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PORemove Holidays and Weekends in a very long time-serie, how to model time-series in Python?
 

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  1. PORemove Holidays and Weekends in a very long time-serie, how to model time-series in Python?
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    <p>Is there some function in Python to handle this. GoogleDocs has a Weekday -operation so perhaps there is something like that in Python. I am pretty sure someone must have solved this, similar problems occur in sparse data such as in finance and research. I am basically just trying to organize a huge amount of different sized vectors indexed by days, time-series, I am not sure how I should hadle the days -- mark the first day with 1 and the last day with N or with unix -time or how should that be done? I am not sure whether the time-series should be saved into matrix so I could model them more easily to calculate correlation matrices and such things, any ready thing to do such things?</p> <p>Let's try to solve this problem without the "practical" extra clutter:</p> <pre><code>import itertools seq = range(100000) criteria = cycle([True]*10 + [False]*801) list(compress(seq, criteria)) </code></pre> <p>now have to change them into days and then change the $\mathbb R$ into $( \mathbb R, \mathbb R)$, tuple. So $V : \mathbb R \mapsto \mathbb R^{2}$ missing, investigating.</p> <p><strong>[Update]</strong> </p> <p>Let's play! Below code solves the subproblem -- creates some test data to test things -- now we need to create arbitrary days and valuations there to try to test it on arbitrary timeseries. If we can create some function $V$, we are very close to solve this problem...it must consider though the holidays and weekends so maybe not easy (not sure).</p> <pre><code>import itertools as i import time import math import numpy def createRandomData(): samples=[] for x in range(5): seq = range(5) criteria = i.cycle([True]*x+ [False]*3) samples += [list(i.compress( seq, criteria ))] return samples def createNNtriangularMatrix(data): N = len(data) return [aa+[0]*(N-len(aa)) for aa in data] A= createNNtriangularMatrix(createRandomData()) print numpy.array(A) print numpy.corrcoef(A) </code></pre>
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      1. PORemove Holidays and Weekends in a very long time-serie, how to model time-series in Python?
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    1. CODoes this help? `today = time.strftime('%A') # as string` or `today = time.strftime('%w') # as integer 0 to 6`
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      1. USSteven Rumbalski
    2. CO`print time.strftime('%A',time.strptime('11/29/1972', '%m/%d/%Y'))` tells me I was born on a Wednesday.
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      1. USSteven Rumbalski
    3. COI think you should create a matrix where each weekday would be defined by its column, identical to what a paper calendar looks like. So, when you want to select mondays, you would use slicing: `mondays = manydays[:,1]`, which is like saying "all elements from second column". In this case, `manydays` is a `numpy.ndarray`.
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