Diplomas and Disadvantage: Mapping U.S. Colleges on County Disadvantage Metrics

Introduction

Over 2/3 of postsecondary students attend a school within 50 miles within their home. Community disadvantages and colleges are both scattered unequally across the country; what might their intersection mean for students? The Diplomas and Disadvantage Dash app hopes to introduce the American public and policymakers to this question by providing a mapping tool with several subsets of colleges and over a dozen county metrics. This tool is meant for visualization purposes, not for statistical analysis; those who wish to explore the relationships they find more deeply can visit University of Michigan's Understanding Communities of Deep Disadvantage page to download the county-level disadvantage data.

More details about the origin of this project can be found in Writeup.pdf.

Running the Dash app

Running the app requires the following packages:

• pandas
• geopandas (installation instructions)
• shapely
• plotly (installation instructions)
• urllib
• json
• dash (installation instructions)
• dash_dangerously_set_inner_html (installation instructions)

Once you ensure that you have the necessary packages, clone this repository and run the command python app.py. This command will let you know the port that the app is running on, and then you can open the page in your web browser.

Example of running the python app.py in Mac Terminal:

This is what the page looks like in a web browser:

On this page, you can select disadvantage metrics in the dropdown menu, choose a subset with the radio buttons, and toggle off or on tooltips under the map.

Generating the plotly map alone

If you would like to generate the plotly map alone instead of the web app, you can use create_map.py in the src folder. If you run the command python src/create_map.py, the resulting map will be saved as figures/basic_map.html, and you can open the map in a web browser. You can open the current figures/basic_map.html file in the respository to see the output of create_map.py, and figures/basic_map_snapshot.png to see a static view of this map.

Other files in this repository

The assets folder contains three files:

• app_elements.css: contains the CSS that sets margins and line heights for the body of the Dash page
• favicon.ico: favicon (small image displayed next to the page title in the browser tab) for the Dash page
• typology.css: contains the CSS that sets the font family and font colors for the page

The figures folder contains the basic_map files as well as the screenshots used for the README.

The raw_data folder contains two files:

• CSV_10312024-789.csv: contains the postsecondary institution data
• Index of Deep Disadvantage - Updated.xlsx: contains the disadvantage data

More details about these files can be found in Writeup.pdf.

The src folder contains two files:

• create_map.py: contains the collect_and_clean and create_map functions for app.py, or can be used on its own to generate a plotly map
• util.py: contains functions for create_map.py and app.py that are mainly used for text and filtering for the metric and subset settings

Writeup.pdf: contains more information about the project background and data sources