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highOutput = [] lowOutput = [] lsth = [None]*window lstl = [None]*window for i in range(0, len(highValue)): maxValue=0 lsth.append(highValue[i]) lsth = lsth[-window:] for j in range(0, len(lsth)): if lsth[j] > maxValue: maxValue = lsth[j] highOutput.append(maxValue) for i in range(0, len(lowValue)): ...


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Instead of wild guesses about R's/python's future in the community, here some facts: The following query on StackExchange Data Explorer counts the number of questions that have <r> or <python> tags. If you scroll down on one of the three webpages provided below, you can see a graph with data on a monthly basis. You can easily run this query on ...


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The major advantage of Python (w/ pandas) over R is that Python supports OOP (object-oriented programming). It makes sense to organize a large code base using a hierarchy of classes. Python also supports the notion of polymorphism so that we can use well-known design patterns (e.g., Strategy, Observer, etc.) in our code.



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