Pandas: Framing the Data
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Data science, and numerical computing, in general, has a problem: the deep linear algebra libraries deal with pure numbers in vectors and matrices, but in the real world there is always metadata attached to those structures that needs to be carried along through the computational pipeline. Rows and columns have information attached to them--names, typically--that has to be accounted for even as we do things like remove rows or swap data around to make certain computations more tractable.