Visualizing Patterns Over Time
Nathan Yau · 2015
This chapter looks at discrete and continuous data. The most common pattern to look for in time series data is trends. Temporal data can be categorized as discrete or continuous. In the discrete case, values are from specific points or blocks of time, and there is a finite number of possible values. The chapter also looks at chart types that help to visualize discrete temporal data, concrete examples on how to create the charts in R and Illustrator. The bar graph is one of the most common chart types. Scatterplot is a type of chart that uses points instead of bars. Continuous data represents constantly changing phenomena. A trend line can be used when there is lot of data since it can be hard to spot trends and patterns. LOESS curve moves along the data fitting a bunch of tiny curves and together forming a single curve.