matloff / matloff/R-vs.-Python-for-Data-Science
Include meta-programming capabilities?
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- Stars
- 448
- Forks
- 40
- PR merge metrics
- No merged PRs in 30d
Description
I think this is a great comparison that maintains a level of objectivity we don't usually see with these types of comparisons.
Would it be worth including meta-programming facilities? I think R is far and away the winner and I think it's one of the core reasons R is able to facilitate the construction of DSLs (like a large portion of the tidyverse) in ways that are currently not possible in Python.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or entry point is named. Start by reviewing the existing comparison and its treatment of R and Python, then determine whether meta-programming and DSL construction belong in scope and what evidence would make the comparison complete.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, r
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100