Rstudio Connect

Daniel Petzold || RStudio Team: Building and Sharing Jupyter Notebooks || RStudio

Learn more about RStudio Team here. https://www.rstudio.com/products/team/ Find the code for this example here. https://github.com/danielpetzold/space-tracker Read our blog post here. https://www.rstudio.com/blog/build-and-share-jupyter-notebooks-on-rstudio-team/ Timecodes 0:00 - Intro 0:07 - Build Jupyter Notebooks to analyze and visualize data 2:47 - Publish directly from RStudio Workbench to your content hub 5:13 - Share With Your Stakeholders on RStudio Connect Jupyter Notebooks are interactive documents for code, outputs, and text. However, they’re often stuck in data scientists’ local computing environments. Collaborating can be difficult and sharing can be tedious. To live up to their fullest potential, data science teams need a way to scale their development securely and efficiently — while providing stakeholders easy access to their output and visualizations. RStudio Team, made up of RStudio Workbench, RStudio Connect, and RStudio Package Manager, brings everything together to help data scientists create, reproduce, and share insights from their Jupyter Notebooks. Let’s dive into a real-life example by exploring data from NASA’s Center for Near-Earth Objects (NEOs). Daniel Petzold walks us through his data analysis and reporting. Want to explore the report yourself? Check out the published report on RStudio Connect here. https://colorado.rstudio.com/rsc/space-tracker/space_tracker.html On RStudio Workbench, you have a choice of editors: the RStudio IDE, JupyterLab, Jupyter Notebook, or VS Code. Choose your preference. From here, you can explore your dataset, embed HTML directly in your document, create visualizations, and more. Once you've run your analyses and created insightful visualizations, you want to be able to share them with your team. RStudio Workbench allows you to publish to RStudio Connect, the content platform from RStudio. You have multiple options: push-button deployment from Jupyter Notebook or using terminal commands from JupyterLab. It’s not enough to publish your work. Once on RStudio Connect, you can share with end-users. Make your analysis accessible to specific users or more generally with different authentication measures. In addition, you can schedule the document to run at a certain time and send out an email with refreshed data. Click the links below to learn more about these offerings. RStudio Workbench: https://www.rstudio.com/products/workbench/ RStudio Connect: https://www.rstudio.com/products/connect/

RStudio Team

Enabling Remote Data Science Teams | RStudio (2020)

Whatever happens in the coming months, remote work is here to stay. The goal of this webinar is to provide data scientists and data science team leaders with the knowledge and tools to succeed as a distributed team. Some of the topics we will cover include: - Setting up a remote and collaborative R environment - Version control and Scrum - Using Shiny and RStudio Connect to share apps within and across teams - How to improve the UI and appearance of Shiny dashboards - How to scale Shiny dashboards to hundreds of users - How to build and grow a remote data science team About Alex: Alex is a Solutions Engineer at RStudio, where he helps organizations succeed using R and RStudio products. Before coming to RStudio, Alex was a data scientist and worked on economic policy research, political campaigns, and federal consulting. About Olga: Olga is experienced in production applications of analytical solutions, especially for FMCG companies. Recently she developed a price elasticity model for Unilever. About Damian: Damian is one of the four co-founders of Appsilon. Before founding Appsilon he worked at Accenture, UBS, Microsoft and Domino Data Lab. About Pedro: Pedro has nearly a decade of experience combining frontend and backend technologies, and is an expert on augmenting R Shiny dashboards with CSS and JavaScript

Collaboration with RStudio Connect - Push Button Publishing + Github.

This tutorial shows you best practices for collaborating with colleague data scientists with RStudio Connect. It walks you through how add collaborators to your RStudio Connect output (Rmd, Shiny Apps, APIs, etc), and how to work with collaborators with version control like git. Steps to Collaboration: Original Author (Kelly) 1. Create document and publish to RStudio Connect 2. Add collaborator on RStudio Connect 3. Share `rsconnect` folder via version control Collaborator (Alex) 1. Pull down code and `rsconnect` folder from version control. 2. Make changes. 3. Publish back to RStudio Connect

The Tidyverse and RStudio Connect | RStudio Webinar - 2017

This is a recording of an RStudio webinar. You can subscribe to receive invitations to future webinars at https://www.rstudio.com/resources/webinars/ . We try to host a couple each month with the goal of furthering the R community's understanding of R and RStudio's capabilities. We are always interested in receiving feedback, so please don't hesitate to comment or reach out with a personal message

Connect Production | RStudio Webinar - 2017

This is a recording of an RStudio webinar. You can subscribe to receive invitations to future webinars at https://www.rstudio.com/resources/webinars/ . We try to host a couple each month with the goal of furthering the R community's understanding of R and RStudio's capabilities. We are always interested in receiving feedback, so please don't hesitate to comment or reach out with a personal message

Connect Basics | RStudio Webinar - 2017

This is a recording of an RStudio webinar. You can subscribe to receive invitations to future webinars at https://www.rstudio.com/resources/webinars/ . We try to host a couple each month with the goal of furthering the R community's understanding of R and RStudio's capabilities. We are always interested in receiving feedback, so please don't hesitate to comment or reach out with a personal message

Tareef Kawaf | Posit useR! 2017 Presentation, Brussels

What has Posit been up to?

Using RStudio Connect in Production