Spatial Ecology Lab 2: Data Analysis with R

Transcription

1 Spatial Ecology Lab 2: Data Analysis with R Damian Maddalena Spring Introduction This lab will get your started with basic data analysis in R. We will load a dataset, do some very basic data manipulations, and create and output plot. This week, you will turn in your complete R script. To grade it, I will run it and check your output. (See Section 7 below.) 2 Formatting of This Document R is designed for interactive use at the command line or batch execution of a script file that contains a series of commands. While working with this document, you will see R code nested inside delineated blue boxes. Some code starts with a > before it, indicating that this code should be executed at the command prompt, line by line in interactive mode. The second type of box you will see does not contain this symbol. This indicates that this is complete code that should be executed as an R script file in batch mode. 3 GUI Code Editors You do not need anything beyond the standard R interface to do your work, but many people prefer coding inside an integrated development environment (IDE). IDEs generally provide GUI tools, coding hints, and tools for debugging. You can see two examples here: In this class, I am keeping things basic by teaching the language and methods outside of an IDE. You are welcome to explore the IDEs available and use one if that helps you. 1

2 4 Getting Help 4.1 On the Internet Google: there were many other people before you that are having the same problem you are having! You might come across answers on one of the following: Stack Exchange: - a message board for programming questions. Quick-R: - A great resource full of simple, working examples for many common analysis tasks (Not much specific to spacial, but a GREAT resource). The Comprehensize R Network (CRAN): R listservs: For example: R-help: The main R mailing list R-sig-ecology: Using R in ecological data analysis R-sig-Geo: R Special Interest Group on using Geographical data and Mapping 4.2 Inside of R While inside of an R session, you can get help using several available commands. #in this example we are asking for help about the read. table () command, which is used to read in data >?read.table #you can also use this version > help(read.table) Both of these commands will print out the documentation for the command you query. What if you didn t remember what you were looking for. Again, an Internet search is valuable here, but you can start by searching within R. > help.search("data.input") You can get help on a particular package like so: > library(help=spatial) Or you can find the packages that contain a a particular function using the find command. > find("paste") 2

3 5 File Organization For these labs, it is assumed that you are working on your TIMMY workspace. When I check your code, I will look for a directory structure that is similar to.../timmy/spatialecology/lab2/. Inside that workspace I will assume.../code,.../data, and.../output. Defining your workspace as a variable #define your workspace as a variable so that it only has to be changed once if you want to change the output location > outputdir < "c:/users/maddalenad/spatialecolog/lab2" Now, you can use your workspace variable by appending the output file name using the file.path() command. #create the output file name > outputfile < file.path(outputdir,"mycoolplot.png") 6 Procedures To begin, let s look at how R manages packages (libraries), which are collections of commands you can import to amend R s basic functionality. 6.1 Managing Packages Loading a library into R. #attempt to load the psych package. > library(psych) What happened? The package might need to be installed. We will do so using the install.packages() command. Installing additional packages not included in the base install: #install the psych package > install.packages("psych") # load the psych package. > library(psych) 3

4 6.2 Managing Your Workspace (Session) Variables in R are case sensitive, temp is not the same variable as Temp or TEMP. Variables cannot contain spaces and should not begin with numbers or symbols. > temp < 62 > depth < 124 List variables you have created: > objects() You can remove variables you created using rm(variablename). #remove the variable temp created above. > rm(depth) 6.3 Reading in Data from a Local File You can read data from a local file using the read.table command. R can read many data formats, but we will work with a.csv file here. #note the use of header = TRUE to tell R that we have column names in the first row. #note the use of sep= to tell R what character we use to delineate columns. # note the / instead of \ on Windows systems df < read.table("c:/users/maddalenad/trees.csv", header=true, sep=",") 6.4 Working with Data R has many built in functions that allow you to understand your data set. We will look at three very simple procedures: #get the min of the DBH variable for the whole dataset > min(df$height) #get the max of the DBH variable for the whole dataset > max(df$height) #find the range of the DBH variable for the whole dataset > range(df$height) There are many packages that will get you basic descriptive statistics with bundled commands. For example: 4

5 #using the psych package > library(psych) > describe(df$height) 6.5 Creating Plots # Creating a Graph #note the main parameter. It controls the main title of the output plot. plot(df$dbh,df$height,main="trees") #add a trend line abline(lm(df$height df$dbh)) #you can clear the current plot and strat fresh with > plot.new() #you can close the current graphics device with > dev.off() You can send a plot to an output file by starting the png monitor and setting it as the target for your plot. #start up the png monitor > png("c:/users/maddalenad/treesplot.png") #plot your data > plot(df$dbh,df$height,main="trees") #close the png plot > dev.off() 6.6 Putting it all Together After going through each of the command above, create an executable.r script file that does the following: #set the workspace as a variable to be use in the code below #open the data file #print the number of records in the data frame #print the names of the data frame #print min, max and range for DBH #print the output of the describe command for DBH 5

6 #create a plot of DBH and height with a title of [Yourname] s Trees Plot. Find the command to change the names of the X and Y axes to simplify them. Save that plot to your workspace in the.../ output subdirectory. Your file should be executable at the command prompt using the source command. (See R help for details.) 7 Submission Submit your.r script file via Blackboard. Only submit the.r file. References [Crawley(2012)] Michael J Crawley. The R book. John Wiley & Sons, [Plant(2012)] Richard E Plant. Spatial data analysis in ecology and agriculture using R. CRC Press,