I am following the discussion around DataFrames from distance, but I am really curious about the findings of the main contributors and the future directions of the DataFrame concept in Julia. This post is an attempt to understand what we can hope for in terms of performance given the general concern around type stability and operations that return data frames with different column types.
To start the discussion, my first question is simple:
Can we have high-performance DataFrames in Julia someday? How the type system will play with this different columns, different types issue?
My second question is not really a question, but a push to foster innovation:
In the case that DataFrames aren’t gonna be fast enough, have you thought of alternatives to replace the concept in its entirety? Some data structure that is even better than DataFrames for data scientists?