Introduction to R

Remind students to install R and RStudio or setup access to RStudio Cloud/Server

Have students open RStudio and check to see if console “sees” R.

IDE - Integrated Development Environment
Makes developing code in R easier
It includes a number of different aspects of code development in one place
Interpreter/Console is where R is actually running
- Can work in here “interactively”
- Run a single command and see the result
- 2 + 2
- This is also where RStudio will run code written in the text dditor
Text editor
- Where we write code we want to keep and potentially reuse later
- Creates a plain text file that stores the code we’ve written
- Does a number of things to make writing clean code easier including
  - Object highlighting to makes it easier to see different things in the code
  - Automatically pairing "" and {}
  - Automatically indenting code
  - Flagging issues with code
  - Autocompleting function and variable names
- tab key autocompletes
  - Let the computer do repetitious work.
  - It’s easier and with fewer mistakes.
It provides information on the variables that currently exist and their values under Environment
And a history of the commands you’ve run under History in case you forgot to write something down
Project management
- Create, delete, and rename files & folders
- Projects to help code know where other files like data files are located

Create new folder for scripts

An online version of RStudio that runs in your browser
We are going to try using this this year for four reasons
1. Everything should work for everyone, there shouldn’t be installation issues or other complexities that come from differences between computers
2. Code is automatically shared with instructors so we can help you figure out why things aren’t working. This is the closest approximation to working side by side with you in the classroom that I’ve been able to find.
3. We can leave some of the complexities of working with R until after we’ve learned the basics
4. Works on tablets as well as computers
Folks with limited internet access, please checkout the video on working with RStudio installed on your own computer

All work for this class will be done in a class workspace
To join this space follow the link provided via Canvas and sign in using your UF email address
When you open RStudio Cloud click on the three lines in the top corner and select Data Carpentry from Spaces
Click on the appropriate week, which should say Start by it the first time you open it
This is your own copy of the assignment, which should include everything you need to both follow along with the lessons and complete the assignment
This is also where we can come look at your code to help if you get stuck
If you want to start a separate project, not for class, just click on New Project instead

2 + 2

50
50 / 1000
50 / 1000 * 2.2

To save the values we calculate for later use we use variables
A variable is a name that has a value associated with it
- Assign using <- or =

weight_g <- 50
weight_g = 50

weight_g / 1000
weight_g / 1000 * 2.2
weight_lb <- weight_g / 1000 * 2.2

weight_g
weight_g * 2
weight_g
weight_g <- 26
weight_g

# Calculate weight of Kangaroo Rat in pounds

# Problem 1

# 1.1
2 + 2

# 1.2
2 - 8

# Problem 2

width = 2
height = 3
length = 1.5
volume = width * height * length
volume

Create assignment script, put in new folder

Now we’re going to work on some exercises to get a feel for this
In class we will often only do part of an exercise and save the rest for later
I use an in-class feedback system to get a feel for when most folks are done and how well folks understand the material
When you are done with the part of the exersise we are doing for class, click on the In class feedback link and fill out the poll
Two sections
- 1-5 rating for how well you understand what we just covered
- A text box to describe anything confusing you if you can describe it
- 4 and 5’s indicate that you’re following things and we can move on
- 3’s and below suggest we need to chat more

Do Exercise 1.1-1.3 - Basic Expressions

Do Exercise 2 - Basic Variables

sqrt(weight_lb)
sqrt(0.11)

A function call is composed of two parts.
- Name of the function
- Arguments that the function requires to calculate the value it returns.
- sqrt() is the name of the function, and 0.11 is the argument.
Another function that we’ll use a lot is str()
All values and therefore all variables have types
str, short for “structure”, lets us look at them

str(weight_lb)
str(10)
str('hello world')

Functions can take multiple arguments.
- Round weight_lb to one decimal place
- Typing round() shows there are two arguments
- Number to be rounded and number of digits

round(0.11, 1)
round(weight_lb, 1)

Arguments return values, so as with other values, if we don’t save the output of a function then there is no way to access it later
It is common to forget this when dealing with functions and expect the function to have changed the value of the variable
But looking at mass_lb we see that it hasn’t been rounded

mass_lb

weight_rounded <- round(weight_lb, 1)
weight_rounded

Do Exercise 4.1-4.3 - Built-in Functions

Notes