![]() Here’s what we liked about the new RStudio IDE Python Integration: py file) and worked interactively with the RStudio IDE’s console, help documentation, and plotting panel performing basic operations that a data scientist will be doing quite frequently. With the rollout of the Python Integration - a major new feature in RStudio - We did a product review of the RStudio IDE from the perspective of data scientist using Python. RStudio is making the case for a powerful mult-language IDE designed for Data Science. Let’s take a look at how the Python integration works. With this release, RStudio is making a case for a powerful, all-in-one R + Python Data Science IDE. The RStudio Version 1.2 Preview Edition comes with support for Python and several other data science languages including SQL and Stan. Until now - RStudio is making the case for a powerful mult-language IDE designed for Data Science. Most data scientists write their code in separate places - Python is written in Jupyter Notebooks, and R is written in the RStudio IDE. The Python language has the Jupyter Notebook (and more recently Jupyter Lab) that provides a web-based notebook. The R language has the RStudio IDE, which is a great IDE for data science because of its feature rich setup for efficiently developing analyses. ![]() The two major data science languages, Python and R, have historically taken two separate paths when it comes to where data scientists are doing the coding. Python Integration in RStudio - Data Science IDE Review ![]()
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