nd4j

The core looks close enough to dataframes that I'd be curious to know how you compare to tablesaw: https://github.com/jtablesaw/tablesaw This looks neat but I'm not sure why I would care about this. There's a ton of solutions out there in the ecosystem out there already with a columnar like interface. Granted, we wrote our own as well[1] that uses the builder pattern that you then toss to an executor (our main backend is spark for this). One reason we wrote this is for persistence purposes. Being able to encode and persist a series of transforms that you can then load remotely has been very helpful for us in machine learning. We've since migrated this project to the eclipse foundation and intend on doing a rewrite of the interface as well as integrate our baked in tensor library[2] in to certain parts of the pipeline for speed purposes an