new features, improvements, and fixes

Charlotte Wickham

Shiny for Python out of alpha

Shiny for Python has moved from alpha to general availability

Winston Chang

Confluence Publishing

Quarto 1.3 adds support for publishing individual documents, and projects containing many documents to Atlassian Confluence

Charlotte Wickham

Jupyter Notebook Cell Embedding

Quarto 1.3 adds support for embedding cells from a Jupyter Notebook into a Quarto document via an embed shortcode. In HTML documents, links are automatically added that point to a rendered version of the external notebook

Charlotte Wickham

Multi-format Publishing

In Quarto 1.3, additional formats listed in HTML documents will automatically be linked in an “Other Formats” section near the top of the page

Charlotte Wickham

Code Annotation

In Quarto 1.3, you can add line based annotations to code chunks to highlight or explain parts of your code

Charlotte Wickham

The Past and Future of Shiny

To celebrate Shiny’s 10th anniversary, let’s talk about how we started and where we’re going

Joe Cheng

Shinylive Extension

With Shinylive, you can embed Shiny for Python applications into Quarto documents and run the entire application (including the Python runtime) inside the user’s web browser

Winston Chang

Quarto Extensions

Quarto Extensions are a powerful way to modify or extend the behavior of Quarto, and can be created and distributed by anyone. Extension types include filters, shortcodes, and custom formats

Using Callouts

Callouts are an excellent way to draw extra attention to certain concepts, or to more clearly indicate that certain content is supplemental or applicable to only some scenarios

Integrating Dynamic R and Python Models in Tableau Using plumbertableau

The plumbertableau and fastapitableau packages allow you to integrate dynamic R and Python models in Tableau, enhancing your organization’s preferred dashboard tool

How To Augment Tableau With R & Python - A Webinar and Case Study from Sweden

In an upcoming webinar on November 17th, Solita will showcase how they successfully combined the strengths of RStudio and Tableau at one of Sweden’s largest government agencies

How to Deliver Maximum Value Using R & Python

For data science teams to be successful, they need to embrace both R and Python. The ease of interoperability gives the user the flexibility to fill in any tool gaps for their own needs

Arrow and beyond: Collaborating on next generation tools for open source data science

RStudio partners with Ursa Labs to build a cross-language data science runtime powered by Apache Arrow

JJ Allaire

About Plotnine

plotnine: a grammar of graphics implementation for Python built on matplotlib and pandas

Feather: A Fast On-Disk Format for Data Frames for R and Python, powered by Apache Arrow

Introducing Feather: a fast binary file format for data frames that works in both R and Python, built on Apache Arrow

Hadley Wickham

BSides Charm 2026

BSidesCharm is a regional Security BSides held in the Baltimore region of Maryland

Data Science & AI Conference 2025

Presented by Lander Analytics, the Data Science & AI Conference brings together top data scientists, AI researchers, and industry leaders from the private and public sectors

posit::conf(2025)

Our annual event brought together data enthusiasts, professionals, developers, and innovators for an unforgettable three days of learning, connection, and inspiration

PyCascades 2026

PyCascades is a regional PyCon in the Pacific Northwest, celebrating the west coast Python developer and user community

PyCon Colombia 2025

PyCon Colombia is the national conference for users and developers of the Python programming language

PyCon US 2026

PyCon US is the largest and longest-running Python gathering globally

PyData Boston 2025

A three-day in-person gathering for the international community of data scientists, engineers, and developers working with data analysis tools

PyLadiesCon 2025

PyLadiesCon is the online conference of the PyLadies communities around the globe

R/Pharma 2025

R/Pharma is a scientifically & industry oriented online conference focused on the use of R in the development of pharmaceuticals

SciPy 2025

SciPy brings together attendees from industry, academia and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development

SDSS Symposium on Data Science and Statistics 2026

The Symposium on Data Science and Statistics provides a unique opportunity for data scientists, computer scientists, and statisticians to come together and exchange ideas

Use Python with R with reticulate

Quick reference guide for use python with r with reticulate

Shiny for Python

Quick reference guide for shiny for python

Natural Language Processing using LLMs in R & Python

Quick reference guide for natural language processing using llms in r & python

Great Tables

Quick reference guide for great tables

Deep Learning with Keras

Quick reference guide for deep learning with keras

Data visualization with Plotnine

Quick reference guide for data visualization with plotnine

Jeroen Janssens, Hassan Kibirige

AI chatbots with shinychat

Quick reference guide for ai chatbots with shinychat