Now that pandas provides a data frame structure, is there any need for structured/record arrays in numpy? There are some modifications I need to make to an existing code which requires this structured array type framework, but I am considering using pandas in its place from this point forward. Will I at any point find that I need some functionality of structured/record arrays that pandas does not provide?
pandas's DataFrame is a high level tool while structured arrays are a very low-level tool, enabling you to interpret a binary blob of data as a table-like structure. One thing that is hard to do in pandas is nested data types with the same semantics as structured arrays, though this can be imitated with hierarchical indexing (structured arrays can't do most things you can do with hierarchical indexing).
Structured arrays are also amenable to working with massive tabular data sets loaded via memory maps (np.memmap). This is a limitation that will be addressed in pandas eventually, though.