Data source: Self-collected dataset of unprompted comments by other people about my dog while going on walks with him.

Tools: R+ggplot for exploratory data analysis and visualization.

This is my original work, and I have directly linked to my original blog post instead of making an image submission because I believe that the context of the post is important.

I am posting this on a Monday because I consider this post to contain Personal Data.

Just randomly found in comments on imgur, might be old, but i think it is an example of actually beautiful data representation...

More like Data is Scary than Data is Beautiful.

Source: https://en.m.wikipedia.org/wiki/Republican_Party_efforts_to_disrupt_the_2024_United_States_presidential_election

It's been trending this way for years, but seeing it graphed out like this is shocking.

What do you think are the effects of this drastic change?

Looks like there's some lying going on, lol

From https://x.com/waitbutwhy/status/1843346677161472417

Link to website: https://whatif.sonycsl.it/15mincity/index.php

cross-posted from: https://slrpnk.net/post/13859498

Related paper

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.

Source: https://eylenburg.github.io/browser_engines.htm

More info https://www.nytimes.com/interactive/2022/06/22/us/shootings-police-response-uvalde-buffalo.html

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.

Source: https://www.census.gov/library/visualizations/2018/comm/acs-5yr-poverty-all-counties.html

cross-posted from: https://sh.itjust.works/post/23749463

Source: https://www.pewresearch.org/short-reads/2024/08/15/a-growing-share-of-us-husbands-and-wives-are-roughly-the-same-age/

Source: https://twitter.com/mediazona_en/status/1823670620065808557

▶️ Total olympic medals won in Paris 2024 and Human Development Index 🏅

@dataisbeautiful

➡️ 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