1 / 15

R-Graphics

R-Graphics. Stephen Opiyo. Basic Graphs. One of the main reasons data analysts turn to R is for its strong graphic capabilities. R generates publication-ready figure s. "graphics" library loads by default when R is started. Ready to go as soon as R opens. Graphing basics.

xuxa
Download Presentation

R-Graphics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. R-Graphics Stephen Opiyo

  2. Basic Graphs • One of the main reasons data analysts turn to R is for its strong graphic capabilities. • R generates publication-ready figures. • "graphics" library loads by default when R is started. • Ready to go as soon as R opens.

  3. Graphing basics Plotting commands • High-level functions: Create a new plot on the graphics device • Low-level functions: Add more information to an already existing plot, such as extra points, lines, and labels

  4. Common high-level functions • plot(): A generic function that produces a type of plot that is dependent on the type of the first argument. • hist(): Creates a histogram of frequencies • barplot(): Creates a histogram of values • boxplot(): Creates a boxplot

  5. Example 1 • Download data D2_Data_1 • Open file D2_Example_1.R • R dataset mtcars

  6. Lower level graphical functions pch (plotting characters)=“” : character or numbers col (color) = “” : character or numbers lty = numbers lwd = numbers axes = “L”: L= F, T xlab =“string”, ylab=“string” sub = “string”, main =“string” xlim = c(lo,hi), ylim= c(lo,hi) cex controls the symbol size in the plot, default is cex=1,

  7. Lower level graphical functions plot typedescription: type= " " p= points l = lines o= over plotted points and lines b, c= points (empty if "c") joined by lines s= stair steps h= histogram-like vertical lines n = does not produce any points or lines

  8. Lower-level graphing functions • pch=0,square • pch=1,circle • pch=2,triangle point up • pch=3,plus • pch=4,cross • pch=5,diamond • pch=6,triangle point down • pch=7,square cross • pch=8,star • pch=9,diamond plus • pch=10,circle plus • pch=11,triangles up and down • pch=12,square plus • pch=13,circle cross • pch=14,square and triangle down • pch=15, filled square blue • pch=16, filled circle blue • pch=17, filled triangle point up blue • pch=18, filled diamond blue • pch=19,solid circle blue • pch=20,bullet (smaller circle) • pch=21, filled circle red • pch=22, filled square red • pch=23, filled diamond red • pch=24, filled triangle point up red • pch=25, triangle point down red

  9. Lower-level graphing functions Symbol shapes and colors

  10. Lower-level graphing functions • Adding text text() text(x,y, “text”, options) points() add some more points to the graph points(x,y, options) Saving graphs in Rstudio

  11. Example 2 • Download data D2_Data_2 • Open file D2_Example_2.R

  12. Making a histogram • Make histograms with varying the number of bars (also called ‘bins’ or ‘cells’), e.g. simdata <-rchisq(100,8) hist(simdata) # default number of bins Setting your own breakpoints bps <- c(0,2,4,6,8,10,15,25) hist(simdata,breaks=bps)

  13. 3-dimensional Scatterplots • Need a package scatterplot3d • Install package scatterplot3d using install.packages("scatterplot3d") command • Alternatively install using Rstudio using Packages

  14. Multiple graph on one page • Combining multiple plots using par () and mfrow = c(nrows, ncols) to create a matrix of nrows by ncols • ?par • par(mfrow=c(1,2))

  15. Exercise par(mfrow=c(3,5)) plot(D2_Data_2[,2], D2_Data_2[,3], type="p", pch=1, col="1", xlab ="Peak1", ylab ="Peak2", main="Plot of Peak1 vs Peak2", font.main =1) Replace pch=1 and col =1 with 2 to 15: Export the graph and save it as Day_2_Graph.pdf

More Related