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 Mars correlates with...
| Variable | Correlation | Years | Has img? |
| Votes for Libertarian Senators in Missouri | r=0.81 | 12yrs | No |
| Air quality in Madison, Indiana | r=0.68 | 7yrs | No |
| Rain in Paris | r=0.62 | 17yrs | No |
| Total length of 'Be Smart' science YouTube videos | r=0.55 | 11yrs | No |
| How good Casually Explained YouTube video titles are | r=0.55 | 9yrs | No |
| Biomass power generated in United Arab Emirates | r=0.52 | 9yrs | No |
| Rain in Paris | r=0.47 | 17yrs | No |
| Runs Scored by the losing team in the World Series | r=-0.52 | 39yrs | No |
| Total runs scored in the World Series | r=-0.55 | 39yrs | No |
| Votes for the Republican Presidential candidate in North Dakota | r=-0.82 | 12yrs | No |
The distance between Jupiter and Mars 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.)