Guess the Map 12: Or, How I Learned to Stop Worrying and Hate Mercator

[Birdjaguar]

Consumption per capita

 

[Samson]

Consumption per capita

Getting warmer.

 

[Birdjaguar]

Meat consumption per capita

 

[Samson]

Meat consumption per capita

Warmer

 

[Birdjaguar]

OK guys and gals, finish it off and grab the next map.

 

[Samson]

Birdjaguar is so close, these things he mention are related, but this is the big one.

 

[The_J]

I'm stumped .

 

[Samson]

Is this any use:

> head(world[order(-world$y_integral),c("name","y_axis","y_pop","y_integral","pop_rank","total_rank")])
181                Qatar   1931.7459 0.0023182295 4.055367e-05      189        126 MULTIPOLYGON (((51.26797 24...
7   United Arab Emirates   4438.3137 0.0009249395 2.298227e-05      179        150 MULTIPOLYGON (((53.92783 24...
120               Kuwait   2718.6338 0.0010102097 2.153649e-05      181        136 MULTIPOLYGON (((48.27539 29...
34                Brunei    335.4469 0.0008641308 1.862270e-05      177         85 MULTIPOLYGON (((115.0268 4....
24               Bahrain    855.8613 0.0011759809 1.721110e-05      184        110 MULTIPOLYGON (((50.60723 25...
226        United States 404769.3984 0.0012891854 1.568398e-05      187        189 MULTIPOLYGON (((-155.5813 1...

y_axis is the primary measure
y_pop is y_axis / current population (the first thing I plotted)
y_integral is y_axis / population integrated by time (the 2nd thing I plotted)
pop_rank is the rank of y_pop
total_rank is the rank of y_axis

 

[Kyriakos]

Obesidad related?

 

[Samson]

Obesidad related?

No, whether is is obesity or obsidian.

 

[Samson]

Both the numerator and the denominator are integrated by year from 1781 until present. For the numerator this basically makes it a total, and I think very meaningful (this number if y-axis above, United States = 404769.3984). The denominator is a rather meaningless number but I think is representative of the population of the country considered over this time period.

 

[The_J]

I'm sure I'll say "obviously" when I see the answer, but I still can't figure it out .

 

[Samson]

You totally will. here are the top countries by absolute value, not adjusted by population:

> head(world[order(-world$y_axis),c("name","y_axis","y_pop","y_integral","pop_rank","total_rank")])

              name    y_axis        y_pop   y_integral pop_rank total_rank                       geometry
226  United States 404769.40 0.0012891854 1.568398e-05      187        189 MULTIPOLYGON (((-155.5813 1...
41           China 210201.18 0.0001570291 1.562769e-06      101        188 MULTIPOLYGON (((110.8888 19...
183         Russia 100720.36 0.0007192192 5.636464e-06      173        187 MULTIPOLYGON (((146.0456 43...
57         Germany  91300.31 0.0011089589 7.463192e-06      182        186 MULTIPOLYGON (((14.19824 53...
76  United Kingdom  77448.90 0.0012439192 9.020000e-06      186        185 MULTIPOLYGON (((-1.065576 5...
110          Japan  63517.22 0.0004998259 4.399678e-06      156        184 MULTIPOLYGON (((123.8887 24...

 

[The_J]

God, is it something like GDP or similarly easy?

 

[Samson]

God, is it something like GDP or similarly easy?

Not GDP. That is the one guess that has been higher profile that what this is, and there is a link between the 2.

 

[klar_heiland]

CO2?

 

[Samson]

CO2?

WE HAVE A WINNER!!!!!!!!!!!!!!!!!!!!!! You are up.

Yes, CO2 emissions since 1781 divided by population. Interesting, but not that surprising, that Qatar is nearly twice as high as the second highest, and 4 times that of the US.

If anyone wants any help making these maps using R feel free to ask. I can make them now in very few minutes from pretty much any page of Our World In Data.

 

[amadeus]

When I see maps like that I always wonder how they count for things like Germany or Russia where borders have changed significantly, or many times.

Just off the top of my head for Germany, the Napoleonic invasion, Prussia after the war, the short North German Confederation, the German Empire, the Weimar Republic, Nazi Germany, and then divided and reunited Germany.

 

[Samson]

When I see maps like that I always wonder how they count for things like Germany or Russia where borders have changed significantly, or many times.

Just off the top of my head for Germany, the Napoleonic invasion, Prussia after the war, the short North German Confederation, the German Empire, the Weimar Republic, Nazi Germany, and then divided and reunited Germany.

This is why the Czech republic and Slovakia were grey, I could not work out how best to distribute the various numbers I had. Reunited germany was easy, I just added up the numbers I had. Other splits, except Yugoslavia, were early enough to not make too much difference. The numbers seemed to account for the different components of the USSR, so they were not a problem.

 

[klar_heiland]

open floor