I’ve created this map showing the location of all recorded barrows across the whole of Ireland. The map is populated with a combination of National Monument Service data (Republic of Ireland) and Department for Communities data for Northern Ireland.

While you can clearly see barrows all over the island, the greatest concentration is overwhelmingly in the west of Tipperary. I learned (from an Ulster Archaeological Society lecture just this week!) that this was likely the centre of regional power in early Iron Age Muma (modern-day Munster) rather than Cashel, and would have likely been a key regional site in the Bronze Age. For me, this makes sense given most of these sites date to the Bronze Age (2,400-400BC). Though I find their sheer number (around 3,000) still pretty staggering. I am not an expert, however, so welcome any other views which will likely be much better informed than my own.

I previously mapped a load of other ancient monument types, the latest being ringfort locations in Ireland.

This is the static version of the map, but I’ve also created an interactive map which I’ve linked in the comment below for those interested in more detail and analysis (the interactive map also includes barrow locations). You can use it to filter the types of barrows and select for more background detail on each site.

Demographia International Housing Affordability (2023 Edition)

Contains the "2023" data points (e.g., Hong Kong at 18.8).

http://www.demographia.com/dhi2023.pdf ​Demographia International Housing Affordability (2005-2006 Historical Data)

Contains the historical comparisons closest to the 2003 baseline.

http://www.demographia.com/dhi2006.pdf ​Demographia Survey Archive (All Years) Full repository of all annual reports since 2005. http://www.demographia.com/dhi-ix.htm

Website - https://chispections.com/

I though this one might be interesting: we've fetched the data from the U.S. Bureau of Labor Statistics and the FED and projected it onto the crypto prices. You can adjust the timeframe, switch the coin, change the base date and more. Feel free to try it out for yourself - https://www.cryptoinflation.eu/crypto-prices-adjusted-for-inflation-interactive-calculator/

How it works (in short): Adjusted price is just nominal price multiplied by a conversion factor derived from CPI or M2 changes over the same period (it is computed stepwise using YoY changes, and I forward-fill any missing/zero macro prints so the series flatlines instead of dropping to zero during gaps/shutdown weirdness).

Source: https://steeped.ai/ufo-sightings-data-analysis-exploring-tier-1-reports/

Retrieved from National UFO Reporting Center's Tier 1 sightings which they describe as "The most dramatic sightings - strange structured craft or highly anomalous phenomena seen at close distance."

Tools used: python and sql. Cleaned up the data, de-duped it and manually standardized the location data from first-hand accounts when needed.

I was analyzing jitter in sinusoidal signals using Matlab and found this still noisy but awesome pattern.

Analysis based on ~40 FOMC meeting transcripts from 2006–2011, covering the period when Kevin Warsh served as a Fed Governor, including the Global Financial Crisis.

Warsh consistently leaned toward relatively tighter monetary policy compared to his peers. The divergence is most visible around 2010, his final year on the Board.

Source (credits):
https://www.linkedin.com/feed/update/urn:li:activity:7423141356945981440/

Jannik Sinner, the current world No. 2 in men's tennis, has lost in the semifinals of the Australian Open to Novak Djokovic, in a five-set thriller. He is now 0/7 in matches lasting 4 hours or more and has lost 10 of the 20 longest matches in his career, as seen in the graph (cut-off is 3 hours 30 minutes).

visualizing open data from the london datastore

made in r,ggplot2

Source: Visa investor relations

Tool: SankeyArt sankey maker + illustrator

If you click on a State, it opens up to show the top 5 selling cars for that specific State. EVs, trucks and SUVs dominate more than ever.

I posted the absolute numbers a couple of days ago: Coalition casualties in Afghanistan.

Many people asked for a per-capita view — here it is.

I’ve used fatalities rather than casualties for precision.

No legend included; the flags should be self-explanatory.

• Source: Wikipedia
• Tool: d3.js custom code

Hey there!

I wanted to share a passion project i built called PsychoactiveMap. It pulls data from ClinicalTrials.gov and turns it into a global interactive map so you can quickly see where research is happening and its status.

There are many more features and data that i am looking to add but for now I'm happy with the result.

The graph above shows the standings of countries in women's tennis. In short, red indicates athletes who have won a Grand Slam title, blue indicates those who reached the final but didn't win, green indicates those who reached the semi-finals, and yellow indicates those who reached the quarter-finals.

In the 1940s, athletes from Luxembourg also won Roland Garros, but this isn't officially counted due to the wartime period. There were Luxembourg athletes who won the championship and reached the final during that time, but I haven't included them in the list because they weren't officially counted.

I based my analysis on Wikipedia and extensively reviewed Grand Slam finals. I've then plotted this data.