> numpy already has, like, 99% of that functionality built in in the form of structured arrays and records
Respectfully, this is pretty wrong. Pandas does vastly more out of the box than numpy. Off the top of my head: I/O from over a dozen of data formats, joins/merges, sql queries directly to dataframes, sql-like queries on dataframes, index slicing by time, multi-indexes, much more ergonomic grouping/aggregation functions, ergonomic wrappers around common graphing use-cases, rolling windows.
I'm not even really a power user of it, so there's probably a zillion more things it does that numpy can't out of the box, and I don't wanna spend time writing time and validating if an implementation exists.
Respectfully, this is pretty wrong. Pandas does vastly more out of the box than numpy. Off the top of my head: I/O from over a dozen of data formats, joins/merges, sql queries directly to dataframes, sql-like queries on dataframes, index slicing by time, multi-indexes, much more ergonomic grouping/aggregation functions, ergonomic wrappers around common graphing use-cases, rolling windows.
I'm not even really a power user of it, so there's probably a zillion more things it does that numpy can't out of the box, and I don't wanna spend time writing time and validating if an implementation exists.