This seems to come up every single time these libraries are brought up around here. People who are primarily programmers don't seem to understand these librarie

This seems to come up every single time these libraries are brought up around here. People who are primarily programmers don't seem to understand these libraries weren't written for them. Wes McKinney was working at a hedge fund when he wrote pandas. The history of Numpy dates back to researchers at MIT and LLNL petitioning Guido to extend the Python syntax to facilitate array programming, because it is supported in programming languages primarily used by scientists and engineers like MATLAB, R, S-Plus. Broadcasting in these languages is fairly intuitive and well understood by the users, and not considered surprising, because it matches pretty closely the way you symbolically manipulate vectors, matrices, and tensors on paper. The array syntax is not what you expect if you're coming from a background primarily in programming applications using other dynamically-typed languages or even Python itself, but it's exactly what you'd expect if you're a scientist used to using MATLAB, or even just used to doing math on paper. And at least back in the early days, that was how hedge funds and quantitative finance worked. They weren't looking for application programmers. They were looking for physicists and electrical engineers. It was a lot easier to teach them how to program than to teach programmers about Brownian motion and stochastic processes. For their intended use cases, Numpy and pandas are among the greatest tools ever created, honestly comparable to MATLAB itself except also free.