time series data and NumPy

[Diez B. Roggisch]

BBands wrote:

> Good morning,
> 
> I store time series data in a SQL database. The results of a typical
> query using pyodbc look like this.
> 
> Date            Close
> "2007-01-17" 22.57
> 
> Where Date is a datetime.date object and Close is a float.
> 
> I'd like to put this data in a NumPy array for processing, but am
> unsure as to how to handle the date. In the past I've used lists, but I
> am looking to boost speed a bit as I wish to do a large number of
> transformations and comparisons.
> 
> Can one index an array using datetime objects?
> 
> For example it would be nice to do a union of two arrays so that any
> dates missing in either one were eliminated.
> 
> Thoughts on doing rolling operations, such as an n-period average or
> variance?
> 
> Thoughts on working with time series data in arrays in general?

I'm pretty sure you're out of luck here - even _if_ NumPy would handle
arbitrary data-types (AFAIK it doesn't, but then I'm not a total expert
there), it certainly won't be able to make its hi-performance functions
work on them.

What you could do would be to convert the date-column into a timestamp,
which is a int/long, and use that. Would that help?

diez