Performance: works with huge tabular data, processes rows/second
Lazy / Virtual columns: compute on the fly, without wasting ram
Memory efficient no memory copies when doing filtering/selections/subsets.
Visualization: directly supported, a one-liner is often enough.
User friendly API: you will only need to deal with the DataFrame object, and tab completion + docstring will help you out: ds.mean<tab>, feels very similar to Pandas.
Lean: separated into multiple packages