Visualize How Components Contribute to Totals With Stack Graphs
Stack Graphs let you visualize quantitative changes to several data sets over time, and you can see how each datapoint contributes to the total. This classic method for visualizing changes in a set of items lets you analyze the sum of the values as well as the individual items in a single chart.
Financial services applications include looking at market cap data over time for several instruments in a portfolio, or reviewing stock price changes in various market sectors. In corporate applications, Stack Graphs are a great way to look at revenue or gross profit figures over time across several product lines.
Stack Graphs are a good choice when you have up to ten or eleven time series datasets to look at, especially for datasets that have a large number of positive datapoints. They are excellent information visualizations to use in conjunction with our Treemap, Heatmap or Scatter Plot tools since they provide different perspectives on the same set of data.
See how constituents contribute to the total on a relative basis
The Percentage Area Graph form of the Stack Graph allows you to plot how the components contribute to the total (100%) in percentage terms. It is an excellent choice for charting time series data when you are interested in seeing the relative contributions for each data set in the series, regardless of the absolute total. This helps you see trends in how each component in the database has changed compared to the others which can easily be missed in a Stack Graph.
Percentage Area Graphs let you visualize quantitative changes to several datasets over time, and you can see how each data point contributes to the total. However, instead of displaying absolute contributions as in the Stack Graph, the total is kept at 100% and each trace shows the relative portion of 100% that can be attributed to the total.
In a retail application, for example, Percentage Area Graphs are a great way to look at how sales of certain product lines are changing over time compared to all the other lines in the store. Applications include any instance where you need to be able to discern trends in market share, relative costs or relative profitability.