In my previous post, I have demonstrated how easy it is to create a bar graph in SQL Server 2017 In-Database Machine Learning using R.
We’re going to build upon that basic graph.
Sometimes doing data analysis would require us to look at an overview of our data across specific partitions, say a year. For example, we want to see how our product groups fare on month-to-month basis across the last 4 years.
In a data analytics perspective, there are quite a handful of data points in this requirement – data aggregate (quantity), monthly periods, and year partitions.
One of the approaches to handle such requirement is by using a
facet. Faceting is a way of plotting subsets of data into a matrix of panels based on one or more variables – or facets.
Click through for the example and code. Facets are quite useful, but they run the risk of misleading if you squeeze too many onto the screen. The same line can look quite different with a “tall” facet versus a “wide” facet, and that can change how people interpret your visual.