Clojure is an Amazing tool for data science.  If people are slow to realize 
this, that is their disadvantage.

The premise that "Clojure hasn't developed as a go to for data science" 
simply doesn't ring true to me at all.  There are numerous examples of 
Clojure use for data science, there are books about it, there are youtube 
videos about it, there are practitioners, there is Incanter, there are 
Transducers, there are Notebooks (Gorilla is awesome), there are Java 
libraries, there are wrapper Clojure libraries, there are a lot of useful 
tools.  

Clojure is my "go to for data science" and I often use it either directly, 
or to manage runs using fast tools (like vw), or to prepare SQL-izations of 
data etc... (Btw, your SQL often runs as easily in 
Postgres/Redshift/Hive/Spark with minimal changes if any if you need to 
scale etc... If you treat your SQL the way you treat HTML, let your customs 
functions write it, you get a lot of analytic power that is not tied to any 
particular database).  There is Clojurescript for visualization... There is 
so much that I am certain I am forgetting to mention some of it.

Also, Big +1 for emacs use (cider is awesome! I rarely want to touch a 
mouse... ) 

Thanks for an amazing, innovative Emacs and Clojure commuity!!

-Avram

The sky is the limit.  







On Sunday, March 29, 2015 at 2:55:34 AM UTC-7, Sayth Renshaw wrote:
>
> Hi 
>
> I last learned clojure in 1.2. Just curious why Clojure hasn't developed 
> as a go to for data science? 
>
> It never seems to get a mention R,Python and now Julia get the attention. 
> By design it would appear that Clojure would be a good fit. Is it a lack of 
> libraries, ease of install, no good default environment  (R Rstudio, 
> IPython ) where as you would need to use emacs with clojure, or is there 
> just a better default use of Clojure? 
>
> Sayth

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