Just the polars on the chart that are significant. The interactive chart is supposed to give all details on hover.

Wow, Do you have the visualisation output from that?. Will be good to see.

https://datawrapper.dwcdn.net/jiiQA/1/ (for interactive use)

Made with Datawrapper using Ourworldindata source.

Not what I meant. This is purely a statistical measure. If you calculate the same numbers for a small county, You will have more biases than when you do it for a country. So, even if I add more biased counties, the national numbers will not be impacted much.

What you are asking is more information , which is sadly not available. Will dig deeper in the future.

Statistically if you average it out, you should reduce bias. But, it won't eliminate the same. Also, such data is not available at a global scale.

Follow-up to the previous post ( ILO data visualized using Datawrapper)

Generally if you go upwards in Altitude, petroleum consumption is higher for heating solutions, Also you may be right - on the security forces, plus the public transportation is minimal - so private transportation might take up more.

Petrol planning and Analysis department of India, made using Datawrapper.

Per capita = total consumption/population.

Interesting. The graph is ordered by the highest %gap. Ethiopia has the highest % gap. But it would be unfair to highlight that considering their pay is well below the world average.

It's not the case, the graph is ordered by %gap. Ethiopia has the highest %gap.

It's the ILO data. They don't cover all geographies. For the ones they cover, some of them don't have enough data vintage. So excluded them.

However the ordering is by % gap basis. I did want to suggest that Ethiopia has a big problem, when the earnings irrespective of male or female is extremely low compared to World average.

Leaving geographies with sparse data (lower representation across sectors). Made from International labour organization data using Datawrapper.

By default my system gets the formatting using the Indian system. Which is 00,00,000 . In the above case One Lakh, twenty five thousand , eight hundred and thirty four crores.

The data is from Finance ministry India website . The tool used ( plain old Excel)