Refuge For Ukraine

Tracking the Russia-Ukraine War visually to send help where it’s most needed.

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Inspiration

With the outbreak of the Russia-Ukraine war, there are thousands of different articles about refugee movements and charities to donate to, many of which are unreliable and difficult to read. We hope to educate the general public about the refugee situation in Ukraine through data visualization with an interactive map and direct people to trustworthy organizations that they can donate to or volunteer with to aid Ukrainians in their time of need.

What it does

Our product features an interactive map that shows the displacement of Ukrainian refugees to several neighboring countries. Users can see how refugee movement has changed over the course of the war using a slider. In addition, our map shows the resources of each Ukrainian province so it can be easily seen where people need help the most. We also have a page dedicated to articles about the war and links to organizations so people can help out.

How we built it

For the front-end, we used the Python framework Flask and some HTML, CSS, and JS. We used Pandas, Geopandas, and Folium for the map and data visualization.

Challenges we ran into

Our team had past experience with Python and a few frameworks, but we were all pretty new to data visualization and had never created a front-end with Python. By doing some research we learned about Flask, Geopandas, and Folium and were able to quickly learn how to implement them in our project through tutorials and articles. We also ran into some issues with our website not loading on Repl.it and had to spend a few hours debugging before we could continue working on our project.

Accomplishments that we're proud of

We're proud of learning new Python frameworks in a short amount of time and finding datasets that suited our project's needs. It was challenging to find the right data because of how recent the Russia-Ukraine war is, but once we found the correct data, we were able to implement it in our map through different formats like choropleth mapping, and proportional symbols. This helped make our data visualization easy to interpret.

What we learned

We learned about different ways in which data can be presented and why it is important to make data easily interpretable. We also learned new frameworks including Flask, Geopands, and Folium.

What's next for Refuge for Ukraine

We plan on adding more useful data to our map such as food shortages so everyone can be well-informed about the situation in Ukraine and lend a helping hand.

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