There are a number of reasons for why we visually represent the data. At the data exploration stage, we can gain an immediate understanding of data properties. Visual representation serves to highlight patterns in data and suggest modeling strategies. Exploratory graphs are usually made quickly and in large numbers. We are not so much concerned with aesthetic or stylistic issues, but we simply want to see what the data looks like.
Beyond using graphs to explore data, they are a primary means of communicating information about our data. Visual representation helps clarify data properties and stimulate viewer engagement. The human visual system is the highest bandwidth channel to the brain, and visualization is the most efficient way to present a large amount of information. By creating a visualization, we can immediately get a sense of important parameters, such as the maximum, minimum, and trends that may be present in the data. Of course, this information can be extracted...
