The initial plot takes the 7 countries that have the biggest contribution of CO2 by diet, and adds the USA, Canada, Mexico, Japan, Germany, South Korea, China, and the average for this data set for comparison.
Version 2 uses gghighlight to call out specific countries and the average CO2/person/year produced on average.
The final version removes the labels (they were cluttering the image) and is interactive: you can see the CO2 produced and zoom in to areas that get crowded.
The initial plot takes the 7 countries that have the biggest contribution of CO2 by diet, and adds the USA, Canada, Mexico, Japan, Germany, South Korea, China, and the average for this data set for comparison.
Version 2 uses gghighlight to call out specific countries and the average CO2/person/year produced on average.
The final version removes the labels (they were cluttering the image) and is interactive: you can see the CO2 produced and zoom in to areas that get crowded.
Mapping the difference between the CO2 production of animal product and non-animal product, over a year. A low value means that a larger proportion of the population feeds on plant products which have a better carbon emission footprint.
The average difference between CO2 production of animal and non-animal products for the countries in this study is 700 kg. Countries with above average CO2 are shaded in brown; those with below average CO2 are shaded in blue-green.I like the color gradient but would like to change the perspective, country outline,
and maybe use a divergent color palette. Interactivity would also be neat.
There is so much data, a table felt necessary. Initially, I used mostly default settings, unaware of the endless possibilities. Then I added search and filter options and allowed more data per page (14 pages seemed like too many…).