meat consumption by country. The raw data is categorized by meat category (beef, pork, poultry, sheep) and the year.
I decided to work with this dataset because I enjoy eating meat and I was curious about the patterns I would find in this dataset.
In my visualization, the data is represented as circles, the sizes relative to the value. The values I chose to focus on 2018.
To interact with the visualization, try clicking the screen.
One interesting thing I noticed during this project is poultry is the most eaten type of meat, and pork is eaten most in Asia.
Something I still wonder about is if the value system is the most accurate way of representing the data. Currently, it is measured in thousand tons of carcass weight converted to kilograms of retail weight per capita.
The most challenging moment of this project was messing with the data and figuring out how I was going to represent this data set. After that, the most challenging part of the project was the time restriction we had
If I had more time, I would like to have a slider or button to change between years, because right now my data is only for 2018.
My proudest moment during this project was when I debugged and my circles appeared, it was relieving to have a working program.