Inspiration

We were inspired by HPE's challenge to find a community problem HPE can help address. We know that HPE prioritizes giving back to communities and values education. We thought we would explore how students have been impacted by COVID-19, and which students are the most vulnerable during this time.

What it does

Our web app allows users to visualize school district data describing the percentage of students in poverty, without access to the internet, in single-parent homes, and homes with high job vulnerability. The user can select which states and factors to visualize, then explore plots created from their choices. Next, the web app shows the user which schools are at the most risk due to COVID-19 in the form of a Student Vulnerability Index (SVI). Specifically, SVI provides a combined metric for the factors which most greatly impact school districts. Finally, the user can navigate to the "Call to Action" section, where the app suggests possible interventions for each vulnerable demographic.

How we built it

We built this app in Python using the streamlit library, which renders Python as a web application. Other libraries we used include pandas, plotly, and Dash, which is a framework for building web apps. We also used devOps tools such as Git for version control, and created and configured an AWS EC2 instance to which we deployed our application. The dataset we used is from the Urban Institute's "School District Data for Mapping Student Needs During COVID-19".

Challenges we ran into

Our first challenge was to learn how to build a web app. We decided to use Streamlit because of its integration with Python and ease of deployment. We also had challenges of merging code with Git.

Accomplishments that we're proud of

Accomplishments to note include dynamic data visualization of our data. Users can choose which variables they want to see on each plot.

What we learned

In developing our solution, our team gained first-hand experience with a number of tools and frameworks, including:

  • Pandas
  • Plotly
  • Streamlit
  • Dash

We also used devOps tools such as Git for version control, and created an AWS EC2 instance to which we deployed our application to the public.

During this project, we also learned of school districts that are particularly vulnerable to impact from COVID-19, and also how to share this actionable data in a meaningful way.

Project Impact

By enabling us to discover which school districts are most susceptible to impact from the COVID-19 pandemic, organizations such as HPE can target these districts for relief efforts to ensure that their students can be successful.

What's next for the project

Given more time, we'd like to expand upon exactly what HPE can do for these communities, and which actions will have the most impact.

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