Introduction to class resources and data structures in R

This is here for ease of reference; you should complete your assignment using your individual GitHub Classroom repositories

Your assignment

The goal for this assignment is to ensure that you:

• have access to our Rstudio server and shared data folder

• can access the assignments in Github Classroom

• are able to determine what data structure you’re working with and what data types are contained with the object

• can succesfully knit an Rmarkdown document to html

Step 1: Load your packages

In general, I do this in one code chunk at the beginning of the Rmarkdown document so that users know exactly what packages they’ll need and can make decisions about if/how they want to install them.

library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

## ✓ ggplot2 3.3.5     ✓ purrr   0.3.4
## ✓ tibble  3.1.3     ✓ dplyr   1.0.7
## ✓ tidyr   1.1.3     ✓ stringr 1.4.0
## ✓ readr   2.0.0     ✓ forcats 0.5.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

Step 2: Load the data

For the next few weeks, we’ll be using data from the High Country News Land Grab University project. These data depict the role of expropriated Indigenous land in funding the fifty-two land-grant universities in the United States. They contain information on nearly 11 million acres of Indigenous land tanke from ~250 tribes, bands and communities through a multitude of treaties and violent land seizures. Check it out as it will help you understand what these data are depicting.

csv.list <- list.files('/opt/data/session02/CSVs/', pattern = "*.csv", full.names = TRUE)
data <- lapply(csv.list, function (x) read.csv(x))

• Question 1: what is lapply doing in the statement above?

• Question 2: what type of data is contained in the 3 column of the 2nd element of the data object? (show the code you used to figure it out by inserting a code chunk)?

• Question 3: what happens if you run the above code with the the read_csv function from the tidyverse package?

• Question 4: Use the first element of the data object to determine the total amount paid for the land depicted in that object (HINT: you’ll need to coerce the data into a different format)

Remember - edit this document and knit to .html within your GitHub Classroom repo and commit and push those changes