[Numpy-discussion] Question on timeseries, for financial application
Sat Dec 12 19:08:22 CST 2009
Quite new to numpy / timeseries module, please forgive the elementary question.
I wish to do quite to do a bunch of multivariate analysis on 1000 different financial markets series, each holding about 1800 data points (5 years of daily data).
What's the best way to put this into a TimeSeries object? Should I use a structured data type (in which case I can reference each series by name), or should I put it into one big numpy array object (in which case I guess I'll have to keep track of the series name in an internal structure)? What are the advantages and disadvantages of each?
Ideally I'd have liked the ease and simplicity of being able to reference each series by name, while maintaining the fast speed and clean structure of one big numpy array. Any way of getting both?
Once I have a multivariate TimeSeries, how do I add another series to it?
Thanks for the help.
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