Top variables that correlate with Popularity of the first name Chandra

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Data source: US Social Security Administration
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Popularity of the first name Chandra correlates with...

Variable	Correlation	Years	Has img?
The number of locker room attendants in Michigan	r=0.88	17yrs	Yes!

Popularity of the first name Chandra also correlates with...

Variable	Correlation	Years	Sys. Score
Average number of milk cows in the United States	r=0.95	40yrs	452
Kerosene used in Mexico	r=0.98	40yrs	432
Kerosene used in Turkiye	r=0.98	40yrs	432
Petroluem consumption in Bulgaria	r=0.96	40yrs	428
Carjackings in the US	r=0.95	25yrs	421
Burglaries in Colorado	r=0.98	35yrs	416
Arson in New York	r=0.97	35yrs	414
The marriage rate in Nevada	r=0.96	21yrs	411
The marriage rate in Tennessee	r=0.96	21yrs	411
Physical album shipment volume in the United States	r=0.95	21yrs	410
Google searches for 'learn spanish'	r=0.95	16yrs	406
Gasoline pumped in Bulgaria	r=0.96	40yrs	398
Remaining Forest Cover in the Brazilian Amazon	r=0.94	33yrs	396
Air pollution in Oxnard, California	r=0.95	40yrs	392
Air pollution in San Diego, California	r=0.95	40yrs	392
The number of switchboard operators in Michigan	r=0.96	17yrs	387
The number of office clerks in Minnesota	r=0.96	17yrs	387
The number of prepress technicians and workers in North Carolina	r=0.96	17yrs	387
Burglaries in Oregon	r=0.97	35yrs	384
The distance between Neptune and Mercury	r=0.92	45yrs	380
The marriage rate in Virginia	r=0.95	21yrs	380
The distance between Neptune and Earth	r=0.91	45yrs	379
The distance between Neptune and the moon	r=0.91	45yrs	379
US birth rates of triplets or more	r=0.9	18yrs	376
Robberies in Oregon	r=0.97	35yrs	374
GMO use in cotton in North Carolina	r=0.96	20yrs	373
US milk fat used to produce fluid beverage milk	r=0.91	20yrs	372
The wind speed in Nashville	r=0.91	35yrs	369
Cottage cheese consumption	r=0.9	30yrs	368
Google searches for 'snoop dog'	r=0.9	16yrs	368
Google searches for 'black holes'	r=0.9	16yrs	368
Customer satisfaction with Verizon	r=0.88	26yrs	366
Viewership count for Days of Our Lives	r=0.86	45yrs	364
Air pollution in Los Angeles	r=0.94	40yrs	363
Burglaries in New York	r=0.96	35yrs	362
Highest Nielsen rating for a TV show each year	r=0.86	45yrs	360
The number of brickmasons in Ohio	r=0.96	17yrs	357
US household spending on books	r=0.94	20yrs	357
Kerosene used in Ecuador	r=0.94	40yrs	356
US household spending on clothing for men	r=0.93	20yrs	356
Burglaries in California	r=0.96	35yrs	352
The divorce rate in Alabama	r=0.94	21yrs	350
The number of typists in Washington	r=0.96	17yrs	347
Kerosene used in Uruguay	r=0.93	40yrs	344
Burglaries in Oklahoma	r=0.95	35yrs	341
The marriage rate in Ohio	r=0.94	21yrs	338
The number of typists in Florida	r=0.95	17yrs	336
Kerosene used in Venezuela	r=0.93	40yrs	334
Air pollution in New York City	r=0.93	40yrs	332
The marriage rate in South Carolina	r=0.94	21yrs	328
The number of sewing machine operators in North Carolina	r=0.95	17yrs	326
US average milk-fat content of frozen dairy products	r=0.94	20yrs	324
Kerosene used in Bolivia	r=0.92	40yrs	322
Air pollution in Los Angeles	r=0.92	40yrs	320
Burglary rates in the US	r=0.93	35yrs	318
The divorce rate in Tennessee	r=0.93	21yrs	318
Kerosene used in Portugal	r=0.92	40yrs	312
The marriage rate in Arizona	r=0.93	21yrs	306
Air pollution in San Diego, California	r=0.91	40yrs	306
Arson in United States	r=0.91	35yrs	305
Petroluem consumption in Romania	r=0.92	40yrs	302
The marriage rate in Arkansas	r=0.93	21yrs	296
Kerosene used in Romania	r=0.92	40yrs	292
The marriage rate in Kentucky	r=0.93	21yrs	286
The number of telemarketers in Illinois	r=0.94	17yrs	286
Gasoline pumped in Somalia	r=0.92	40yrs	282
Burglaries in Rhode Island	r=0.95	35yrs	281
The marriage rate in Wyoming	r=0.93	21yrs	276
The number of prepress technicians and workers in Maine	r=0.95	17yrs	276
Kerosene used in Hong Kong	r=0.91	40yrs	271
Burglaries in Washington	r=0.95	35yrs	271
The divorce rate in Oregon	r=0.92	21yrs	266
The number of postal service machine operators in Massachusetts	r=0.95	17yrs	266
Motor vehicle thefts in Oklahoma	r=0.95	35yrs	261
The number of cutters and trimmers, hand in North Carolina	r=0.95	17yrs	256
The marriage rate in Idaho	r=0.92	21yrs	255
Petroluem consumption in Uzbekistan	r=0.93	28yrs	252
Arson in Colorado	r=0.94	35yrs	250
The number of CEOs in Ohio	r=0.94	17yrs	246
The divorce rate in North Carolina	r=0.91	21yrs	245
Burglaries in Michigan	r=0.94	35yrs	240
Jet fuel used in Ukraine	r=0.91	28yrs	239
The number of switchboard operators in Ohio	r=0.95	17yrs	236
The marriage rate in South Dakota	r=0.91	21yrs	234
Burglaries in New Mexico	r=0.94	35yrs	230
The number of typists in Ohio	r=0.95	17yrs	226
The marriage rate in Wisconsin	r=0.91	21yrs	224
Burglaries in Texas	r=0.94	35yrs	220
The number of postal service machine operators in Rhode Island	r=0.95	17yrs	216
Burglaries in Connecticut	r=0.94	35yrs	210
Electricity generation in Liberia	r=0.88	40yrs	210
The number of sewing machine operators in Tennessee	r=0.95	17yrs	206
Motor vehicle thefts in Massachusetts	r=0.94	35yrs	200
Gasoline pumped in Cuba	r=0.89	40yrs	198
The number of typists in Texas	r=0.95	17yrs	196
Robberies in Michigan	r=0.94	35yrs	190
The number of prepress technicians and workers in Wisconsin	r=0.95	17yrs	186
Kerosene used in Argentina	r=0.88	40yrs	186
Kerosene used in Brazil	r=0.88	40yrs	176
The number of typists in Arizona	r=0.94	17yrs	174
Kerosene used in Cuba	r=0.88	40yrs	166

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^{What is Sys. Score?} 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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