Learning objectives
- Gain familiarity the RStudio IDE
- Manage your workspace in an interactive R session
- Understand variable assignment
- Use load() to import a data set
- Take a look at a data frame
- Add columns, subset, and summarize a data frame
- To be able to seek help via
?
and Google
Challenge 1 – Make a new directory and project for DIBSI Day 2
- In your project directory, either using the Project tab of RStudio or your OS’ file system, create the following directories:
- data
- scripts
- results
- Create a new .R script file in the scripts/ folder calling it whatever you like
MCQ – Variable Assignment
What does the following code print?
a <- 1 b <- 2 c <- a + b b <- 4 a <- b c <- a c
Option 1) a Option 2) 3 Option 3) 4 Option 4) ::nothing::
Challenge 2 – Extra practice: Assignment & Comparison
Which elephant weighs more? Convert one’s weight to the units of the other, and store the result in an appropriately-named new variable. Write a command to test whether elephant1 weights more than elephant2 (1 kg ≈ 2.2 lb).
elephant1_kg <- 3492 elephant2_lb <- 7757
MCQ – Subset and vectorize
Load the continents data frame again. Make a copy from your day 1 project folder, and move it to the data folder you just created for day 2.
What is the total land area of continents that have at least 10% of the world’s population?
- Use subsetting to get the areas you want
- Use the
sum()
function to find the total land areaOption 1) 149428500 Option 2) 126700000 Option 3) 22728500 Option 4) 100
For a brief note on data types in R, we turn to the Data Carpentry: R for data analysis and visualization of Ecological Data Introduction to R materials.
This lesson is adapted from the Software Carpentry: R for Reproducible Scientific Analysis Vectors and Data Frames materials and the Data Carpentry: R for data analysis and visualization of Ecological Data Introduction to R materials.