In this chapter, we introduce basic graphs, plots, and charts used to visualize data. The process of visualization enables an analyst to graphically examine the data under review. This is more intuitive, and often facilitates the rapid identification of anomalies in the data that can be hard to extract from the raw data.

Several visual representations were examined, including line charts, a variety of bar charts, pie charts, scatterplots, histograms, donut charts, and bubble charts. Each of these graphical depictions of data provides a different perspective of the data being analyzed. The most appropriate technique depends on the nature of the data being used. While we have not covered all of the possible graphical techniques, this sample provides a good overview of what is available.

We were also concerned with how Java is used to draw these graphics. Many of the examples used JavaFX. This is a readily available tool that is bundled with Java SE. However, there are several other libraries available. We used GRAL to illustrate how to generate some graphs.

With the overview of visualization techniques, we are ready to move on to other topics, where visualization will be used to better convey the essence of data science techniques. In the next chapter, we will introduce basic statistical processes, including linear regression, and we will use the techniques introduced in this chapter.