indeed.  thank you, josh.  I would add a final chapter at

http://docs.julialang.org/en/release-0.4/

with a set of links to various further resources, examples, full
stand-alone programs, etc.  for me, at least, the perl cookbook and sets of
self-contained snippet programs to start with, were the main reason why I
learned perl many years ago.

the key problem to my use of julia over R for my students is that I do not
have a resident julia expert at UCLA.  this won't change anytime soon,
because they are hard to find (hire) :-(.  this google forum is great, but
it's scary to switch without a double hull.  many, many full *working*
standalone examples are the next best thing for me.

regards,

/iaw


----
Ivo Welch ([email protected])
http://www.ivo-welch.info/
J. Fred Weston Distinguished Professor of Finance
Anderson School at UCLA, C519
Free Finance Textbook, http://book.ivo-welch.info/
Exec Editor, Critical Finance Review,
http://www.critical-finance-review.org/
Editor and Publisher, FAMe, http://www.fame-jagazine.com/

On Wed, Feb 10, 2016 at 10:25 AM, Josh Day <[email protected]> wrote:

> I think a lot of what you're looking for already exists.  It's just that
> things like "run a regression according to variable names" wouldn't belong
> in base Julia.  If you haven't already, I'd take a look at StatsBase.jl,
> DataFrames.jl, and GLM.jl.
>
>
> http://dataframesjl.readthedocs.org/en/latest/io.html#importing-data-from-tabular-data-files
> https://github.com/JuliaStats/GLM.jl
>
>
>
> On Wednesday, February 10, 2016 at 10:58:37 AM UTC-5, ivo welch wrote:
>>
>>
>> ladies and gents---I am not (yet) a julia user.
>>
>> may I suggest adding more examples into two places where julia users will
>> face starting hurdles?
>>
>> [1] the I/O docs of julia.  like, reading and writing csv files that are
>> compressed and decompressed on-the-fly, even if not in the ultimate
>> efficient manner.    a large fraction of the time and frustration of new
>> users is consumed by the task of shoehorning data into and out of new
>> computer languages.  with all of R's problem, the ' d <- read.csv("f.csv")'
>> and 'd<-read.csv(pipe(paste("gzcat ", fname)))' reduced this entry
>> frustration greatly.  perhaps xml file reading and writing.  perhaps...
>>
>> [2] more 'standard task' programs would be great.  read a csv file, run a
>> regression according to variable names on the command line, print output,
>> draw a graph.  I know there are fragments throughout the docs, but some
>> section with ready to run complete programs would be good, perhaps at the
>> end of the manual.
>>
>> in a year, I hope to switch my students from R to julia.
>>
>> regards,
>>
>> /iaw
>>
>>

Reply via email to