The ongoing debate on the two most widely-used tools in Data Science, Python and R, has always been fascinating. Each side presents arguments, making it difficult to choose between the two.

My opinion is that you need to use the best tool for the project. Sometimes R will be better. Sometimes Python will be better. But what happens if you need both languages in the same workflow? Do you need to choose? No, is the simple answer. You can use both.

Posit PBC brings an innovative solution that allows the use of both languages in a single project. I tested it on a text classification project using BERT. The language model and the data are downloaded from Hugging Face with Python code, exploring the data with tidyverse and modeling preparation with tidymodels, both packages from R.

It’s remarkable to see how easily it is to switch between both languages.

Clear, only one language could have been used to this demo. However, it is nice to navigate between both in the same workflow.

Link to the demo: https://rpubs.com/Teguim/textclassificationwithBERT