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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