Education

Daniel Chen - LLMs, Chatbots, and Dashboards_ Visualize Your Data with Natural Language - PyData

LLMs have a lot of hype around them these days. Let’s demystify how they work and see how we can put them in context for data science use. As data scientists, we want to make sure our results are inspectable, reliable, reproducible, and replicable. We already have many tools to help us in this front. However, LLMs provide a new challenge; we may not always be given the same results back from a query. This means trying to work out areas where LLMs excel in, and use those behaviors in our data science artifacts. This talk will introduce you to LLms, the Chatlas package, and how they can be integrated into a Shiny to create an AI-powered dashboard. We’ll see how we can leverage the tasks LLMs are good at to better our data science products

Rodrigo Silva Ferreira-When Rivers Speak Analyzing Massive Water Quality Datasets-PyData Boston 2025

Rivers have long been storytellers of human history. From the Nile to the Yangtze, they have shaped trade, migration, settlement, and the rise of civilizations. They reveal the traces of human ambition… and the costs of it. Today, from the Charles to the Golden Gate, US rivers continue to tell stories, especially through data.

Over the past decades, extensive water quality monitoring efforts have generated vast public datasets: millions of measurements of pH, dissolved oxygen, temperature, and conductivity collected across the country. These records are more than environmental snapshots; they are archives of political priorities, regulatory choices, and ecological disruptions. Ultimately, they are evidence of how societies interact with their environments, often unevenly.

In this talk, I’ll explore how Python and modern data workflows can help us “listen” to these stories at scale. Using the United States Geological Survey (USGS) Water Data APIs and Remote SSH in Positron, I’ll process terabytes of sensor data spanning several years and regions. I’ll demonstrate that, while Parquet and DuckDB enable scalable exploration of historical records, using Remote SSH is paramount in order to enable large-scale data analysis. By doing so, I hope to answer some analytical questions that can surface patterns linked to industrial growth, regulatory shifts, and climate change.

By treating rivers as both ecological systems and social mirrors, we can begin to see how environmental data encodes histories of inequality, resilience, and transformation.

Whether your interest lies in data engineering, environmental analytics, or the human dimensions of climate and infrastructure, this talk will explore topics at the intersection of environmental science, will offer both technical methods and sociological lenses to understand the stories rivers continue to tell

Jeroen Janssens - Package Your Python Code as a CLI | PyData London 25

www.pydata.org

Learn how to transform your Python code into a command-line tool. Jeroen Janssens, author of Data Science at the Command Line, guides you through the process of turning your scripts into reusable, executable tools, integrating them into your data workflows and harnessing the power of the Unix command line.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

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Jeroen Janssens

Wes McKinney - Retooling for a Smaller Data Era | PyData Global 2024

www.pydata.org

In this talk, I will offer my perspective on the modern data tools landscape and in particular user-facing tools for interactive data science and data exploration. The latest trends of composable data systems and embeddable query engines like DuckDB and DataFusion create both challenges and opportunities to create a more coherent and productive stack of tools for both end user data scientists and developers building data systems.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

KEYNOTE: Dr. Jeroen Janssens - Embrace the Unix Command Line and Supercharge Your PyData Workflow

www.pydata.org

Discover why the Unix command line remains a powerful and relevant tool for data scientists, even in a Python-dominated landscape. This talk will demonstrate how embracing the command line and leveraging its many tools can significantly enhance your productivity, streamline data workflows, and complement your Python skills.

Jeroen Janssens, PhD, is a polyglot data science consultant and certified instructor. His expertise lies in visualizing data, implementing machine learning models, and building solutions using Python, R, JavaScript, and Bash. Jeroen is passionate about open source and sharing knowledge. He is the author of Data Science at the Command Line (O’Reilly, 2021) and is currently writing Python Polars: The Definitive Guide (O’Reilly, 2025). Every now and then he blogs at https://jeroenjanssens.com .

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Jeroen Janssens

Janssens, Chow & Nieuwdorp - Turning DataFrames into Pretty Pictures with Plotnine | PyData NYC 2024

www.pydata.org

Learn how Plotnine, a Python package inspired by R’s ggplot2, enables the creation of sophisticated and effective data visualizations with minimal effort. This tutorial will explain how Plotnine’s grammar of graphics approach provides a flexible, intuitive way to visualize data, either as ad-hoc plots or fine-tuned graphs suited for communication.

