Cassie L.
Visualization of meat consumption around the world
Visualization of meat consumption around the world
For my final data visualization project, I chose to work with a data set from the OECD (Organisation for Economic Co-operation and Development) about meat consumption by type of meat, and for specific countries. The data is detailed, and tracks kg of meat per capita, the country, and the year (between 2018 and 2029). Any years in the future are predictions.
I decided to work with this dataset because the data seemed very clear, and it involved country-related stuff, meaning I could experiment with the map visualization option.
In my visualization, the data is represented on a map, with dots of different sizes representing the kg per capita of that kind of meat in each country.
To interact with the visualization, try clicking on the type of meat you want to view, and then use the slider at the top to change which year's data is shown. You can also hover over the bubbles to see some extra text.
One interesting thing I noticed during this project is that the most popular kind of meat was poultry, followed by beef, then pork, then sheep. Personally, I expected beef to be the most consumed, but I guess poultry counts for ALL of poultry.
Something I still wonder about is what the data was like for some of the other countries like the USA, China, Brazil, and Russia. In the dataset, a lot of countries were grouped together, which was difficult to clean and distribute, so I just deleted them from the dataset. They are some of biggest countries, so it's kind of sad that I wasn't able to use them.
The most challenging moment of this project was figuring out how to make my dataset interactive. Originally, I had four buttons for the four kinds of meat, and then twelve buttons for the years, which was tons of lines of code, and really inefficient. In the end, I used a slider, which was a lot easier to use.
If I had more time, I would like to add colors when the buttons are pressed, and then find a way to make the bubbles expand/shrink a little more because the changes in the number values make the differences between the years really hard to see.
My proudest moment during this project was when I figured out how to make the slider work, which took a couple class session to work out.