Once an instance is chosen for that session it cannot be changed. While not strictly required, explictly choosing a Python instance is a best practice. To get started, install the reticulate package and set the path to the correct version of Python using the use_python() function. In this post, we will help you get started with reticulate and demonstrate a few useful features of the package. While this is not the first package of this type, the ease of use and available features make it very useful. It is a powerful package which can translate data between R and Python to allow for almost seamlessly integration between the two languages. Reticulate offers the ability to run Python code directly from R. The recently released R reticulate package helps bridge the gap between the two languages and allows users to integrate them into the same workflow. However, it can be difficult to utilize both languages in a data science workflow because of the different tools and data structures of each language.
From my perspective, both languages have their own strengths, and the user should choose based on their specific use case. There is an ongoing debate in the data science world about the merits of R vs. Python.
Run Python code from R using the reticulate package Matt Brown
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