quick pass on pandas <-> xts bridge.

[Dale Jung]

https://gist.github.com/3287286

Put this together last night. It will convert pandas DataFrame to an xts object if the index is Datetime. So something like:

rdaily = r['dailyReturn']

rdaily(df) # calling R function with DataFrame within python.

Will work without converting the df explicitly. Also means that 

r.assign('xts_object', df) # properly converts df to xts

assert isinstance(r('dailyReturn(xts_object)'), DataFrame) # properly converts xts output to DataFrame on the python side. 

I don't have a lot of test cases since I'm new to R. So caveat emptor. Just wanted to share and get suggestions if I'm approaching it wrong.

[Dale Jung]

Update on more poking around:

https://github.com/dalejung/trtools/commit/de195f96f496f642f4cc45e40a2257c13f3a4e57

Added a DatetimeIndex <-> POSIXct bridge. 

Changed the index conversion to send m8[s] ints instead of converting to strings first. 

Should respect timezone now. Will always default to UTC when sending over to R because there is no naive datetime in R.

Starting to think that the automatic conversion shouldn't happen. Maybe grabbing a xts from R should return an XTS object instead of a dataframe. Then have a to_df method on XTS.

Otherwise there might be too much random DataFrame and DatetimeIndex creations. 

Same thing for going from DataFrame -> XTS. It's nice to pass in a pandas DataFrame into R functions, but if pass it in twice it will recreate the XTS object twice.