Neal Richardson

Vice President, Engineering at Posit, PBC

nealrichardson

Software by Neal Richardson#

Events attended by Neal Richardson#

Posts and resources by Neal Richardson#

Neal Richardson - MCP, or not MCP | Pydata London 26

Neal Richardson - MCP, or not MCP | Pydata London 26 \Model Context Protocol is a standard for defining tools that can be made available to LLMs and AI applications. There’s a lot of noise out there about what you should use to get the best results from AI, so in this talk, I will provide some guidance on when you should use MCP, and when you should reach for some other tool. I will describe cases where MCP is the right tool for the job, and when other things, like skills or other context files, are better. I will also devote attention to questions of security and authentication, which are important for MCP, and provide concrete examples of how MCP servers can be used to unlock agentic workflows while also strengthening data governance. This talk is intended for those who are interested in using LLMs for workflows involving data. No prior experience with MCP is required. Outline: Intro: how can I get data from this API into my Claude Code session? What is MCP? When should you use it, when should you use other tools Work through an example Sharing and deploying MCP servers, alternatives and best practices Optimizing your tools for best results www.pydata.org 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

Neal Richardson

Neal Richardson | Bigger Data With Ease Using Apache Arrow | RStudio

The Apache Arrow project enables data scientists using R, Python, and other languages to work with large datasets efficiently and with interactive speed. Arrow is so fast at some workflows that it seems to defy reality–or at least the limits of R’s capabilities. This talk examines the unique characteristics of the Arrow project that enable it to redefine what is possible in R. The talk also highlights some of the latest developments in the arrow R package, including how you can query and manipulate multi-file datasets, and it presents strategies for speeding up workflows by up to 100x. About Neal: Currently Director of Engineering at Ursa Labs / RStudio. Previously led product and engineering at Crunch.io. Ph.D. in Political Science from the University of California, Berkeley

Neal Richardson

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 Forcats Rstats Open Source OSS Reticulate Neal Richardson Apache Apache Arrow Big Data

Neal Richardson | Accelerating Analytics with Apache Arrow | RStudio (2020)

The Apache Arrow project is a cross-language development platform for in-memory data designed to improve system performance, memory use, and interoperability. This talk presents recent developments in the ‘arrow’ package, which provides an R interface to the Arrow C++ library. We’ll cover the goals of the broader Arrow project, how to get started with the ‘arrow’ package in R, some general concepts for working with data efficiently in Arrow, and a brief overview of upcoming features

Neal Richardson

rstudio Rstudio::conf(2020) Neal Richardson 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 Rstats Open Source OSS Reticulate Apache Arrow

Neal Richardson

Software by Neal Richardson#

dplyr

reticulate

Shiny for Python

purrr

renv

actions

sparklyr

pak

Events attended by Neal Richardson#

AI in Production

PyData London 2026

Posts and resources by Neal Richardson#

Neal Richardson - MCP, or not MCP | Pydata London 26

Neal Richardson | Bigger Data With Ease Using Apache Arrow | RStudio

Neal Richardson | Accelerating Analytics with Apache Arrow | RStudio (2020)