latest_ny_times_counties_with_populations (view)

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⚠️ Consult the README for warnings about using and building on this data. Also review Why It’s So Freaking Hard To Make A Good COVID-19 Model and Ten Considerations Before You Create Another Chart About COVID-19.

Data license: LICENSE · Data source: The New York Times · About: simonw/covid-19-datasette

65 rows where state = "South Dakota" sorted by cases_per_million descending

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state 1

  • South Dakota · 65 ✖
date county state fips cases deaths population deaths_per_million cases_per_million ▲
2022-05-13 Dewey South Dakota 46041 3139 44 5892 7467 532756
2022-05-13 Bon Homme South Dakota 46009 2292 39 6901 5651 332125
2022-05-13 Potter South Dakota 46107 703 7 2153 3251 326521
2022-05-13 Lyman South Dakota 46085 1205 12 3781 3173 318698
2022-05-13 Charles Mix South Dakota 46023 2942 35 9292 3766 316616
2022-05-13 Buffalo South Dakota 46017 620 18 1962 9174 316004
2022-05-13 Codington South Dakota 46029 8474 101 28009 3605 302545
2022-05-13 Davison South Dakota 46035 5907 80 19775 4045 298710
2022-05-13 Minnehaha South Dakota 46099 57428 519 193134 2687 297347
2022-05-13 Aurora South Dakota 46003 805 17 2751 6179 292620
2022-05-13 Todd South Dakota 46121 2975 53 10177 5207 292325
2022-05-13 Grant South Dakota 46051 2047 51 7052 7231 290272
2022-05-13 Pennington South Dakota 46103 32903 342 113775 3005 289193
2022-05-13 Kingsbury South Dakota 46077 1340 22 4939 4454 271309
2022-05-13 Fall River South Dakota 46047 1807 39 6713 5809 269179
2022-05-13 Brule South Dakota 46015 1415 20 5297 3775 267132
2022-05-13 Brown South Dakota 46013 10344 121 38839 3115 266330
2022-05-13 Butte South Dakota 46019 2757 45 10429 4314 264358
2022-05-13 Corson South Dakota 46031 1070 17 4086 4160 261869
2022-05-13 Yankton South Dakota 46135 5929 59 22814 2586 259884
2022-05-13 Mellette South Dakota 46095 527 8 2061 3881 255701
2022-05-13 Lawrence South Dakota 46081 6605 83 25844 3211 255571
2022-05-13 Lincoln South Dakota 46083 15590 102 61128 1668 255038
2022-05-13 Gregory South Dakota 46053 1065 34 4185 8124 254480
2022-05-13 Tripp South Dakota 46123 1382 24 5441 4410 253997
2022-05-13 Union South Dakota 46127 4026 52 15932 3263 252698
2022-05-13 Beadle South Dakota 46005 4596 60 18453 3251 249065
2022-05-13 Faulk South Dakota 46049 572 16 2299 6959 248803
2022-05-13 Meade South Dakota 46093 7042 64 28332 2258 248552
2022-05-13 Clay South Dakota 46027 3493 21 14070 1492 248258
2022-05-13 Edmunds South Dakota 46045 949 16 3829 4178 247845
2022-05-13 Hughes South Dakota 46065 4335 58 17526 3309 247346
2022-05-13 Sanborn South Dakota 46111 575 6 2344 2559 245307
2022-05-13 Hamlin South Dakota 46057 1508 41 6164 6651 244646
2022-05-13 Walworth South Dakota 46129 1315 26 5435 4783 241950
2022-05-13 McCook South Dakota 46087 1348 31 5586 5549 241317
2022-05-13 Ziebach South Dakota 46137 664 11 2756 3991 240928
2022-05-13 Deuel South Dakota 46039 1043 12 4351 2757 239715
2022-05-13 Day South Dakota 46037 1295 35 5424 6452 238753
2022-05-13 Perkins South Dakota 46105 684 18 2865 6282 238743
2022-05-13 Haakon South Dakota 46055 452 12 1899 6319 238020
2022-05-13 Hutchinson South Dakota 46067 1733 36 7291 4937 237690
2022-05-13 Hyde South Dakota 46069 307 8 1301 6149 235972
2022-05-13 Turner South Dakota 46125 1969 62 8384 7395 234852
2022-05-13 Bennett South Dakota 46007 789 14 3365 4160 234472
2022-05-13 Roberts South Dakota 46109 2436 53 10394 5099 234365
2022-05-13 Douglas South Dakota 46043 684 16 2921 5477 234166
2022-05-13 Brookings South Dakota 46011 8149 52 35077 1482 232317
2022-05-13 Custer South Dakota 46033 2034 26 8972 2897 226705
2022-05-13 Spink South Dakota 46115 1418 36 6376 5646 222396
2022-05-13 Clark South Dakota 46025 804 9 3736 2408 215203
2022-05-13 Moody South Dakota 46101 1386 28 6576 4257 210766
2022-05-13 Miner South Dakota 46097 457 13 2216 5866 206227
2022-05-13 Jerauld South Dakota 46073 415 20 2013 9935 206159
2022-05-13 Stanley South Dakota 46117 637 7 3098 2259 205616
2022-05-13 Jones South Dakota 46075 177 2 903 2214 196013
2022-05-13 Campbell South Dakota 46021 268 7 1376 5087 194767
2022-05-13 Hanson South Dakota 46061 655 6 3453 1737 189690
2022-05-13 Jackson South Dakota 46071 632 21 3344 6279 188995
2022-05-13 Lake South Dakota 46079 2335 28 12797 2188 182464
2022-05-13 McPherson South Dakota 46089 426 9 2379 3783 179066
2022-05-13 Sully South Dakota 46119 245 3 1391 2156 176132
2022-05-13 Hand South Dakota 46059 562 12 3191 3760 176120
2022-05-13 Marshall South Dakota 46091 796 13 4935 2634 161296
2022-05-13 Harding South Dakota 46063 201 3 1298 2311 154853

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CREATE VIEW latest_ny_times_counties_with_populations AS 
    select
      ny_times_us_counties.date,
      ny_times_us_counties.county,
      ny_times_us_counties.state,
      ny_times_us_counties.fips,
      ny_times_us_counties.cases,
      ny_times_us_counties.deaths,
      us_census_county_populations_2019.population,
      1000000 * ny_times_us_counties.deaths / us_census_county_populations_2019.population as deaths_per_million,
      1000000 * ny_times_us_counties.cases / us_census_county_populations_2019.population as cases_per_million
    from
      ny_times_us_counties
      join us_census_county_populations_2019 on ny_times_us_counties.fips = us_census_county_populations_2019.fips
    where
      "date" = (
        select
          max(date)
        from
          ny_times_us_counties
      )
    order by
      deaths_per_million desc;