Time series analysis in Python PDF

Time series analysis can be useful to see how a given asset, security, or economic variable changes over time . It can also be used to examine how the changes associated with the chosen data point compare to shifts in other variables over the same time period.

An observed time series can be decomposed into three components: the trend (long term direction), the seasonal (systematic, calendar related movements) and the irregular (unsystematic, short term fluctuations) .

Time series analysis is a specific way of analyzing a sequence of data points collected over an interval of time . In time series analysis, analysts record data points at consistent intervals over a set period of time rather than just recording the data points intermittently or randomly.