Chaining transformations into a visualization pipeline

Now that we’ve worked out how to add a single transformation to a set of query data frames, let’s take it one step further and chain together a series of transformations to create a visualization pipeline. This example might seem a bit trivial, but it illustrates how to work through the process of manipulating tables via transformations to produce a result that facilitates a specific visualization.

In this case, we are going to take some of our weather data and make transformations to the query result, a use case that resembles a situation where you might not have the data in the format you want.

From there, we will do some transformations that will produce a dataset suitable for the time series visualization. The results will be along the lines of what we accomplished in the previous chapter, but the idea here is to get the results by transformation rather than by modifying the query. Remember, there may be...