I was inspired to create this project due to my annoyance with current COVID-19 data visualization. I feel like as a member of the general public, we never get to see and explore the data ourselves for locations that interest us.

What it does

This web app takes data from Our World In Data (which is updated daily) and allows for the user to visualize the data over a wide variety of parameters across time for a particular location (ex. How many new cases of COVID-19 are there in the United States recently as compared to April or December?).

How I built it

I built this web app using Shiny inside RStudio. I got the data import process to be automatic (assuming the link doesn't change), and from there just manipulated the data set to extract the information that I needed in a variable way.

Challenges I ran into

I don't have much experience with Shiny (especially input/output managing) and ran into problems trying to make the data set update automatically based on what the user inputs (making the data set "reactive"). Also, (as sad as it is) I haven't used R in a while and so some of the files were out of date. In order to use "install.packages()" you need Rtools installed and I didn't have that and initially tried to install the wrong version.

Accomplishments that I'm proud of

I'm proud that I created a non-biased graphical representation of COVID-19 data and that it allows for a lot of different variables to be viewed to give the user a larger sense of what is actually going on. I'm proud of figuring out how to make graphs/names/etc. that are user defined variables.

What I learned

I learned a lot about input/output and also how to capture data from a url (that was my first time trying that).

What's next for COVID-19 Data Analysis

Ideally improved functionality (easier to read axes, different colors, more types of data and ways to visualize it). I think it would be cool to make something identical but specifically just for the United States as this data was international and not state specific.

Built With

  • r
  • rstudio
  • shiny
  • shinyapps
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