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Originally r/DataisBeautiful
Link to website: https://whatif.sonycsl.it/15mincity/index.php
cross-posted from: https://slrpnk.net/post/13859498
I'll note that in the US, their urban area definition includes a lot of outlying and substantially unpopulated areas which fall within county boundaries; these areas tend to show up as having long travel times to services.
The image is from a Washington Post article which took the data from an interesting research paper titled Who Pays For Your Rewards? Redistribution in the Credit Card Market.
The research paper is a good read. (A free PDF of the whole paper is available at the link.) It examines how the use of rewards credit cards results in a massive wealth transfer from low-credit-score customers to high-credit-score customers:
We estimate an aggregate annual redistribution of $15 billion from less to more educated, poorer to richer, and high to low minority areas, widening existing disparities.
The Washington Post article attempts to frame the clear north-south split as a result of healthcare issues in the south. That explanation seems too narrow to me. This map looks too similar to maps of poverty and education, and we know health correlates strongly with both of those issues.
Edit to fix a sentence fragment. Sorry; it was late and I was tired.
Best of luck to Mozilla. Their line on the chart may end soon if they lose funding from Google.
Stolen from Reddit.
The big drop in the 1970's was supposedly due to a change in the program to de-emphasize outdoor activities. The step down in 2019 was the LDS church cutting ties and starting their own program.
If you consider this as a proportion of the population it's an even bigger drop. In 1970 there were about 4.8M scouts in a population of 205M, so about 2.3% of all Americans were in Boy Scouts. Now it's 1M scouts in a population of 341M, so only 0.3% of Americans are in Boy Scouts.
▶️ Total olympic medals won in Paris 2024 and Human Development Index 🏅
➡️ https://www.businesstimes.com.sg/opinion-features/what-olympic-medal-table-really-tells-us
After reading the article we made this #boxplot using #LabPlot, an open source data analysis and visualization software.
The plot doesn't provide answers, it rather invites some thinking.
#Olympics #Olympics2024 #France #China #USA #UnitedStates #UnitedKingdom #UK #Brazil #Australia #Japan #Italy #Canada #Germany #Italy #Netherlands #DataAnalysis #DataScience #OpenSource #FOSS
This chart has been floating around, and I find it interesting to speculate about the reason for this shift.
Have attitudes changed this much? Do teens have less independence or fewer places to go to do these things? Are parents more involved in teens' lives? Was vaping excluded in the study?
Source OP's comment:
Source: birth rates in the US, from social security card applications. Provided by SSA.gov. For the age ranges, we make the assumption that all women lived to exactly 73 years old, which is the life expectancy for females at birth in 1960. Therefore, the population in each age range will not be entirely accurate, particularly for 69+, but it nonetheless shows the trends of birth rates and popularity of these names over time. Tools: python, pandas, Vega>
