Assignment 6

Author

Garrett DeVoe

Go to the shared posit.cloud workspace for this class and open the assign06 project. Open the assign06.qmd file and complete the exercises.

This is a very open-ended assignment. There are three musts:

  1. You must use the tidycensus package to get either decennial or ACS data from the US Census Bureau.

  2. You must get data for two different variables and they can’t be population or median home values.

  3. You must show all the code you used to get the data and create the table or chart.

You can then either create a cool table or chart comparing the two variables. They can be from any region and for any geography…it doesn’t necessarily need to be Maine.

Note: you will receive deductions for not using tidyverse syntax in this assignment. That includes the use of filter, mutate, and the up-to-date pipe operator |>.

The Grading Rubric is available at the end of this document.

We’ll preload the following potentially useful packages

library(tidyverse)
library(tidycensus)
library(gapminder)
library(gt)
library(gtExtras)
library(scales)

This is your work area. Add as many code cells as you need.

maine_occupied_2020 <- get_decennial(
  geography = "county",
  state = "Maine",
  year = 2020,
  variables = "H1_002N", 
  sumfile = "pl"
)
Getting data from the 2020 decennial Census
Warning: • You have not set a Census API key. Users without a key are limited to 500
queries per day and may experience performance limitations.
ℹ For best results, get a Census API key at
http://api.census.gov/data/key_signup.html and then supply the key to the
`census_api_key()` function to use it throughout your tidycensus session.
This warning is displayed once per session.
Using the PL 94-171 Redistricting Data Summary File
Note: 2020 decennial Census data use differential privacy, a technique that
introduces errors into data to preserve respondent confidentiality.
ℹ Small counts should be interpreted with caution.
ℹ See https://www.census.gov/library/fact-sheets/2021/protecting-the-confidentiality-of-the-2020-census-redistricting-data.html for additional guidance.
This message is displayed once per session.
maine_vacant_2020 <- get_decennial(
  geography = "county",
  state = "Maine",
  year = 2020,
  variables = "H1_003N", 
  sumfile = "pl"
)
Getting data from the 2020 decennial Census
Using the PL 94-171 Redistricting Data Summary File
maine_unit_occupancy_2020 <- maine_occupied_2020 |>
  union(maine_vacant_2020)

maine_unit_occupancy_2020 <- maine_unit_occupancy_2020 |>
  mutate(variable = replace(variable, variable == "H1_002N", "Occupied")) |>
  mutate(variable = replace(variable, variable == "H1_003N", "Vacant"))

maine_unit_occupancy_2020 |>
  gt()
GEOID NAME variable value
23001 Androscoggin County, Maine Occupied 45393
23003 Aroostook County, Maine Occupied 29784
23007 Franklin County, Maine Occupied 12842
23009 Hancock County, Maine Occupied 24948
23013 Knox County, Maine Occupied 17883
23015 Lincoln County, Maine Occupied 15803
23019 Penobscot County, Maine Occupied 64250
23021 Piscataquis County, Maine Occupied 7615
23025 Somerset County, Maine Occupied 21924
23029 Washington County, Maine Occupied 13757
23031 York County, Maine Occupied 88924
23005 Cumberland County, Maine Occupied 128100
23011 Kennebec County, Maine Occupied 53223
23017 Oxford County, Maine Occupied 24712
23023 Sagadahoc County, Maine Occupied 16136
23027 Waldo County, Maine Occupied 17143
23001 Androscoggin County, Maine Vacant 4444
23003 Aroostook County, Maine Vacant 8519
23007 Franklin County, Maine Vacant 8014
23009 Hancock County, Maine Vacant 15185
23013 Knox County, Maine Vacant 6372
23015 Lincoln County, Maine Vacant 7805
23019 Penobscot County, Maine Vacant 10628
23021 Piscataquis County, Maine Vacant 6962
23025 Somerset County, Maine Vacant 7861
23029 Washington County, Maine Vacant 7837
23031 York County, Maine Vacant 23274
23005 Cumberland County, Maine Vacant 21352
23011 Kennebec County, Maine Vacant 9384
23017 Oxford County, Maine Vacant 11418
23023 Sagadahoc County, Maine Vacant 2802
23027 Waldo County, Maine Vacant 4778 
maine_unit_occupancy_2020 |>
  mutate(NAME = str_remove(NAME, ", Maine")) |>
  group_by(NAME) |>
  select(NAME, variable, value) |>
  gt() |>
cols_label(
    variable = md("**Unit Status**"), 
    value = md("**Quantity**")) |>
  tab_header(md(
    "**Number of Occupied & Vacant** \\
    **Units in Maine by County**"))

Number of Occupied & Vacant
Units in Maine by County

Unit Status

Quantity
Androscoggin County
Occupied 45393
Vacant 4444
Aroostook County
Occupied 29784
Vacant 8519
Franklin County
Occupied 12842
Vacant 8014
Hancock County
Occupied 24948
Vacant 15185
Knox County
Occupied 17883
Vacant 6372
Lincoln County
Occupied 15803
Vacant 7805
Penobscot County
Occupied 64250
Vacant 10628
Piscataquis County
Occupied 7615
Vacant 6962
Somerset County
Occupied 21924
Vacant 7861
Washington County
Occupied 13757
Vacant 7837
York County
Occupied 88924
Vacant 23274
Cumberland County
Occupied 128100
Vacant 21352
Kennebec County
Occupied 53223
Vacant 9384
Oxford County
Occupied 24712
Vacant 11418
Sagadahoc County
Occupied 16136
Vacant 2802
Waldo County
Occupied 17143
Vacant 4778

Submission

To submit your assignment:

  • Change the author name to your name in the YAML portion at the top of this document
  • Render your document to html and publish it to RPubs.
  • Submit the link to your Rpubs document in the Brightspace comments section for this assignment.
  • Click on the “Add a File” button and upload your .qmd file for this assignment to Brightspace.

Grading Rubric

Item
(percent overall)		 100% - flawless 67% - minor issues 33% - moderate issues 0% - major issues or not attempted
Chart or table accuracy.
(45%)		 No errors, good labels, everything is clearly visible in the rendered document.
At least two valid variables used from US census data (can be census or ACS)
(40%)
Messages and/or errors suppressed from rendered document and all code is shown.
(7%)
Submitted properly to Brightspace
(8%)		 NA NA You must submit according to instructions to receive any credit for this portion.