Line plots

Line plots, as we have already seen in the preceding examples, are very effective when it comes to exploratory data analytics. They can be used both to understand correlations and look at data trends. So, by further making use of aesthetics, we can make them more interesting and informative.

Getting ready

We will use the Gadfly library, which we have used in the preceding recipes. So, to install the library, you can follow the installation steps mentioned in the previous recipes.

How to do it...

1. Let's start with a basic line plot, which plots their incidences of melanoma in the respective years. So, this plot can be seen as a typical time series plot, where the x axis is a time variable and the y axis is the variable that is parameterized by time. So, to plot this, we simply need to include the dataset in the plot() function and include the Geom.line aesthetic, as follows:

   plot(dataset("Lattice", "melanoma"), x = "Year", y = "Incidence", Geom.line)
   

   

2. We can also have multiple line...