search for: practicaldatascience

Displaying 7 results from an estimated 7 matches for "practicaldatascience".

2020 May 01
0
Request: tools::md5sum should accept connections and finally in-memory objects
...md5.c#L27 > > ______________________________________________ > R-devel at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel --------------- John Mount http://www.win-vector.com/ <http://www.win-vector.com/> Our book: Practical Data Science with R http://practicaldatascience.com <http://practicaldatascience.com/> [[alternative HTML version deleted]]
2020 Jan 14
0
[R] choose(n, k) as n approaches k
...gmail.com > > ______________________________________________ > R-devel at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel --------------- John Mount http://www.win-vector.com/ <http://www.win-vector.com/> Our book: Practical Data Science with R http://practicaldatascience.com <http://practicaldatascience.com/> [[alternative HTML version deleted]]
2020 Jan 15
4
A bug understanding F relative to FALSE?
Hi all, Is the next behaviour suitable? identical(F,FALSE) ## [1] TRUE utils::getParseData(parse(text = "c(F,FALSE)", keep.so=rce = TRUE)) ## line1 col1 line2 col2 id parent token terminal text ## 14 1 1 1 10 14 0 expr FALSE ## 1 1 1 1 1 1 3 SYMBOL_FUNCTION_CALL TRUE c ## 3 1 1 1 1 3
2020 May 01
4
Request: tools::md5sum should accept connections and finally in-memory objects
AFAIK there is no hashing utility in base R which can create hash digests of arbitrary R objects. However, as also described by Henrik Bengtsson in [1], we have tools::md5sum() which calculates MD5 hashes of files. Calculating hashes of in-memory objects is a very common task in several areas, as demonstrated by the popularity of the 'digest' package (~850.000 downloads/month). Upon
2020 Jan 15
1
[R] choose(n, k) as n approaches k
...gt;> >> ______________________________________________ >> R-devel at r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-devel > > --------------- > John Mount > http://www.win-vector.com/ > Our book: Practical Data Science with R > http://practicaldatascience.com > > > > > -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
2020 Jan 14
4
[R] choose(n, k) as n approaches k
OK, I see what you mean. But in those cases, we don't get the catastrophic failures from the if (k < 0) return 0.; if (k == 0) return 1.; /* else: k >= 1 */ part, because at that point k is sure to be integer, possibly after rounding. It is when n-k is approximately but not exactly zero and we should return 1, that we either return 0 (negative case) or n
2020 May 01
1
Request: tools::md5sum should accept connections and finally in-memory objects
..._________________________ >> R-devel at r-project.org <mailto:R-devel at r-project.org> mailing list >> https://stat.ethz.ch/mailman/listinfo/r-devel > > --------------- > John Mount > http://www.win-vector.com/ > Our book: Practical Data Science with R > http://practicaldatascience.com > > > > >