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.
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.