Spotting patterns in time series

There are four types of patterns we typically should look out for when analyzing time series data. This includes trends, seasonal variations, cyclical variations, and irregular variations. Line plots are very helpful charts for analyzing these patterns. With line plots, we can easily spot these patterns within our dataset.

When analyzing our data for trends, we try to spot a long-term increase or decrease in the values in the time series. When analyzing our data for seasonal variations, we try to identify periodic patterns that are influenced by the calendar (quarter, month, day of the week, and so on). When analyzing our data for cyclical variations, we try to spot sections where the data points rise and fall with varying magnitudes and over longer periods which aren’t fixed; for example, the duration of a cycle is at least two years, and each cycle can occur over a range of years (such as every two to four years) and not a fixed period ...