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LogoutDevelopers are trying to add more power to Python and Pandas in various ways. Some of the most notable projects are:
Dask: a low-level scheduler and a high-level partial Pandas replacement, geared toward running code on compute clusters.
Ray: a low-level framework for parallelizing Python code across processors or clusters.
Modin: a drop-in replacement for Pandas, powered by either Dask or Ray.
Vaex: a partial Pandas replacement that uses lazy evaluation and memory mapping to allow developers to work with large datasets on standard machines.
RAPIDS: a collection of data-science libraries that run on GPUs and include cuDF, a partial replacement for Pandas.