![]() Once web packaging is finally sorted, it'll be near perfect. I can easily interleave code and descriptions, hide what I want, run it from scratch entirely as a default, and produce a range of outputs including interactive static webpages. It is to me what the final output of notebooks should be. The only thing I have against it at the moment is the debugging story isn't very nice by default, though I've not looked into how to improve this.Įdit - if you've not looked into rmarkdown, I heartily recommend it. ![]() ![]() Partly because I already know how to solve the problems I have in python more quickly than in R. I've started using rMarkdown more heavily, with reticulate & python for most data munging and r for plotting. I'm not sure I follow this, you can just set the interpreter. But as far as I can tell, it does not solve the knotty problems that arise in Python, e.g. It's an outstanding effort, and works well for pure computation. "RStudio is to be commended for developing the reticulate package, to serve as a bridge between Python and R. I'd say it has the shortest learning curve (especially for someone familiar with SQL), and is one of the main reasons I still use R today outside of deep learning - I find it much more friendly to work with than any alternative. I also strongly disagree with the Tidyverse bashing. Base R is quirky compared with modern programming languages, and the API is pretty inconsistent. I disagree with the "learning curve" if you've learned other programming languages Python has a pretty simple and familiar core, and Pandas (while the API is an inconsistent mess) is well documented. Python has much better libraries for building general purpose tools (but fewer libraries for complex statistics). Python has good error handling, scripting and logging out of the box and managable package management, and is familiar to most developers and operations. R was built as a language to use interactively and does things like raise warnings for things that should be errors, requires an external package (packrat) for reproducible package management, and in general is foreign to most developers running operations. This is missing the most important difference - deployability.
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