R Cheat Sheet with Basic Commands, Functions and Plot, Cheat Sheet of Advanced Computer Programming

Download R Cheat Sheet with Basic Commands, Functions and Plot and more Cheat Sheet Advanced Computer Programming in PDF only on Docsity! CCR Summer 2013 R – Reference Sheet Eric Pitman Annual Summer Workshop in Computational Science Author: C. Ryan Mraz NAME: _____________________________ R – Reference Sheet ---------------------------------------------------------------------RStudio Tips-------------------------------------------------------------------  There is no editor window until you open up a file! To do so, click:  To see your history (commands you have already issued), click the history pane or simply click the up arrow on your keyboard while on the command line  To change the relative sizes of each window, hover the mouse over the window border until appears.  Is your project loaded? Check the upper right Corner:  There are two ways to load csv files in Rstudio: 1) In the RStudio Workspace: Select Import Dataset: From Text File Select a .csv file to Open Use Heading=Yes 2) From the command line: Set the Working Directory Load command: > drop=read.csv(“drop.csv”) *Keep Your Projects Tidy!!  To clear the Console window, use: ctrl + L  To clear individual items in the Workspace, use: r m(variable_name)  To clear all items in the Workspace or plotspace, use: Here: Then Here: R – Reference Sheet example histogram: data(Cars, package=”MASS”) hist( Cars93$RPM, breaks = 4, xlab="RPM", main="histogram of engine RPM", col="red" ) example density plot: data(Cars, package=”MASS”) plot( density(Cars93$RPM,bw=200), main="Density Curve of Engine RPMs of 93 Cars", xlab="RPM", col="blue" ) example boxplot: boxplot(formula=mpg~gear, data=mtcars, main="Mileage by Gear Number", xlab="Number of Gears", ylab="Miles Per Gallon", col=c("red","green","blue") ) R – Reference Sheet example ROC Curve: library(pROC) plot.roc( roc(exp$human_crystal, exp$class3_crystal), ylab="Sensitivity (True Positive Rate)", xlab="Specificity (1 - False Positive Rate)", print.auc = TRUE, print.auc.col="red", main='Generation 8 ROC curve: 13 proteins, 2 time points each', print.thres=TRUE, print.thres.col="blue", grid=TRUE ) #------------------------------------------------------------Common Graph Modifiers------------------------------------------------------- abline(lm(y~x)) # prints linear regression line on graph pch=# # Chooses the type of point character to plot cex = # # Magnifies text or labels on a graph/chart [smaller<(default=1)<larger] par(mfrow=c(rows,collumns)) # Prints multiple graphs/charts on one sheet par(mar=c(#,#,#,#)) # Changes margins’ sizes starting at bottom legend(x="location", # location of legend title = "---", c("Label.1","Label.2",etc.), # separation labels fill = c("Color.1","Color.2",etc.) ) *N.B. There are practically endless possibilities for making graphs and plots pretty!! Play around and find out how!! R – Reference Sheet #--------------------------------------------------------------Apply Family--------------------------------------------------------- # There are many types of the function apply, but for our purposes, we will only be using sapply. sapply The apply() family of functions can be used to call some other function multiple times on a dataset, with several different arguments. sapply() returns a vector or matrix result. You can use sapply() on a native R function, or on a function you wrote yourself. EXAMPLE: > u=c(33,45,37,50) # Creating Vector u > v=c(2,5,8,11) # Creating Vector v > d=data.frame(u=u,v=v) # Creating Data frame d from Vectors u and v > > d # This is what our data frame looks like: u v # 4 rows of 2 columns 1 33 2 2 45 5 3 37 8 4 50 11 > > > sapply( d, mean) # Here, we apply the mean function to our data frame # using sapply u v # sapply applies the mean function to each column of 41.25 6.50 # the data frame and outputs each answer in a user- # friendly format