COVID-19 Visualizer πŸ¦ πŸ˜·πŸ“ˆ

Inspiration πŸ’‘

Having so much data in our hands, we want to visualize it in a way that is easier to understand for everyone. It would be more convenient to look at graphs and maps rather than a bunch of numbers as it is visually more appealing. While having the initial idea, we did a bit of research and were able to get a lot of ideas from leading sources in healthcare, news, and research that had already set up much more advanced visualizations of covid data, such as John Hopkins or the New York Times. We tried implementing it our way even though it is our first time using data visualization for this large data set.

What it does πŸ“‹πŸ“Š

This web-based application helps visualize which countries use a certain COVID-19 vaccine using a color-coded world map and a drop-down feature that allows one to view different global usages of various vaccine releases. Each map shows which countries use which kind of vaccines are used and the graph displays the total percentage vaccinated in a country compared to the population of the specific country.

How we built it πŸ‘©πŸ»β€πŸ’»

Using Python, Pandas, NumPy, and other libraries like Dash, and Plotly, we were able to calculate and show some patterns about different countries' use of COVID vaccinations.

Challenges we ran into πŸ§—πŸΌβ€β™€οΈπŸ€―

Data sanitization and reworking the datasets we found to fit what we needed to visualize an answer to the question. The datasets obtained and provided had much of the data missing and we needed to accumulate the data, clean it, and pre-process it for usage in our tables.

Accomplishments that we're proud of πŸ‘πŸ½πŸ€©πŸ˜‰

Being able to figure out how to adjust and reformat the data to answer the questions we had, as well as visualize them in a dashboard was exciting. For both of us, it was our first time using some libraries and we had a difficult time learning them and implementing them on the fly. We are glad it worked to most of what we expected even though we expected more out of what we can do.

What we learnedπŸ§πŸ€“

This HackHers experience gave us a crash course in Dash and data visualization and introduced us to the many challenges that data scientists face when trying to identify trends in data or conduct further research.

What's next for COVID-19 Visualizer πŸ‘©πŸ»β€πŸ’»

After improving crucial functionality and working off bugs as they come up, we'd also be interested in developing an app for this platform so that our work isn't just limited to a web browser on a computer.

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