R packages for data science
28 points
7 days ago
| 5 comments
| tidyverse.org
| HN
tanvach
2 minutes ago
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A plug for tidyverse adjacent data.table - really should be combined someday :)
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parsimo2010
55 minutes ago
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I almost wish Hadley had forked R to make the tidyverse. What I usually see are people that start using tidy functions and coding style, but at some point they realize they don’t know how to do something the tidy way or something hasn’t been implemented in a tidy package yet, so they fall back to base R.

Imho, transitioning from tidy to base R makes your code less readable than just using base R throughout.

If the tidyverse were forked and base R functions weren’t available then people would be forced to come up with a different solution and maybe they would stay committed to being tidy. I realize that probably won’t ever happen, there is too much work to reimplement all the missing base R functions.

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Fomite
19 minutes ago
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This. They're basically two languages sitting on top of each other. It's fascinating seeing students who have been taught using the tidyverse try to switch gears.
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mushufasa
1 hour ago
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To pre-empt critics of R, remember: R is a lisp!
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UniverseHacker
1 hour ago
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But with a much more human legible syntax that doesn’t require huge numbers of nested parentheses.
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tetris11
57 minutes ago
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    `+`(1,2)
is a valid R call for anyone wondering
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vharuck
16 minutes ago
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So is this:

    `(`(1)
Bonus points: Find a use for having the parenthesis be a function.
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techsystems
1 hour ago
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Use tidytable Much faster, exact same syntax, much smaller member usage
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svoit
1 hour ago
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The Tidyverse is solid. I sometimes wish I used R more in industry because of how good it is.

IMO, R is kind of a syntactic Frankenstein otherwise.

Tidymodels also exists: https://www.tidymodels.org/

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mscbuck
1 minute ago
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From what I saw in the latest "language" surveys or whatever, R does seemingly seem to be making a slight comeback. I was actually surprised at its place above Ruby, iirc. Again, not that these surveys are the end-all-be-all, but I've also started to see a lot more data science postings that have R or Python be a requirement, where I feel like for a few years it was ALL Python.
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