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Data source: Bureau of Larbor Statistics
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The number of telecommunications line installers and repairers in South Dakota correlates with...

VariableCorrelationYearsSys. Score
Total views on OverSimplified YouTube videosr=0.977yrs354
Total likes of OverSimplified YouTube videosr=0.967yrs353
Total comments on OverSimplified YouTube videosr=0.917yrs300
How 'hip and with it' 3Blue1Brown YouTube video titles arer=0.878yrs236
Final Match Score Difference in the Volkswagen Challenger Setr=0.7310yrs136
Grocery store spend in South Dakotar=0.6418yrs128
Miss America's ager=0.5619yrs124
The number of movies Meryl Streep appeared inr=0.5320yrs123
Associates degrees awarded in Library sciencer=0.6211yrs122
The number of movies Joaquin Phoenix appeared inr=0.5220yrs122
Worldwide revenue from Harley Davidson motorcyclesr=0.6411yrs120
xkcd comics published about politicsr=0.5516yrs120
Total number of batters faced by Joe Nathanr=0.5914yrs116
Mizuho Financial Group's stock price (MFG)r=0.5616yrs116
U.S. hotel industry occupancy rater=0.612yrs115
Carnival Corporation's stock price (CCL)r=0.5220yrs114
Popularity of the 'slaps roof of car' memer=0.4917yrs114
Average viewer count per season of "How I Met Your Mother"r=0.629yrs111
Shell's stock price (SHEL)r=0.520yrs111
Hot days in Sydneyr=0.4920yrs111
How cool 3Blue1Brown YouTube video titles arer=0.88yrs110
Maria Sharapova's WTA Title Countr=0.5215yrs109
Number of public school students in 7th grader=0.4620yrs108
Nuclear power generation in Switzerlandr=0.4819yrs108
Biomass power generated in Panamar=0.4619yrs106
Highway diesel consumption in USr=0.619yrs104
Liquefied petroleum gas used in Surinamer=0.4719yrs104
US hotel industry's revenue per available roomr=0.5712yrs100
Popularity of the 'hard pills to swallow' memer=0.4517yrs98
xkcd comics published about timer=0.4616yrs97
How good 3Blue1Brown YouTube video titles arer=0.768yrs94
Searches for 'never gonna give you up'r=-0.6717yrs88
Google searches for 'Brexit'r=0.467yrs84
The number of movies Jude Law appeared inr=0.4520yrs81
Average length of Casually Explained YouTube videosr=0.738yrs80
Global annual sales of the Xbox 360r=-0.7410yrs80
Rain in Sydneyr=-0.6320yrs80
Rain in Sydneyr=-0.620yrs78
Bankruptcies in Californiar=-0.7111yrs75
Brad Pitt's net worthr=-0.5620yrs74
Popularity of the first name Jelanir=-0.620yrs74
Automotive recalls for issues with Steeringr=-0.5720yrs73
Petroluem consumption in Luxembourgr=0.4520yrs72
The number of movies Nicolas Cage appeared inr=0.4520yrs71
Greece's annual import volumer=-0.5520yrs71
Automotive recalls issued by Hyundai Motor Americar=-0.520yrs70
Asthma attacks in American childrenr=-0.5317yrs70
Google searches for 'Johnny Depp'r=-0.5419yrs70
How trendy SciShow Space YouTube video titles arer=0.729yrs69
Craig Bellamy's appearances in matches for the Wales national teamr=0.5711yrs69
Powerball lottery numbersr=-0.5613yrs68
Annual U.S. inflation rater=-0.5120yrs67
Annual Changes in U.S. PPI for Commoditiesr=-0.5120yrs67
Popularity of the first name Tater=-0.5220yrs66
Google searches for 'who is elon musk'r=-0.4818yrs64
Customer satisfaction with CNN.com (AT&T)r=-0.4719yrs64
How professional-sounding Simone Giertz's YouTube video titles arer=0.729yrs59
The number of movies Penelope Cruz appeared inr=-0.6920yrs58
Solar power generated in Cabo Verder=0.4912yrs53
Tesla's stock price (TSLA)r=-0.6912yrs53
Assist Tackle Count by Champ Bailey in a Given Yearr=0.511yrs49
How insightful AsapSCIENCE YouTube video titles arer=0.6911yrs46
Popularity of the 'rickroll' memer=-0.5517yrs46
Rain in Sydneyr=-0.5820yrs46
Biomass power generated in Malir=0.4712yrs40
Average number of comments on Casually Explained YouTube videosr=0.718yrs36
Number of home runs hit by Matt Kempr=-0.7215yrs33
Number of Earthquakes in the United Statesr=-0.6910yrs32
NVIDIA's stock price (NVDA)r=-0.5220yrs31
How professional-sounding SciShow Space YouTube video titles arer=0.699yrs24
Rainfall in San Franciscor=-0.5620yrs22
Wipro's stock price (WIT)r=-0.5320yrs19
The number of movies Ralph Fiennes appeared inr=-0.5420yrs18
Jet fuel used in Seychellesr=-0.5619yrs10
Average number of comments on AsapSCIENCE YouTube videosr=0.6411yrs9
Infosys' stock price (INFY)r=-0.5120yrs7
The number of movies Kate Hudson appeared inr=-0.5320yrs6
How professional-sounding AsapSCIENCE YouTube video titles arer=0.6311yrs-2
Lionel Messi's match count with Argentinar=-0.5418yrs-2
Fossil fuel use in Irelandr=-0.5219yrs-2
The number of movies Jeremy Irons appeared inr=-0.5220yrs-4
Advanced Micro Devices' stock price (AMD)r=-0.4820yrs-6
Liquefied petroleum gas used in United Statesr=-0.5220yrs-14
The average number of likes on Casually Explained YouTube videosr=0.78yrs-15
Marvell Technology's stock price (MRVL)r=-0.4820yrs-16
The number of movies Tom Hanks appeared inr=-0.4820yrs-18
Average views of OverSimplified YouTube videosr=0.77yrs-26
ON Semiconductor's stock price (ON)r=-0.4919yrs-26
The number of movies Sigourney Weaver appeared inr=-0.4920yrs-28
DexCom's stock price (DXCM)r=-0.5117yrs-36
How 'hip and with it' SciShow Space YouTube video titles arer=0.669yrs-40
The number of movies Vin Diesel appeared inr=-0.4720yrs-40
West Pharmaceutical Services' stock price (WST)r=-0.4820yrs-46
The number of movies Andrew Garfield appeared inr=-0.4918yrs-50
Total length of OverSimplified YouTube videosr=0.667yrs-52
Monolithic Power Systems' stock price (MPWR)r=-0.518yrs-56
The number of movies Jim Carrey appeared inr=-0.4720yrs-60
Average views of Casually Explained YouTube videosr=0.658yrs-62
Synopsys' stock price (SNPS)r=-0.4720yrs-67
How insightful SciShow Space YouTube video titles arer=0.639yrs-74


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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.)
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