Quick links Presentation: https://bit.ly/plotnine-tutorial GitHub repository: https://bit.ly/plotnine-repo Slideshow about what to expect: https://bit.ly/expect-plotnine

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Isabel Zimmerman - End-to-end data science with the Positron IDE | PyData NYC 2024

www.pydata.org

The process of data science is inherently iterative, requiring constant inspection and visualization of data. Positron is a new, next generation integrated development environment (IDE) built to facilitate exploratory data analysis, reproducible authoring, and publishing data artifacts. This talk will discuss the motivation behind creating Positron and demonstrate the features that support these iterative data science workflows.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Isabel Zimmerman

Jeroen Janssens - How I hacked UMAP and won at a plotting contest | PyData Amsterdam 2024

www.pydata.org

In this talk, I’ll share my journey of animating UMAP, a cutting-edge dimensionality reduction algorithm, by visualizing not just its final output but each intermediate step as well. I’ll explain why and how I modified UMAP’s source code, while also demonstrating the use of Polars for data wrangling, Plotnine for visualization, and ffmpeg for animation. The result ultimately earned me a runner-up position in the 2024 Plotnine plotting contest.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 01:06 Plotnine contest 02:18 Hoi! I’m Jeroen 03:13 Visualizing the behavior of an algorithm 07:58 Keeping track of intermediate predictions 09:23 Tool: UMAP 12:31 Tool: Polars 13:15 Python Polars: The Definitive Guide 13:40 MNIST dataset 14:46 Tool: Plotnine 17:04 Tool: FFmpeg 18:58 Final result 19:38 To conclude 20:40 Q & A

Jeroen Janssens

J.J. Allaire - Keynote: Dashboards with Jupyter and Quarto | PyData NYC 2023

www.pydata.org

https://drive.google.com/file/d/1O_ed6OKEXZBIzKn6yyF9W7f6NaNV-L3J/view?usp=drive_link

Keynote by JJ Allaire

J.J. is the Founder and CEO of Posit (which you might only know by its previous name, RStudio). J.J. is now leading the Quarto project, a Jupyter-based scientific and technical publishing system. In this talk, J.J. will introduce Quarto Dashboards, an easy way to create production quality dashboards from Jupyter Notebooks. J.J. will also more broadly discuss Posit’s recent work in the open source PyData ecosystem along with plans for significantly expanding that work in the future.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

JJ Allaire

Gordon Shotwell & Tracy Teal - Build Simple and Scalable Apps with Shiny | PyData NYC 2023

www.pydata.org

https://gshotwell.github.io/shiny-algorithm

This talk explores the intuitive algorithm behind Shiny for Python and shows how it allows you to scale your apps from prototype to product. Shiny infers a reactive computation graph from your application and uses this graph to efficiently re-render components. This eliminates the need for data caching, state management, or callback functions which lets you build scalable applications quickly.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Tracy Teal - It’s not just code: managing an open source project | PyData Seattle 2023

www.pydata.org

An open source project starts with ideas and code, but it continues with people. We know that most open source projects rely on just one or two people for most of the work. And code is just a small part of these roles, which also include project management, conflict resolution, decision making in uncertain situations, building an inclusive community, and lots and lots of communication. Whether you’re just starting a project, interested in getting involved in open source, or already have a community of thousands, there are some tips, tricks and templates that you can use to make maintaining an open source project more manageable.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Joe Cheng - Shiny: Data-centric web applications in Python | PyData Seattle 2023

www.pydata.org

Shiny is a web framework that is designed to let you create data dashboards, interactive visualizations, and workflow apps in pure Python or R. Shiny doesn’t require knowledge of HTML, CSS, and JavaScript, and lets you create data-centric applications in a fraction of the time and effort of traditional web stacks.

Of course, Python already has several popular and high-quality options for creating data-centric web applications. So it’s fair to ask what Shiny can offer the Python community.

In this talk, I will introduce Shiny for Python and answer that question. I’ll start with some basic demos that show how Shiny apps are constructed. Next, I’ll explain Transparent Reactive Programming (TRP), which is the animating concept behind Shiny, and the reason it occupies such an interesting place on the ease-vs-power tradeoff frontier. Finally, I’ll wrap up with additional demos that feature interesting functionality that is made trivial with TRP.

This talk should be interesting to anyone who uses Python to analyze or visualize data, and does not require experience with Shiny or any other web frameworks.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Joe Cheng

J.J. Allaire - Publishing Jupyter Notebooks with Quarto | PyData Seattle 2023

www.pydata.org

Quarto is a multi-language, open-source toolkit for creating data-driven websites, reports, presentations, and scientific articles. Quarto is built on Jupyter, and in this talk we’ll demonstrate using Quarto to publish Jupyter notebooks as production quality websites, books, blogs, presentations, PDFs, Office documents, and more. We’ll also cover how to publish notebooks within existing content management systems like Hugo, Docusaurus, and Confluence. Finally, we’ll explore how Quarto works under the hood along with how the system can be extended to accommodate unique requirements and workflows.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Isabel Zimmerman - Practical MLOps for better models | PyData Global 2022

www.pydata.org

Machine learning operations (MLOps) are often synonymous with large and complex applications, but many MLOps practices help practitioners build better models, regardless of the size. This talk shares best practices for operationalizing a model and practical examples using the open-source MLOps framework vetiver to version, share, deploy, and monitor models.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Isabel Zimmerman

