[SciPy-User] Status of TimeSeries SciKit

[Matt Knox]

Wes McKinney <wesmckinn <at> gmail.com> writes:
> 
> I agree. I already have 50% or more of the features in
> scikits.timeseries, so this gets back to my fragmentation argument
> (users being stuck with a confusing choice between multiple
> libraries). Let's make it happen!

Ok. In the interest of moving this forward, here is a quick list of things I
see missing in pandas that scikits.timeseries does. For brevity I will skip the
reasons that these features exist, but if the usefulness is not obvious please
ask me to clarify.

Frequency conversion flexibility:
    - when going from a higher frequency to lower frequency (eg. daily to
      monthly), the timeseries module adds an extra dimension and groups the
      points so you still have all the original data rather than discarding
      data
    - allow you to specify where to place the value - the start or end of the
      period - when converting from lower frequency to higher frequency (eg.
      monthly to daily) 
    - support of a larger number of frequencies

Indexing:
    - slicing with dates (looks like "truncate" method does this, but would
      be nice to be able to just use slicing directly)

- simple arithmetic on dates ("date + 1" means "add one unit at the current
  frequency")
- various date/series attributes such as year, qyear, quarter, month, week,
  day, day_of_year, etc...
  (ref: http://pytseries.sourceforge.net/core.datearrays.html#date-information)
- full missing value support (TimeSeries class is a subclass of MaskedArray)    
- moving (rolling) median/min/max

- Matt Knox