Dear Gabor,
THanks a lot
THanking you,
Yours sincerely,
AKSHAY M KULKARNI
From: Gabor Grothendieck
Sent: Thursday, December 12, 2024 7:39 PM
To: akshay kulkarni
Cc: R help Mailing list
Subject: Re: [R] SQL and R
The advantages of SQL
The advantages of SQL are that
- it can be used from many languages so if you know SQL you can easily
move that part of your code to python, say,
and visa versa
- it is widely used
- it can handle data stored outside of R and possibly otherwise too large for R
- some SQL databases support multiple
From: R-help on behalf of Eberhard W Lisse
Sent: Thursday, December 12, 2024 2:53 AM
To: r-help@r-project.org
Subject: Re: [R] SQL and R
Looks like an assignment question.
If so, do your homework yourself. Google is your friend
el
On 2024-12-11 15:16, akshay kulkarni wrote:
> dear Memb
...@gmail.com ; Ben
Bolker
Subject: Re: [R] SQL and R
And to answer the dependency question.
Neither is dependent on the other. But both can be complimentary.
If you consider that SQL*may* be a route to accessing your data (if it's in a
database).
And R *may* be a route to analysis of the
Dear John,
THanks a lot.
THanking you,
Yours sincerely,
AKSHAY M KULKARNI
From: Sorkin, John
Sent: Thursday, December 12, 2024 3:09 AM
To: akshay kulkarni ; R help Mailing list
; avi.e.gr...@gmail.com ; Ben
Bolker
Subject: Re: SQL and R
Dea
Dear JC,
THanks .
THanking you,
Yours sincerely,
AKSHAY M KULKARNI
From: R-help on behalf of J C Nash
Sent: Wednesday, December 11, 2024 10:27 PM
To: r-help@r-project.org
Subject: Re: [R] SQL and R - tangential
My late friend Morven
Dear Bert,
THanks a lot
From: Bert Gunter
Sent: Wednesday, December 11, 2024 9:25 PM
To: akshay kulkarni
Cc: R help Mailing list
Subject: Re: [R] SQL and R
Just a slight technical note -- Ben gave you a good answer already, imo.
The note is
Some people prefer SQL syntax. Also, SQL implementations are generally
intrinsically linked with persistent disk storage, so it works
straightforwardly with data sets larger than RAM. Finally, most implementations
support shared access to the data from multiple clients.
A long time ago in a com
And to answer the dependency question.
Neither is dependent on the other. But both can be complimentary.
If you consider that SQL*may* be a route to accessing your data (if it's in
a database).
And R *may* be a route to analysis of the data.
If the data is in a CSV file, Excel file, API etc. y
Dear Askay,
I believe my grey hair allows me to help answer your question. SQL, and its
progenitor SEQUEL, were developed specifically to manipulate relational
databases. It was developed in the early 1970s (equivalent to the historical
bronze age) when the concept of a relational database (see
Looks like an assignment question.
If so, do your homework yourself. Google is your friend
el
On 2024-12-11 15:16, akshay kulkarni wrote:
> dear Members, I have recently started studying SQL and MySQL. My
> question is, what exactly is SQL used for? That is, whatever can be
> done by SQL, like
8 AM
To: r-help@r-project.org
Subject: Re: [R] SQL and R - tangential
My late friend Morven Gentleman, not long after he stepped down from being
chair
of Computer Science at Waterloo, said that it seemed computer scientists had
to create
a new computer language for every new problem they encounter
My late friend Morven Gentleman, not long after he stepped down from being chair
of Computer Science at Waterloo, said that it seemed computer scientists had to
create
a new computer language for every new problem they encountered.
If we could use least squares to measure this approximation, we'
Akshay,
Your question has way too many answers.
SQL has a long history and early versions came long before R arrived on the
scene. There is a huge embedded base of hardware and software dedicated to
managing databases. It has some features that most R programs do not even
dream of doing. Besides
Just a slight technical note -- Ben gave you a good answer already, imo.
The note is: R is Turing complete, which mean that *anything* any
language can do, R could be programmed to do also. The point is what
can be done well in R and what can be done (often much) better with
other tools, as Ben ex
Others may know more than I do, but roughly:
(1) SQL provides access to relational database management systems
that are much more robust and handle large-scale data;
(2) methods based on SQL will often handle data that are too large to
fit in memory
R complements SQL by providing a mu
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