Hp <- cut(hp,3) # divide horse power into three bands Additionally, you can write functions that modify the rendering of panels. It is frequently easiest to set these options within the high level plotting functions described above. To view the options that can be changed, look at help(xyplot). Unlike base R graphs, lattice graphs are not effected by many of the options set in the par( ) function. The difference between graphs 2 & 3 is the use of the layout option to contol the placement of panels. Note, as in graph 1, that you specifying a conditioning variable is optional. Main='Dotplot Plot by Number of Gears and Cylinders', # dotplot for each combination of two factors Ylab='Miles per Gallon', xlab='Car Weight') Main='Scatterplots by Cylinders and Gears',

# scatterplots for each combination of two factors Ylab='Cylinders', xlab='Miles per Gallon', # boxplots for each combination of two factors Main='Density Plot by Numer of Cylinders', # kernel density plots by factor level (alternate layout) Main='Density Plot by Number of Cylinders', They use the car data (mileage, weight, number of gears, number of cylinders, etc.) from the mtcars data frame. ~x means display numeric variable x alone. y~x | A*B means display the relationship between numeric variables y and x separately for every combination of factor A and B levels. For example ~x|A means display numeric variable x for each level of factor A. formula specifies the variable(s) to display and any conditioning variables. Where graph_type is selected from the listed below. In particular, the package supports the creation of trellis graphs - graphs that display a variable or the relationship between variables, conditioned on one or more other variables. The lattice package, written by Deepayan Sarkar, attempts to improve on base R graphics by providing better defaults and the ability to easily display multivariate relationships.

Graph r package