While the imdb data contained movie release years, fundamentally the objects of interest were the individual films and the ratings, not a linked series of events over time that might be correlated with one another. This latter type of data – a time series – raises a different set of questions. Are datapoints correlated with one another? If so, over what timeframe are they correlated? How noisy is the signal? Pandas DataFrames have many built-in tools for time series analysis, which we will examine in the next section.
In our previous example, we were able to use the data more or less in the form in which it was supplied. However, there is not always a guarantee that this will be the case. In our second example, we'll look at a time series of oil prices in the US by year over the last century (Makridakis, Spyros, Steven C. Wheelwright, and Rob J. Hyndman. Forecasting methods and applications, John Wiley & Sons. Inc, New York(1998). We'll start...
