Base R and most R packages come from cran.r-project.org.

• base R comes with basic data management, analysis and visualization tools
• On top of that R comes with a universe of packages (more than 11,000 on CRAN!)

Packages are after-market installations. You download them once, then call each time you need to use them.

Let's install and call the tidyverse package, which we will be using later in the seminar. This is a highly-used set of tools for data manipulation, analysis and visualization.

First, install, the packages with install.packages. Do this once. Type this into the R console and hit Enter.

install.packages("tidyverse")

You will be asked which mirror to download from. Select a location near you!

To load the package to your workspace, call it using library. Do this each session you want to use the package.

library(tidyverse)

From time to time, remember to check for updates to the packages you are running with `update.packages()'.

This is really the only time we are going to use R on its own. For the rest of the lesson, we will be working from RStudio.

• RStudio is a popular integrated development environment (IDE) that run on top of Base R.
• download for FREE at rstudio.com
• You still need to download Base R from CRAN!

When you open RStudio for the first time you will see three panes. After writing your first script, you'll see four.

These are, starting clockwise from upper-left:

credit: "R for Fledglings," Therese M. Donovan.

• Script editor
• Workspace and history pane
• R console
• Files, plots, packages and help pane

We will now walk through the various panes of RStudio which will begin the introduction to R programming.

This is where commands are submitted to R to execute.

An example… And a caveat.

Type your commands after the prompt symbol, which looks like >.

You should see a vertical, blinking bar to the right of the prompt. We will start coding here.

1. run a function
2. create or modify an object

We'll be doing the first next.

R can be used as a fancy calculator. Type this directly into the console.

1+1
## [1] 2
5*4
## [1] 20
2^3
## [1] 8

2+3*4/(5+3)*15/2^2+3*4^2
## [1] 55.625
5e4
## [1] 50000

R also allows you to test conditions of equality among values: + Equality: == (NOT = - this is important!) + Not equal: != + Greater / Less than: > or < + Greater / Less than or equal to: >= or <=

#does 5 equal 4?
5 == 4
## [1] FALSE

#is 10 less than or equal to 11?
10<=11
## [1] TRUE

#is the sqrt of 36 equal to 6 squared?
sqrt(36) != 6
## [1] FALSE

sqrt(36)
## [1] 6

You've just passed the number 36 through the sqrt function, just as you might would on a scientific calculator.

Sqrt(10)
## Error in eval(expr, envir, enclos): could not find function "Sqrt"

Remember, it's the sqrt function, NOT the Sqrt function.

Moral of the story: R is case sensitive and all-around finnicky!

Normally you would not interact directly with the Console. Instead, you will write your code into the script file and then send the code to the console for it to execute.

The script file is your long-term record of the code you ran. The console only keeps a short-term record of it.

In RStudio, choose File | New File | R Script or Ctrl+N to open a new R script.

You will see a blank document in the upper left panel of RStudio.

Type the following lines of code into your R Script.

#get the square root of 36
sqrt(36)
## [1] 6

Lines of code that are preceded by the# symbol are comments.

Comments are not executed in R. Rather, they are notes that help the coder understand and remember what the program should do.

To send code to R, place your cursor anywhere on the line, then press the Run button. You can also use Ctrl+Enter in RStudio.

#get the square root of 36
sqrt(36)
## [1] 6

Notice that after executing the line your cursor drops to the next line of code.

You can also highlight multiple lines of code at once and press Run.

#get the square root of 36
sqrt(36)
## [1] 6
#get the square root of 100
sqrt(100)
## [1] 10

To save your R script, go to File | Save or type Ctrl+S in RStudio.

The help tab in this window is useful for beginners. It returns a help file when you use help() in your command prompt:

#call the helpfile for the sqrt funtion
help(sqrt)
## starting httpd help server ... done

This tab will hold any plots you create in your R section.

We will create a plot later, but for now let's go ahead and use the help() command on plot() itself.

Each helpfile in R contains a section called Examples, and there you can copy code from the helpfile and run it in the console to see an example of the function in action.

#plot example of plot function
plot(x <- sort(rnorm(47)), type = "s", main = "plot(x, type = \"s\")")

The History Tab

On the History tab you will see a history of all the commands you have sent to R console in the session.

Now let's click on the Environment tab.

You will see that R has created an object called "x." Where did this come from? You created this when you copied and ran code from the plot function example. Objects are largely what make R, R.

Earlier we used sqrt to calculate the square root of a number. Wouldn't it be nice to save the result to use for later? Let's do that by creating an object, result. Type the following into your script:

#use sqrt function to calculate sqrt of 10 and store result in object called result
result<-sqrt(10)

You should see that the object appears in the section on the Environment tab labeled "Global Environment." A major part of your work involves creating objects.

The objects stored in the Environment and History together make up the workspace environment.

When you close R, R brings up a window that asks whether you'd like to save the workspace image (a snapshot of the current contents in the environment).

As a good practice, rarely save the workspace if the code can be quickly re-run. It is easy to accumulate an unmanageable amount of data and objects.

1. Clear the environment by clicking the "clear" button (with the broom). You can also write rm(list=ls()) in your script.
2. View the environment in your console by typing ls().
3. Remove objects in the environment by using the rm function. For exampe, rm(x) will remove x from your environment.
4. You can save individual items of the workspace with the save function. For example, save(x) will save individual objects in the workspace.

Now that you have a brief introduction to RStudio's panes let's look at the program's options where you can control settings such as font size, etc.

Go to Tools | Global Options and you'll see the following box:

• General - look but don't touch…
• Code editing - make sure the soft wrap option is selected; this will ensure that lines of code are automatically wrapped so you don't have to press return when you get to the end of a line.
• Appearance (this one is fun)- choose a color scheme that works for you.
• Pane layout - use the default layout for the duration of this primer.
• Packages - make sure "enable packages pane"" is checked. We'll cover packages in the next chapter.
• Spelling - allows a spell-check of your files.