On 11.02.2014 14:47, Daniele Nicolodi wrote: > On 11/02/2014 14:41, Andreas Hilboll wrote: >> On 11.02.2014 14:22, Daniele Nicolodi wrote: >>> On 11/02/2014 14:10, Andreas Hilboll wrote: >>>> On 11.02.2014 14:08, Daniele Nicolodi wrote: >>>>> Hello, >>>>> >>>>> I have two time series (2xN dimensional arrays) recorded on the same >>>>> time basis, but each with it's own dead times (and start and end >>>>> recording times). I would like to obtain two time series containing >>>>> only the time overlapping segments of the data. >>>>> >>>>> Does numpy or scipy offer something that may help in this? >>>>> >>>>> I can imagine strategies about how to approach the problem, but none >>>>> that would be efficient. Ideas? >>>> >>>> Take a look at pandas. It has built-in time series functionality. >>> >>> Even using Pandas (and I would like to avoid to have to depend on it) it >>> is not clear to me how I would achieve what I want. Am I missing something? >> >> If the two time series are pandas.Series objects and are called s1 and s2: >> >> new1 = s1.ix[s2.dropna().index].dropna() >> new2 = s2.ix[s1.dropna().index].dropna() >> new1 = new1.ix[s2.dropna().index].dropna() >> >> Looks hackish, so there might be a more elegant solution. For further >> questions about how to use pandas, please look at the pydata mailing >> list or stackoverflow. > > Correct me if I'm wrong, but this assumes that missing data points are > represented with Nan. In my case missing data points are just missing.
pandas doesn't care. Andreas. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