Keynote: Hadley Wickham - Embracing multi-lingual data science | PyData Global 2022

www.pydata.org

RStudio recently changed its name to Posit to reflect the fact that we’re already a company that does more than just R. Come along to this talk to hear a few of the reasons that we love R, and to learn about some of the open source tools we’re working on for python.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Hadley Wickham

Isabel Zimmerman - Holistic MLOps for better science | PyData NYC 2022

www.pydata.org

Machine learning operations (MLOps) are often synonymous with large and complex applications, but many MLOps practices help practitioners build better models, regardless of the size. This talk shares best practices for operationalizing a model and practical examples using the open-source MLOps framework vetiver to version, share, deploy, and monitor models.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

Isabel Zimmerman

Eric Cronstrom | How we made the switch: a case study on automating a complex report | RStudio

The Center for Charter Schools at Central Michigan University produces annual reports for about 60 schools. The reporting process used to be a cumbersome blend of many technologies. The Center used to use a blend of SQL, Excel, inDesign, and VBScript that would all culminate in a nice looking, branded report for each school. 2 years ago, staff turnover allowed the data team to rethink the process, having had experience in R from graduate work the team at the Center decided to go all in on R Studio and R Markdown for report production a mere 1 month before the reports were due to be published.

This talk will be a case study of how we as an organization adopted RStudio tools to streamline a cumbersome process to fantastic results.

About Eric: Eric is responsible for administering a wide range of day to day program functions associated with the performance and accountability of CMU partner schools. He ensures that the data the Center utilizes to evaluate school performance is accurate and stored within a sound data infrastructure. He also leverages his wide range of technical skills to lead the development and production of reports and respond to questions regarding school performance and demographic context. Prior to joining the Center, Eric was a database administrator for Central Michigan University Libraries. He has also served as a lecturer at Central Michigan University teaching courses in web design, database design and programming. He earned a master’s degree in information systems management and a bachelor’s degree in computer science from Central Michigan University. He is also pursuing an additional master’s degree in applied statistics at Central Michigan University

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 Ggplot2 Tibble Readr Stringr Tidyr Purrr Github Data Wrangling Tidy Data Odbc Rayshader Plumber Blogdown Gt Lazy Evaluation Tidymodels Statistics Debugging Programming Education Forcats Rstats Open Source Oss Reticulate K12 Charter Schools Education

Mary Rudis | How R and Posit are revolutionizing Stats Education in Community Colleges | Posit

Talk from rstudio::conf(2019)

There is no doubt that Posit has had an impact on how introductory statistics is taught in colleges today. When we consider the sheer dominance that giants like Texas Instruments, IBM, and Pearson Publishing have had in academic curriculum development, it’s no small wonder that tools like R and Python have been able to gain a foothold. Projects like DataCamp, ModernDive.com, “Introductory Statistics with Randomization and Simulation” courtesy of openintro.org, Wickham’s “R for Data Science” and Peng’s “R Programming for Data Science” are great resources for the student who has already some fundamental math or statistical background and has become comfortable around computing and applications-driven computational exercises. But many of us know that Data Science cannot simply be relegated to the privileged few that stumble into it by virtue of circumstance. My passion, and the purpose of my talk, is to provide educators with a digestible guidebook that would be appropriate for introduction to statistical concepts in high school, college, and under-resourced schools looking for ways to increase diversity in STEM. Organized in small, adaptable activities designed to be the amuse-esprit enticing both the timid and the skeptical to the proverbial banquet table that is Posit, this exploration into the world of statistics education should be of interest to a wide audience. My hope is to increase data literacy in real world context – with primary emphasis on descriptive statistics and distributions.

About Mary Rudis: After graduating from Lehigh University in Bethlehem, PA with a degree in Mathematics, Mary began as a high school mathematics and computer science teacher, developing technology infrastructure for a small, private high school in Pennsylvania. Throughout her career, she brings innovative approaches and enjoys the role of trailblazer. Mary’s most recent accomplishments as math department chair included developing mathematics curriculum and coordinating engineering, bioengineering and data science degrees at Great Bay Community College in Portsmouth, NH. Mary’s primary interests are learning and instruction, developing data science curricula for two-year colleges and 4-year liberal arts colleges, and working with area high school students in STEM at the University of NH Tech Camp each summer