Thanks on name!

Fair enough on docs being a bit scarce. The main intent is to being able to easily make a pandas dataframe a sequence of tuple/namedtuples, and convert a sequence of tuple/namedtuple to a pandas dataframes.

There seems to be a lot of similar functionality (although in a very different paradigm) to Pandas, I'd be very interested to see performance benchmarks between the two on some common pipelines (csv -> filter -> aggregate -> SQL)

For operations where vectorization pandas will be much faster since its based on numpy. That being said, there are things which are very awkard to do in pandas which are very easy in pyfunctional