Additional Info: I wrote a Python script using Astropy to calculate the distance between the named planets on the first day of each month for every year.
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The distance between Jupiter and the Sun correlates with...
Variable | Correlation | Years | Has img? |
How good LockPickingLawyer YouTube video titles are | r=0.99 | 9yrs | No |
How cool LockPickingLawyer YouTube video titles are | r=0.98 | 9yrs | No |
The number of secretaries in Alaska | r=0.95 | 13yrs | Yes! |
Total comments on Extra History YouTube videos | r=0.86 | 12yrs | Yes! |
Professor salaries in the US | r=0.83 | 13yrs | Yes! |
The average age of batters for the Pittsburgh Pirates | r=0.54 | 49yrs | No |
Biomass power generated in Mexico | r=0.49 | 31yrs | No |
Rain in Sydney | r=-0.54 | 48yrs | No |
The number of food scientists and technologists in North Carolina | r=-0.87 | 19yrs | Yes! |
The distance between Jupiter and the Sun also correlates with...
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You caught me! While it would be intuitive to sort only by "correlation," I have a big, weird database. If I sort only by correlation, often all the top results are from some one or two very large datasets (like the weather or labor statistics), and it overwhelms the page.
I can't show you *all* the correlations, because my database would get too large and this page would take a very long time to load. Instead I opt to show you a subset, and I sort them by a magic system score. It starts with the correlation, but penalizes variables that repeat from the same dataset. (It also gives a bonus to variables I happen to find interesting.)