2019-09-05, 12:00–12:30, Track 2 (Baroja)
The main scientific computing programming languages have different models the main data structures of data science such as dataframes and n-d arrays. In this talk, we present our approach to reconcile the data science tooling in this polyglot world.
In this presentation, we demonstrate how xtensor can be used to implement numerical methods very efficiently in C++, with a high-level numpy-style API, and expose it to Python, Julia, and R for free. The resulting native extension operates in-place on Python, Julia, and R infrastructures without overhead.
We then dive into the xframe package, a dataframe project for the C++ programming language, exposing an API very similar to Python's xarray.
Features of xtensor and xframe will be demonstrated using the xeus-cling jupyter kernel, enabling interactive use of the C++ programming language in the notebook.