Learning R hands on

1. Learning R hands on

2. Organization of Folders: • Class Data folder has datasets (end in .csvor .rda) • Rcode has the scripts of R commands that can cut and pasted into an R window (end in .R) • Ppt has the powerpoints

3. The Basics Rintro.R • Reading in comma separated data • Listing a data set or its components • Subscripts • Sequences and combing values (: and “c”) • Creating a new data set with <- • Arithmetic in R • Applying some stats to data • Saving your work

4. Fooling with the data RintroManipulating.R • Subscripting to get a subset of data • Working with rows and columns • Arithmetic on a column at once Pay attention to where the commas are! e.g. BT2[3,5] BT2[3,] BT2[,5] BT2[,3:5] or BT2[1:10,3:5] These are all different!

5. Plotting DataRintroPlotting.R • Histogram hist • Adding more features to the plot • Scatterplots using plot • Box plots for several data sets boxplot • Adding text to a scatter plot • Changing the axes scales Build a complicated plot by adding features through several simple steps

6. Writing functionsRintroFunctions.R • The uses for { } and ( ) • What goes in and what comes out • Listing a function • Optional arguments • Calling a function and assigning its results to a new data set • Review of R arithmetic

7. More on R programmingRintroProgramming.R • Changing the data type • Looping the for block • if statements and logicals • lists • The apply function

8. Best Practices in coding • Use informative names for important variables • Comment steps that are not obvious • Break R expressions into several steps for clarity • Many smaller and simple functions are good– avoid functions more than about 50 lines. • Simple is good – overly clever is a good way to introduce bugs! • Add default values and test that will prevent data analysis errors.

9. The interquartile range function # finds the interquartile range of a vector MyIQR<- function( y,na.rm=FALSE){ if( !is.vector(y) ){ stop(‘data is not a vector’)} # omits NAs if na.rm is TRUE Q25<- quantile( y, .25, na.rm=na.rm) Q75<- quantile( y, .75, na.rm=na.rm) IQR<- Q75 – Q25 return(IQR) }