R

What are the main drawbacks of using R for data science?

The question is about R .

Answer:

The real drawbacks of R for data science are not the interface, they are memory behavior on large datasets and a split ecosystem that adds an extra learning curve most languages don't have. R's default execution is single threaded and works with data loaded fully into memory, so a dataset larger than available RAM can slow to a crawl or fail outright without extra tooling.

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