**Quantum Forest » rblogs**, and kindly contributed to R-bloggers)

This is simple example code to display side-by-side lattice plots or ggplot2 plots, using the `mtcars`

dataset that comes with any R installation. We will display a scatterplot of miles per US gallon (mpg) on car weight (wt) next to another scatterplot of the same data, but using different colors by number of engine cylinders (cyl, treated as factor) and adding a smooth line (under the `type`

option).

library(lattice) data(mtcars) # Create first plot and assign it to variable p1 = xyplot(mpg ~ wt, data = mtcars, xlab = 'Car weight', ylab = 'Mileage') # Create second plot and assign it to variable p2 = xyplot(mpg ~ wt, group= factor(cyl), data = mtcars, xlab = 'Car weight', ylab = 'Miles/gallon', type=c('p', 'smooth')) # print calls print.lattice, which takes a position # argument. print(p1, position = c(0, 0, 0.5, 1), more = TRUE) print(p2, position = c(0.5, 0, 1, 1))

According to the documentation, **position** *is a vector of 4 numbers, typically c(xmin, ymin, xmax, ymax) that give the lower-left and upper-right corners of a rectangle in which the Trellis plot of x is to be positioned. The coordinate system for this rectangle is [0-1] in both the x and y directions*. That is, the first `print()`

sets position to occupy the left part of the graph with full height, as well as to avoid refreshing the graph when displaying the new plot (`more = TRUE`

). The second `print()`

uses the right part of the graph with full height.

In the case of ggplot2, the code is not that different:

library(ggplot2) # Create first plot and assign it to variable p1 = qplot(wt, mpg, data = mtcars, xlab = 'Car weight', ylab = 'Mileage') # Create second plot and assign it to variable p2 = qplot(wt, mpg, color = factor(cyl), data = mtcars, geom = c('point', 'smooth'), xlab = 'Car weight', ylab = 'Mileage') # Define grid layout to locate plots and print each graph pushViewport(viewport(layout = grid.layout(1, 2))) print(p1, vp = viewport(layout.pos.row = 1, layout.pos.col = 1)) print(p2, vp = viewport(layout.pos.row = 1, layout.pos.col = 2))

More details on ggplot’s notation can be found here.

**leave a comment**for the author, please follow the link and comment on their blog:

**Quantum Forest » rblogs**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...