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
>
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---------------
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/>
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2020 Jan 14
0
[R] choose(n, k) as n approaches k
...gmail.com
>
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---------------
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/>
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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
>
>
>
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