[R] Data.table vs dplr handling multiple variables

Jeff Newmiller
2017-04-28T23:38:44Z

All approaches have strong points and weak points. Your question has no clear
answer.

I happen to like dplyr for many things (including lots of timestamp values), but
base R is always there to solve problems if the analysis framework-du-jour has
troubles. So learn base R ways of doing things if nothing else.

For next time: please read the Posting Guide. Give us a minimal example in R of
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the right answer will look like (consider using the reprex R package), and turn
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--
Sent from my phone. Please excuse my brevity.

On April 28, 2017 8:13:18 AM PDT, Ek Esawi <esawiek at gmail.com>
wrote:
>Hi All?
>
>I am often working with large datasets with multiple variables
>(integer,
>decimal, string, complex, date, and time) that require processing,
>cleaning, etc. I am relatively new to R and I would like to get some
>input
>on the following issue: I am trying to figure out which R-package(s) is
>most suitable for my work. I looked into data.table and dplyr. Both are
>very good but I found out that data.table does not handle time data
>well
>(one has to use fast time package) and not sure whether dplyr does the
>same
>or not. I am not sure about their handling of other variables listed
>above.
>I like data.table.
>
>
>The questions: (1) which package should I invest on learning and how to
>deal with issue like time data and possibly other variables such
>complex
>numbers, date, etc.? (2) What is the ?best? practical solution for such
>issue?
>
>
>
>Thanks in advance,
>
>
>EKE
>
>	[[alternative HTML version deleted]]
>
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