> Finally: some portion of the hate it gets is probably from engineers without a statistics background who aren't familiar with the huge dictionary of jargon and abbreviations its APIs use.

Pandas' jargon isn't really even statistics jargon. For example data frames are tables, which are inherently rows and columns. Columns have names, rows can have names too (although that's not really needed). Pandas' documentation has very few mentions of rows and columns at all, instead they use "axes", "labels" and "index" and there's not even a proper explanation in documentation of what those mean. And that "index" is something that the user needs to manage, sometimes "drop", sometimes "reset" without really understanding why. It seems to me two things: (1) really bad choice of naming things and (2) exposing to users some performance-related details that should have been kept under the hood, if they are needed at all.