Python

Using R to Drive Agility in Clinical Reporting: Questions and Answers

2020-10-08 Andy Nicholls, Michael Rimler
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Andy Nicholls and Michael Rimler from healthcare firm GlaxoSmithKline plc (GSK) answer questions posed during their recent webinar, Using R to Drive Agility in Clinical Reporting. Read more →

RStudio v1.4 Preview: Python Support

2020-10-07 Kevin Ushey
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Last week, we introduced RStudio’s new visual markdown editor. Today, we’re excited to introduce some of the expanded support for Python in the next release of RStudio. Python Support The RStudio 1.4 release introduces a number of features that will further improve the Python editing experience in RStudio: The default Python interpreter to be used by RStudio / reticulate can now be customized in the Global Options pane, 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 →

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 →

reticulate 1.14

2019-12-20 Kevin Ushey
We’re excited to announce that reticulate 1.14 is now available on CRAN! You can install it with: install.packages("reticulate") With this release, we are introducing a major new feature: reticulate can now automatically configure a Python environment for the user, in coordination with any loaded R packages that depend on reticulate. This means that: R package authors can declare their Python dependency requirements to reticulate in a standardized way, and reticulate will automatically prepare the Python environment for the user; and Read more →

R vs. Python: What's the best language for Data Science?

2019-12-17 Lou Bajuk
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We will briefly examine the debates over R vs. Python, and then share why we believe R and Python can, should and do work beautifully together. Read more →

Try out RStudio Connect on Your Desktop for Free

2019-02-13 Cole Arendt
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Have you heard of RStudio Connect, but do not know where to start? Maybe you are trying to show your manager how Shiny applications can be deployed in production, or convince a DevOps engineer that R can fit into her existing tooling. Perhaps you want to explore the functionality of RStudio’s Professional products to see if they fit the needs you have in your work. Today, we are excited to announce the RStudio QuickStart, which allows you to try out RStudio Connect for free from your desktop. Read more →

RStudio 1.2 Preview: Reticulated Python

2018-10-09 RStudio Team
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One of the primary focuses of RStudio v1.2 is improved support for other languages frequently used with R. Last week on the blog we talked about new features for working with SQL and D3. Today we’re taking a look at enhancements we’ve made around the reticulate package (an R interface to Python). The reticulate package makes it possible to embed a Python session within an R process, allowing you to import Python modules and call their functions directly from R. Read more →

reticulate: R interface to Python

2018-03-26 JJ Allaire
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We are pleased to announce the reticulate package, a comprehensive set of tools for interoperability between Python and R. The package includes facilities for: Calling Python from R in a variety of ways including R Markdown, sourcing Python scripts, importing Python modules, and using Python interactively within an R session. Translation between R and Python objects (for example, between R and Pandas data frames, or between R matrices and NumPy arrays). Read more →