Presentation: Plotting Systems in R
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The document provides an overview of plotting systems in R, including base, lattice, and ggplot2, explaining how to create and save plots using various functions. It details the various graphic devices, plotting functions, and layered approaches in ggplot2 for visualizing data, with examples using the 'mtcars' dataset. Additionally, it includes resources for further learning about R graphics.
![Example
attach(mtcars)
head(mtcars[, c("hp", "mpg")])
plot(hp, mpg)](https://image.slidesharecdn.com/presentation-151117051541-lva1-app6892/85/Presentation-Plotting-Systems-in-R-5-320.jpg)
![Example
attach(mtcars)
head(mtcars[, c("hp", "mpg")])
plot(hp, mpg)
title("MPG vs. hp”) # Add a title](https://image.slidesharecdn.com/presentation-151117051541-lva1-app6892/85/Presentation-Plotting-Systems-in-R-6-320.jpg)
Presentation: Plotting Systems in R
- 1. Plotting systems in R Ilya Zhbannikov
- 2. Graphics Devices in R • Screen device • File device (pdf, png, jpeg, etc.) Graphics device: a place to make plot appear
- 3. How does a plot get created? • Call a plotting function, i.e. plot(), xyplot(), qplot() • The plot appears on a screen device • Annotate plot, if necessary • Save it to file, for example.
- 4. Screen and file devices • How the plot will be used? • Use screen device for quick visualisation or exploratory studies. • Plotting functions (plot(), qplot(), xyplot()) send output to the screen device by default. • If the plot will be printed, use file device instead.
- 6. Example attach(mtcars) head(mtcars[, c("hp", "mpg")]) plot(hp, mpg) title("MPG vs. hp”) # Add a title
- 7. Available plotting systems • Base • lattice • ggplot2
- 8. Base plotting system • Installed by default • Quickest way to visualise your data • Plot can be further updated using additional options
- 10. Extended example plot(disp,mpg, main = "MPG vs. HP", # Add a title type = "p", col = "grey", # Change the color of the points pch = 16, # Change the plotting symbol see help(points) cex = 1, # Change size of plotting symbol xlab = “Horse power", # Add a label on the x-axis ylab = "Miles per Gallon", # Add a label on the y-axis bty = "n", # Remove the box around the plot #asp = 1, # Change the y/x aspect ratio see help(plot) font.axis = 1, # Change axis font to bold italic col.axis = "black", # Set the color of the axis xlim = c(20,500), # Set limits on x axis ylim = c(5,50), # Set limits on y axis las=1) # Make axis labels parallel to x-axis
- 11. Extended example
- 12. More examples
- 14. • Multivariate data • Uses formulas • Single function call The Lattice Plotting System
- 15. The Lattice Plotting System • lattice: code for producing Trellis graphics, includes functions like xyplot(), bwplot(), levelplot() • Grid: implements a different graphics system and the lattice package are on top of it
- 16. Main plot functions • xyplot(): scatterplots • bwplot(): boxplots • histogram(): histograms • stripplot(): a boxplot points • dotplot(): plot dots on "violin strings" • splom(): scatterplot matrix • levelplot(), contourplot(): for "image" data
- 17. Example library(lattice) attach(mtcars) xyplot(mpg ~ hp, data = mtcars)
- 18. Extended example
- 19. More examples • See lattice_example_1.R
- 20. ggplot2 Plotting System • “Grammar of Graphics” by Leland Wilkinson, written by Hadley Wickham • Data must be a data frame • Uses grammar • Web site: http://ggplot2.org
- 21. What is "Grammar of Graphics"? "In brief, the grammar tells us that a statistical graphic is a mapping from data to aesthetic attributes (colour, shape, size) of geometric objects (points, lines, bars). The plot may also contain statistical transformations of the data and is drawn on a specific coordinate system”- ggplot2 book
- 22. qplot() and ggplot() • qplot() - works like plot() function in base plotting system data • should represent a data frame • aesthetic (size, colour, shape) and geoms (points, lines) • core of ggplot()
- 23. qplot • qplot() - works like plot() function in base plotting system data • Should represent a data frame • aesthetic (size, colour) and geoms (points, lines) • Core of ggplot()
- 24. Example library(ggplot2) attach(mtcars) head(mtcars) # Simple plot: qplot(data=mtcars,x=hp, y=mpg,main="MPG vs. hp")
- 26. Example # Boxplots: qplot(data=mtcars,x=factor(cyl), y=mpg,geom="boxplot", main="MPG vs. # of Cylinders")
- 27. Components of ggplot() • A data frame • aesthetic mapping (how data are mapped to colour and size) • geoms (points, shapes, lines) • facets • stats (binning, smoothing, quantiles) • scales (for aesthetic mapping, i.e. male=‘red’, female=‘blue’) • coordinate system Peng at al, Explanatory Data Analysis, Coursera online class
- 28. Steps to plot with ggplot() • Plots are build up in layers • Plot the data • Overlay a summary • Add metadata and annotation Peng at al, Explanatory Data Analysis, Coursera online class
- 29. Peng at al, Explanatory Data Analysis, Coursera online class
- 30. Peng at al, Explanatory Data Analysis, Coursera online class Example # Basic: ggplot(mtcars, aes(hp, mpg)) + geom_point()
- 31. Peng at al, Explanatory Data Analysis, Coursera online class Example # With color: ggplot(mtcars, aes(hp, mpg)) + geom_point(aes(color = cyl))
- 32. Peng at al, Explanatory Data Analysis, Coursera online class Example # Boxplots: ggplot(data=mtcars, aes(hp, mpg)) + geom_boxplot(aes(as.factor(cyl)))
- 33. Peng at al, Explanatory Data Analysis, Coursera online class Example # Faceting mtcars$cyl <- factor(mtcars$cyl) ggplot(data=mtcars, aes(hp, mpg)) + geom_point() + facet_grid(~ cyl)
- 34. Peng at al, Explanatory Data Analysis, Coursera online class Example # Faceting mtcars$cyl <- factor(mtcars$cyl) ggplot(data=mtcars, aes(hp, mpg)) + geom_point() + facet_grid(~ cyl)
- 35. Peng at al, Explanatory Data Analysis, Coursera online class Example ggplot(data=mtcars, aes(hp, mpg)) + geom_point() + facet_grid(~ cyl) + geom_smooth(colour = "blue", size = 1, method=lm)
- 36. Resources • http://www.r-bloggers.com • http://revolutionanalytics.com • http://www.statmethods.net (Quick-R) • Coursera (Data Science Specialisation)