Description
Read Graphical Data Analysis with R, Ch. 6, 7
Grading is based both on your graphs and verbal explanations. Follow all best practices as discussed in class.
Data cleaning: for many of the questions, you will have to clean up the data more than in past assignments.
Labels do not have to perfect but they have to be legible. Often it is helpful to shorten or abbreviate labels:
this can be done before plotting or at times within the plot functions. You may make any changes to the data
as appropriate before plotting, including renaming column names and the like. Be sure though to include all
adjustments in your scripts.
1. Coal Emissions
Data: https://datadiscovery.nlm.nih.gov/Environmental-Health/TOXMAP-EPA-Clean-Air-Markets-2016-Coal-Emissions/
n97u-wtk7
(OK to manually download .csv file)
(a) Using parcoords::parcoords(), create an interactive parallel coordinate plot of SO2, NOx, CO2, Heat
Input and Gross Load. Each line in the plot should represent one coal plant. Note any patterns.
(b) Create a second interactive parallel coordiante plot, with the lines colored by state. Include only the
states with more than 15 plants. Do any new patterns emerge? Explain briefly.
(c) What do SO2, NOx and CO2 stand for? Briefly describe why each is harmful.
2. Planets
Using rvest, scrape the data from this table: https://nssdc.gsfc.nasa.gov/planetary/factsheet/ (hint:
html_table is helpful). Remove MOON data. Then, using GGally::ggparcoord(), create two parallel
coordinate plots of the numerical variables in the dataset, one colored by the value of Ring System? and
one colored by planet name. In both cases, each line should represent one planet. Use coord_flip so the
variable names are easier to read. Describe any patterns you find.
3. Heart Disease
Data: four data frames that begin with heart_disease in the ucidata package
Packages: You may use vcd or ggmosaic.
(a) Create three mosaic plots, each involving two categorical variables from heart_disease_cl and interpret
the plots. (You may reuse variables, for example X ~ Y and X ~ Z).
(b) Combine the four heart disease datasets and create a mosaic plot showing chest pain by sex and location.
Describe any patterns.
4. District 3 Elementary Schools
Recently, there has been much debate about the lack of racial and economic diversity at Manhattan District
3 elementary schools, part of a larger and long-standing controversy about iniquities in the New York City
public school system as a whole.
1
The New York Times article, “Rezoning Plan to Remake 3 Upper West Side Schools Will Proceed, City Says,”
(https://www.nytimes.com/2016/11/10/nyregion/rezoning-plan-for-3-upper-west-side-schools-will-proceed-city-says.
html) (2016-11-10) identifies the 11 elementary schools in Manhattan District 3.
For this question, we will analyze parent survey results for these schools.
Data: https://www.schools.nyc.gov/about-us/reports/school-quality/nyc-school-survey
(a) Choose one of the likert style questions from the 2019 parent survey and use a diverging stacked bar
chart to show results for the 11 schools identified in the article referenced above.
(b) Choose a question that was asked in 2014 and 2019 and compare results for the three schools discussed
most in the article: P.S. 199, P.S. 191, and P.S. 452. You may use two separate diverging stacked bar
charts or combine all the information in one.
(c) Interpret your findings of (b) in light of the reputations of the schools as presented in the article. Are
they surprising or what you would have expected?
