R Programming By Example

Pricing and profitability by protein source and continent

As usual, we start developing our graph function. We receive as parameters the data, and the variables for the x axis (x) and y axis (y), and, in this case, we anticipate four cases that correspond to the combinations of including or not the color and shape variables for the graph. We do the standard checking and create the corresponding graph base. Here comes the different part, we call the ggMarginal() function of the ggExtra package with the graph object we want (in this case, the base graph plus the points layer), and specify the type of graph to be used for the marginal distributions. You can chose from density, histogram, and boxplot. We choose histogram:

graph_marginal_distributions ...