Assignment 1

In this assignment, you will read in a file, practice some basic data manipulation, and make a graph. You will be performing all your work within an R Markdown document for this assignment. You will be working with North Carolina countywide population projections provided by the North Carolina Office of State Budget and Management (https://www.osbm.nc.gov/facts-figures/population-demographics/state-demographer/countystate-population-projections/population-overview). Make sure each line of code has a descriptive comment.

Download the Data Here

Create a new R Markdown document

  1. If RStudio is open, close it and do not save your environment. Open RStudio and make sure that your environment is empty, then choose File | New File | R Markdown. Note: to clear your Environment, find the button that looks like a broom in the Environment tab!

    In the popup window, enter “Assignment #1” for the title and for author, enter your name. Make sure that the type (on the left) is Document and the Default Output Format is HTML.

    Note that the new R Markdown document should have populated the “header” section to include the information you entered. For example, mine looks like this:

---
title: "Assignment #1"
author: "Julia Cardwell"
date: "5/1/2023"
output: html_document
---
  1. Save your .RMD file using the following naming convention:
  • Lastname_GEOG215_Assg1.Rmd
  • For example, Julia’s file would be: Cardwell_GEOG215_Assg1.Rmd

Read in and Summarize the Data

  1. Add a code chunk at the top of your .Rmd. Load the tidyverse library

  2. Add a third-level heading to your R Markdown file named, “Read in Data”. Below this heading, add a code chunk. In the chunk, use a relative file path to read in (using the read_csv() command) the file named “nc_population_projections.csv” and assign it to an object called nc_pop.

  3. Under the code chunk you just created, insert a third-level heading to your R Markdown file named, “Data Preparation and Summary”. Create an object called nc_pop_simplified that only contains the following variables: pop_2010, pop_2020, pop_2030, pop_2040, pop_2050.

  4. Using in-line code, write a sentence (in plain text underneath the code chunk) that describes the number of rows and the number of columns in nc_pop_simplified. You must use a command to complete this task, not simply write the correct answer.

Create a Plot

  1. Under the code chunk you last created, insert a third-level heading to your R Markdown file named “Plot”.

  2. Write a command to create a histogram of all county values in the pop_2050 column.

Calculate State-Level Values

After examining the dataset, you have probably noticed that each row represents a county in North Carolina. It is often useful to examine the “study region” as a whole (in this case, the full state). We will now aggregate the county-level data to the state-level.

  1. Under the code chunk you last created, insert a third-level heading to your R Markdown file named “Aggregating data”

  2. Write a command that creates a new object called state_summary that gets the sum of each column except County.

  3. Add a new column to the state_summary object called overall_change. Use the mutate() command to fill this column with the statewide population change from 2010-2050

  4. In plain text below the code chunk, explain why we would get an error if we try to take the sum of the County variable. In that same plain text, add in-line code that prints the statewide population change from 2010-2050.

Deliverables

Upload your .Rmd and .html files to Canvas.