At Kyso [1] we are really concerned about climate change and environmental damage in general - one of my co-founders actually started as an environmental scientist. We make tools to make data-visualisations easier using Jupyter but we've been wanting for the last few weeks to really focus the content that we write on climate change, from a data point of view.
I'm wondering does anyone here have experience with this - where do you source data-sets, what kind of charts have the most impact on people - is this even worth doing?
Interesting; your meat consumption data seems to contradict what BBC's article on meat consumption in India seems to imply. It makes it out as though Indians are eating a lot of meat. Perhaps it's simply that a lot of Indians do eat meat, but not very much of it (relative to North Americans for example).
> Although some will attribute this to a tradition of vegetarianism, surely this is mostly due to the limited access to meat for the poor. As I note below, meat consumption is highest across high-income countries, and the demand for meat in India is, therefore, expected to grow faster with stronger & sustainable forecasted economic growth and rising per capita income.
Most Indians do eat meat, but from what I've seen eating meat with every meal (as is common in the United States) is pretty rare. Also, note that meat is usually expensive, so a good portion of the country cannot afford to eat meat on a regular basis.
I'm wondering does anyone here have experience with this - where do you source data-sets, what kind of charts have the most impact on people - is this even worth doing?
We've made a few studies before going through Co2 rates (https://kyso.io/KyleOS/atmospheric-co2-concentrations-2), which countries are on the most sustainable path (https://kyso.io/KyleOS/environment-ranking) and per capita meat consumption (https://kyso.io/eoin/per-cap-meat-consumption) but we'd love to get some advice on how to really target high impact work in this area
[1] https://kyso.io I'm a founder