R and Python, a Data Science Love Story

A webinar presentation by RStudio

Live on January 16, 2020 at 11am-12pm EST

What You'll Learn
Many Data Science teams today are bilingual, leveraging both R and Python in their work. While both languages are tremendously powerful, teams frequently struggle to use them together. We’ve heard from our customers how even experienced data scientists familiar with both languages often struggle to combine them without painful context switching and manual translations. Data Science leaders and business stakeholders find it difficult to make key data science content easily discoverable and available for decision-making, and IT Admins and DevOps engineers grapple with how to efficiently support these teams. 
In this webinar, you will learn how RStudio helps Data Science teams tackle all these challenges, and make the Love Story between R and Python a happier one: 
  • Easily combine R and Python in a single Data Science project
  • Leverage a single infrastructure to launch and manage Jupyter Notebooks and JupyterLab environment, as well as the RStudio IDE
  • Organize and share Jupyter Notebooks alongside your work in R and your mixed R and Python projects.
This webinar will show examples of all these capabilities, and discuss the benefits of leveraging R and Python.


Jenny Bryan

About Roche & Genentech

James holds a master’s degree in data science from the University of the Pacific and works as a solutions engineer. He works to integrate RStudio products in enterprise environments and support the continued adoption of R in the enterprise. His past consulting work centered around helping businesses derive insight from data assets by leveraging R. Outside of R and data science, James’s interests include spending time with his wife and daughters, cooking, camping, cycling, racquetball, and exquisite food. Also, he never turns down a funnel cake.

Jenny Bryan

About Lou Bajuk

Sr. Director of Product Marketing at RStudio

Lou is a passionate advocate for data science software, and has had many years of experience in a variety of leadership roles in large and small software companies, including product marketing, product management, engineering and customer success. In his spare time, his interests includes books, cycling, science advocacy, great food and theater.

Jenny Bryan

About Sean Lopp

Product Manager at RStudio

Sean leads teams to create useful, enjoyable products. Before RStudio he was a data scientist and worked on alternative vehicle models at NREL, infant sleep dynamics, and originally studied mathematics. He lives outside Denver, CO and skis and bikes with his family.

Jenny Bryan

About the speaker

Jenny Bryan is a recovering biostatistician who takes special delight in eliminating the small agonies of data analysis. She’s part of Hadley’s team, working on R packages and integrating them into fluid workflows. She’s been working in R/S for over 20 years, serves in the leadership of rOpenSci and Forwards, and is an Ordinary Member of the R Foundation. Jenny is an Associate Professor of Statistics (on leave) at the University of British Columbia, where she created the course STAT 545.


Only 1,000 live attendees are allowed in the Webinar on a first come first serve basis. There will be approximately 60 minutes of presentation. While we usually have a question and answer session, there will be a lot of ground to cover during this presentation. 

Slides & Code

We've started a Github repository with all webinar materials. Speakers for this webinar and all future webinars will add their materials to the repository. https://github.com/rstudio/webinars

Webinar Recordings

If you can't attend, don't worry. We record (almost) every webinar and post all materials on our website within 48 hours. See past webinars at https://resources.rstudio.com/webinars

RStudio provides the premiere open source and enterprise-ready professional software for R, including RStudio Desktop, RStudio Server, RStudio Connect, RStudio Package Manager Shiny Server, and shinyapps.io. The tidyverse, shiny, ggplot, ggvis, dplyr, knitr, R Markdown, and packrat are R packages from RStudio that every data scientist will want to enhance the value, reproducibility, and appearance of their work.