The thing that inspired me to create a Covid-19 Info-Graph was, the fact that I wanted to help: healthcare workers, the elderly, and society in their mission to combat this new strain of coronavirus. Unfortunately, where I live (Belle River, ON), I see lots of people who do not keep a safe distance from others, and who do not stay inside.
This piece of software, helps inform users on the effects of too many individuals getting infected with Covid-19 all at once, and it also gives users some insight into facts and things they can do to prevent the spread of Covid-19.
I built this by using the Numpy library, the Tkinter library, and the Matplotlib library, and by programming this in Python. The home page contains a graph, showing the positive effects of following effective measures to combat Covid-19. This was done using Numpy as Pandas. In addition, there is also a button that leads users to some fascinating facts about Covid-19, and what can be done to prevent the spread of this virus.
Before this Hackathon began, I ran into the monumental challenge of having to build a fully-functional GUI in Python, without a partner. Unfortunately, my partner had to deal with some issues that he had, and we weren't able to work on this project together. During the development process a challenge that I ran into was integrating matplotlib and Tkinter together, so that the graph can appear on the window. In addition, I initially planned on making a web-scraping tool that would scrape the web for coronavirus cases. However, as time moved on, that couldn't be feasible due to my lack of knowledge in web-scraping
Some things that I am proud of are: creating a fully-functional GUI with a matplotlib graph on the GUI, and learning lots about connecting different files together in Python.
There are many things that I learned in this Hackathon. Some of those things are: matplotlib, fundamentals of web-scraping and the BeautifulSoup library, along with using data science libraries in Python.
The next things for the Covid-19-Infograph are: creating a page that hosts a graph which shows the total number of cases, total number of death, recovered cases, and having a fully functional GUI.
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