Congratulations. This is really a great effort and something we really 
needed. I hope the community takes this as the base layer for data science 
and we can build on your efforts, expand the documentation, etc.



On Monday, June 15, 2020 at 5:50:52 PM UTC+1, Chris Nuernberger wrote:
>
> Good morning Clojurians :-)
>
> It is with much pride that I announce version 2.0 of tech.ml.dataset 
> <https://github.com/techascent/tech.ml.dataset>, our library that maps 
> powerful concepts from libraries like Pandas and data.table into Clojure 
> using functional paradigms. This data frame 
> <https://github.com/mobileink/data.frame/wiki/What-is-a-Data-Frame%3F> 
> library has unified loading from csv, tsv, xlsx, xls, Apache parquet, 
> Apache arrow (.feather), sql, json and sequences of maps as well as 
> efficient cpu and memory 
> <https://gist.github.com/cnuernber/26b88ed259dd1d0dc6ac2aa138eecf37> 
> performance. Finally, because the dataset knows the datatype of each 
> column, you can interoperate with schema-ful things like SQL 
> <https://github.com/techascent/tech.ml.dataset.sql> without writing down 
> the schema.
>
>
> user> (require '[tech.ml.dataset :as ds])
> nil
> user> (-> (ds/->dataset "https://vega.github.io/vega/data/stocks.csv";)
>           (ds/descriptive-stats))https://vega.github.io/vega/data/stocks.csv: 
> descriptive-stats [3 10]:
>
> | :col-name |          :datatype | :n-valid | :n-missing |       :min |      
> :mean | :mode |       :max | :standard-deviation | :skew |
> |-----------|--------------------|----------|------------|------------|------------|-------|------------|---------------------|-------|
> |      date | :packed-local-date |      560 |          0 | 2000-01-01 | 
> 2005-05-12 |       | 2010-03-01 |                     |       |
> |     price |           :float32 |      560 |          0 |      5.970 |      
> 100.7 |       |      707.0 |               132.6 | 2.413 |
> |    symbol |            :string |      560 |          0 |            |       
>      |  MSFT |            |                     |       |
>
> Data science is (still) alive and well in Clojure and the JVM. Stepping 
> back and considering python bindings 
> <https://github.com/clj-python/libpython-clj>, R bindings 
> <https://github.com/scicloj/clojisr>, smile <https://haifengl.github.io/>, 
> the next-gen blas/numerics library Neanderthal 
> <https://github.com/uncomplicate/neanderthal> and the exceptionally 
> powerful saite science platform <https://github.com/jsa-aerial/saite>, we 
> have really come a long way in the last year! 
>
> Thanks and enjoy :-)
>

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