Ease Uncertainty by Boosting Your Data Science Team's Skills

2020-09-23 Carl Howe
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To help address some of the uncertainty data science leaders may be feeling heading into the fall planning season, we note three new resources to help your team learn new skills and communicate their value better. Read more →

Learning Data Science with RStudio Cloud: A Student's Perspective

2020-09-17 Daniel Petzold, Carl Howe
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Lara Zaremba, a student at Goethe University, shares her experiences using RStudio Cloud to learn data science and how it has empowered her to help teach others. Read more →

Announcing the 2020 RStudio Table Contest

2020-09-15 Rich Iannone and Curtis Kephart
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Today we announce the 2020 RStudio Table Contest. One thing we love about the R community is how open and generous you are in sharing the code and process you use to solve problems. This lets others learn from your experience and invites feedback to improve your work. We hope this contest encourages more sharing, and helps to recognize the many outstanding ways people work with and display data in R. Read more →

Debunking R and Python Myths: Answering Your Questions

2020-09-10 Samantha Toet and Carl Howe
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In this post, we answer questions raised by participants and attendees during our recent Debunking R & Python Myths webinar. Our bottom line was to use the tools that let you be most productive in the shortest amount of time. Read more →

3 Fun Shiny Apps for Your Long Labor Day Weekend

2020-09-04 Carl Howe
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We offer 3 entertaining Shiny apps plus a bonus app from our 2nd Annual Shiny Contest that will help you forget work over Labor Day weekend Read more →

3 Ways to Expand Your Data Science Compute Resources

2020-08-27 Carl Howe
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Data scientists frequently have computational needs that stretch far beyond their laptops. Data science leaders should embrace features of RStudio Server that give data scientists access to shared IT resources without breaking the bank Read more →

Why Package and Environment Management is Critical for Serious Data Science

2020-08-20 Mike Garcia, ProCogia
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The renv package helps create reproducible project environments that are critical for data science teams to deliver real, lasting value. Read more →

R and RStudio - The Interoperability Environment for Data Analytics

2020-08-17 Curtis Kephart and Lou Bajuk
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From design philosophies to current development priorities, R with RStudio is a wonderful environment for anyone who seeks understanding through the analysis of data. Here's why. Read more →

How to Deliver Maximum Value Using R & Python

2020-08-13 Dan Chen, Lander Analytics
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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. Read more →

rstudio::global() talk deadline extension

2020-08-13 Hadley Wickham
We’ve received requests from a number of you to submit talks for rstudio::global() after the deadline (tomorrow, August 14). We know things are particuarly tough at the moment, so we’re extending the deadline by two weeks for everyone;┬áthe new submission deadline is August 28 at 11:59PM PDT. We’ll aim to get decisions back by late September. APPLY NOW! Read more →