Telling Stories with Data - Data Points: Visualization That Means Something - page 9

and decrease, but by how much do they change per day? Per week? Per
month? Are there periods when the stock went up more than usual? If so,
why did it go up? Were there any specific events that triggered the change?
As you can see, when you start with a single question as a starting point,
it can lead you to additional questions. This isn't just for time series data,
but with all types of data. Try to approach your data in a more exploratory
fashion, and you'll most likely end up with more interesting answers.
You can split your time series data in different ways. In some cases it
makes sense to show hourly or daily values. Other times, it could be bet-
ter to see that data on a monthly or annual basis. When you go with the
former, your time series plot could show more noise, whereas the latter is
more of an aggregate view.
Those with websites and some analytics software in place can identify with
this quickly. When you look at traffic to your site on a daily basis, as shown
in Figure 1-6, the graph is bumpier. There are a lot more fluctuations.
FIGurE 1-6 Daily unique visitors to FlowingData