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Con No library ecosystem for modern data science: exploratory data analysis, statistics, machine learning
Fortran is good for pure number crunching on supercomputers. The available open source libraries are mostly in domains like physics or climate science and they are mostly about things like simulations or partial differential equations solving. So it's more suitable for going from models to data, rather than for data science, which is the reverse: going from data to models. Even if you decide to use Fortran for computation, things like getting data from databases and visualization have to be done with non-Fortran libs. Nevertheless, it's worth noting that data science languages like Julia, R, or Python do use wrapped Fortran libraries (mostly for matrix computations).
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