A repository for my COVID-19 visualizations. Here's a playlist of those videos: https://www.youtube.com/user/1abacaba1/videos
This Github repo was announced and explained in this video, from 2021-06-25: https://www.youtube.com/watch?v=dkbNXQFc4Ro
These visualizations all use Processing 3 to draw the actual visualization videos: https://processing.org/ If you'd like to run these code snippets and save them to a video file, you'll also need "Hamoid's Video Exporter", a library that allows to export directly to .mp4 video files from within Processing. Here is a demonstration of me downloading and using the Hamoid library: https://www.youtube.com/watch?v=ol6PM0BMjzI&list=PLsRQr3mpFF3Khoca0cXA8-_tSloCwlZK8&index=10 A handful of visualizations also have Python scripts to do non-video related tasks, like sound processing.
Watch this video for a brief explanation about what this repo is: [video is not out yet]
Note: I programmed most of these visualizations quickly, as soon as data was posted to worldometers.info, since I wanted to give the public the most up-to-date summaries as possible. As a result, none of the code is really designed with ease-of-use, coding style, or collaborator-friendliness in mind. That's why you might find that my code seems very hard to understand or tweak, and I apologize for that. However, I won't be regularly maintaining this code or providing coding assistance to new programmers for this project. This repo is supposed to be a dumping ground of my personal projects, that just happens to be public, in case people are curious!
Also: The data-visualization called "GapMinder Inspired" is designed to collect up-to-date data in an easy way. As in, there is a single Python script that reads the data from worldometers.com, assuming that website doesn't drastically update in the future (after 2021-06-21). Watch the above video for a demonstration on how to run it. For all the other data-visualizations, there is simply a data file (perhaps called something like "worldData.csv", that I downloaded and compiled at the time, but is frozen in time (meaning, it won't update). You're free to update/change these as you wish, but it will take a bit of work on your end, since there isn't any "data-collecting" script for those!
Seen at 3:14 in the 2020-02-28 video: https://www.youtube.com/watch?v=9PYKYjkqnGU&t=194s
Compares the COVID-19 death toll with the death tolls of other causes (like car crashes, influenza, etc.) specifically in one country.
Note: By editing the first few lines of the source code, this data visualizer can show data from other countries, such as India.
Seen at 11:30 in the 2020-05-31 video: https://www.youtube.com/watch?v=b1hRKhHhOF4&t=690s
Seen at 2:51 in the 2020-04-02 video: https://www.youtube.com/watch?v=sz1bGzYdRdk&t=171s
Seen at 0:00 in the 2020-04-10 video: https://www.youtube.com/watch?v=x_wZQ8fVIwQ
Seen at 4:42 in the 2020-02-12 video: https://www.youtube.com/watch?v=6dDD2tHWWnU&t=282s
Seen at 1:30 in the 2021-01-21 video: https://www.youtube.com/watch?v=i7SNyzmKXUE&t=90s
Inspired by Hans Rosling's work with scatter plot visualizations at Gapminder: https://www.gapminder.org/
Seen at 0:17 in the 2020-11-07 video: https://www.youtube.com/watch?v=eeiguFaRil0&t=17s
Seen at 2:27 in the 2021-01-21 video: https://www.youtube.com/watch?v=i7SNyzmKXUE&t=2m27s
getCountryList.py will scrape worldometers.com and save a list of all countries. You don't need to ever run this, because countryList.tsv is in the repo.
Running getData.py will download the most recent international data of COVID-19 cases and deaths from worldometers.com, and processData.py will process it into one compact file that the Processing visualizer can interpret. Check out and modify the first few lines of both Python files to allow those scripts to download US state data instead of country data.
Seen at 0:00 in the 2020-06-29 video: https://www.youtube.com/watch?v=3HHOK1gNypE
Seen many times. One of the first times was at 1:09 in the 2020-03-19 video: https://www.youtube.com/watch?v=n4no04822NQ&t=69s
One of the more recent times is at 0:17 in the 2021-01-20 video: https://www.youtube.com/watch?v=i7SNyzmKXUE&t=17s
Note: You won't be able to get this code to run. Here was how the code was originally supposed to work: You run scraper.py in one command prompt, which loads the worldometers.com/coronavirus website every 60 seconds looking for updates. Simultaneously, you run visualizer.py in another command prompt, which reads from the dataStream.txt file that scraper.py outputs, and turns that data into a 30 FPS video output that can then be livestreamed. However, when I try to run this code these days, I get a 403 Forbidden error from worldometers. This probably means none of you will be able to get the livestream up and working, either. I'm only including this code here in case anybody is curious in my coding style/process/workflow, but not necessarily seeing it work in action.
Seen in the 2020-03-21 livestream: https://www.youtube.com/watch?v=nmrhTEwAqD0
Also seen in the 2020-03-21 livestream: 2020-03-25: https://www.youtube.com/watch?v=u35rna7XvEA
Seen at 0:00 in the 2021-01-10 video: https://www.youtube.com/watch?v=x7KYJ1MFGdc
Note: This visualization seems to downplay the severity of the virus, which I now regret. At the time of making it (Feb 12, 2020), there had been 2 deaths outside China. I was worried that people were treating this outbreak the same way they had the 2014 Ebola outbreak, which was panic and xenophobia. So, I was trying to provide a more levelled perspective to convey to people to not overreact. However, in hindsight, this visualization made the virus seem less deadly than it truly became, which was my mistake. I'm posting this code in the spirit of open-sourcing everything, but I hope people don't use it to downplay the virus further. (If the code is edited to show recent data, it should accurately reflect how serious it is.)
Seen at 5:44 in the 2020-02-12 video: https://www.youtube.com/watch?v=6dDD2tHWWnU&t=344s
Compares the COVID-19 death toll in the United States with the death tolls of other causes (like car crashes, influenza, etc.). It is also aligned to see October 1 as the start of each year, because October 1 is the start of the "flu season". The goal is to see if COVID-19's trends fits in with the pattern of annual flu waves, and it does not.
Seen at 6:27 in the 2020-05-31 video: https://www.youtube.com/watch?v=b1hRKhHhOF4&t=387s
Seen at 0:00 in the 2020-03-08 video: https://www.youtube.com/watch?v=KrgYEdb-Fls
Heard at 0:00 in the 2020-03-08 video: https://www.youtube.com/watch?v=KrgYEdb-Fls
Note: chinaCOVID19deathCount.txt is a timetable describing all the times that a guzheng sound should play (in 44,000 Hz samples) If you run coronasounder.py, it will read that timetable, and use the 6 sounds in the "sounds" folder to play a Guzheng sound at each time interval listed! Also, sometimes, Windows Media Player is unable to play the output file. When that happens, I just load the .wav file successfully in Audactiy (https://www.audacityteam.org/), and then save it as a new file.
