Class times and due dates

Lab assignment due date (no reading quiz or live coding assignment this week):

Sunday, August 11, 11:59pm
Note: This due date is earlier than Tuesday! I'm sorry about that, but we run into UVA's strict grade submission deadline. No late lab assignments, live coding assignments, or quizzes can be accepted after this date.

Our class live session for this module will be on Wednesday, August 7, 7:15-8:15pm:

Zoom link for both classes: https://virginia.zoom.us/j/99100731857?pwd=QTZCTnVVdndnaDl0MSttelNFRVBSQT09

Textbook, Video Lectures, and Slides

Please read Chapter 12 of "Surfing the Data Pipeline with Python": https://jkropko.github.io/surfing-the-data-pipeline/ch12.html

I did not use any slides for this module as it is not possible to show what interactive visualizations can do on slides.

Lecture 12.1: Interactive Data Visualization with plotly

Lecture 12.2: Dashboards

Lecture 12.3: Congratulations!

External Readings and Reading Quiz

The readings for this module are

Browsing the Plotly Gallery to see what is possible and how to code different graphs: https://plotly.com/python/plotly-fundamentals/

Working through the Dash tutorial: https://dash.plotly.com/installation

Some thoughts on how to make an effective UX design: https://www.toptal.com/designers/data-visualization/dashboard-design-best-practices

There is no reading quiz for module 12. This week everyone will automatically receive full credit for the module 12 reading quiz to thank you for all your hard work this semester. That said, if you really want to take a quiz, here's one! Reading Quiz 12

Lab Assignment

You can find this module's lab assignment on Gradescope (don't forget the [instructions for submitting your assignments to Gradescope] ) :

Lab assignment on Gradescope

You can download the PDF version of the lab on Gradescope, but here is the .ipynb notebook file that you can use as a template to write your assignment:

labassignment12.ipynb

Live Coding Exercise

Note: we work through the following exercise during the final week of the class, but no live coding script is required or due.

Source: DALL-E, responding to the prompt: "A student in an online class making a data dashboard about counties in Virginia but it's also the end of the semester and everyone is really tired."

Building a Virginia County Cost and Standard of Living Dashboard

Our goal is to build a dashboard that illustrates the cost and standard of living in all of Virginia's 133 counties and independent cities. The dashboard will include:

Total population
Average annual pay
A general cost of living metric
Poverty rates
Education rates
Years of potential life lost rate (a metric of overall rates of early death)
Percent in fair or poor health
Average number of mentally unhealthy days
Percent adults reporting currently smoking
Percent adults with obesity
Food environment index (accessibility to healthy foods)

The data come from the following sources:

Annual pay come from the U.S. Census County Business Patterns API: https://www.census.gov/data/developers/data-sets/cbp-zbp/cbp-api.html

Cost of living is estimated for all counties by the U.S. Department of Commerce https://www.commerce.gov/news/blog/2024/03/estimating-county-level-regional-price-parities-public-data

Education and poverty statistics come from the U.S. Department of Agriculture Economic Research Service: https://www.ers.usda.gov/data-products/county-level-data-sets/county-level-data-sets-download-data/

Overall population and population by race comes from U.S. Census data from 2023, made available via the Weldon Cooper Center at UVA:
https://www.coopercenter.org/virginia-population-estimates

Aggregate health metrics and the food environment index come from County Health Rankings & Roadmaps, a program of the University of Wisconsin Population Health Institute: https://www.countyhealthrankings.org/health-data/methodology-and-sources/data-documentation

I've already collected and cleaned the data and compiled it into this CSV file. Start by downloading this file and opening it in Python:

vacounties.csv

If you are curious about the data collection and cleaning, everything is in this notebook: VA_counties_data.ipynb

Our goals over the next two weeks:

Create visualizations using plotly illustrating
1. the map of Virginia, color-coded by country according to different features;
2. an HTML enabled data table to show the raw data;
3. A correlation matrix between all numeric features;
4. and a scatterplot with best-fit line showing the relationships between pairs of features.
Create a dashboard with tabs for the county-level statistics and relationships

We'll pick up on dashboarding from where we left off last week: livecoding12_counties.ipynb