Gnumeric for Data Science

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From gnumeric-list-bounces gnome org Fri Jun  5 15:32:00 2015
From: "W. D. Allen" <ballensr gmail com>
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Can a *'GNUmeric spreadsheet + Python' *
configuration function equivalently to
'*R + any one of different spreadsheets'*
for doing Data Science statistics work?

Well the short answer is, "No.";-)

For a more nuanced approach you might separate the programming
language from the spreadsheet.  

For me the main advantage of Gnumeric is that some of its statistical
routines are better than Excel, but AFAIK Gnumeric does not run Excel
macros.  Also, last I knew Gnumeric had been discontinued for Windows.
In any case, I would see a spreadsheet as useful mainly as a data
container and possibly for some very light data cleaning.  They are
also great for browsing data to get a feel for what sort of surprises
are in there.  I would not recommend doing serious statistics with any

R and Python are not entirely comparable.  Python is a general purpose
language and add-ins can extend its statistical capabilities to a point
where it has about 0.037% of the power of R.  But this may be all you
need.  If the task is mainly getting the data into usable form, after
which only basic statistics will be applied to it, Python can be a
good choice.

R is a special purpose language for statistics.  Where Python has a
few addins for stats. R has thousands.  R is an implementation of the
S programming language from Bell Labs, also home of Unix and C.  The
Unix philosophy is specialized tools for each purpose that can be
strung together in a chain to complete complex tasks.  While R has
been ported to other environments, it's not always a good fit if users
are not thinking like Unix users.  For example, Windows users may
complain about R's limited data cleaning capabilities, while Unix
users would just use standard Unix tools for that (AWK, Perl, Emacs,
and maybe Python).

These are my opinions.  You may get others here;-) You can probably
find extensive flame wars on the net for R vs. Python.

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