latest_ny_times_counties_with_populations (view)
Data license: LICENSE · Data source: The New York Times · About: simonw/covid-19-datasette
254 rows where state = "Texas" sorted by cases_per_million descending
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state 1
- Texas · 254 ✖
date | county | state | fips | cases | deaths | population | deaths_per_million | cases_per_million ▲ |
---|---|---|---|---|---|---|---|---|
2022-05-13 | Collingsworth | Texas | 48087 | 702 | 16 | 2920 | 5479 | 240410 |
2022-05-13 | Menard | Texas | 48327 | 513 | 12 | 2138 | 5612 | 239943 |
2022-05-13 | Hidalgo | Texas | 48215 | 207289 | 3909 | 868707 | 4499 | 238617 |
2022-05-13 | Motley | Texas | 48345 | 286 | 13 | 1200 | 10833 | 238333 |
2022-05-13 | Kleberg | Texas | 48273 | 7304 | 147 | 30680 | 4791 | 238070 |
2022-05-13 | Montague | Texas | 48337 | 4694 | 129 | 19818 | 6509 | 236855 |
2022-05-13 | Culberson | Texas | 48109 | 514 | 14 | 2171 | 6448 | 236757 |
2022-05-13 | Real | Texas | 48385 | 817 | 25 | 3452 | 7242 | 236674 |
2022-05-13 | Wheeler | Texas | 48483 | 1193 | 23 | 5056 | 4549 | 235957 |
2022-05-13 | Ward | Texas | 48475 | 2830 | 44 | 11998 | 3667 | 235872 |
2022-05-13 | McLennan | Texas | 48309 | 60473 | 902 | 256623 | 3514 | 235649 |
2022-05-13 | Dawson | Texas | 48115 | 2998 | 94 | 12728 | 7385 | 235543 |
2022-05-13 | Fort Bend | Texas | 48157 | 189442 | 1260 | 811688 | 1552 | 233392 |
2022-05-13 | Montgomery | Texas | 48339 | 141687 | 1291 | 607391 | 2125 | 233271 |
2022-05-13 | Runnels | Texas | 48399 | 2393 | 66 | 10264 | 6430 | 233144 |
2022-05-13 | Baylor | Texas | 48023 | 818 | 32 | 3509 | 9119 | 233114 |
2022-05-13 | Hamilton | Texas | 48193 | 1972 | 33 | 8461 | 3900 | 233069 |
2022-05-13 | Coryell | Texas | 48099 | 17626 | 211 | 75951 | 2778 | 232070 |
2022-05-13 | Somervell | Texas | 48425 | 2116 | 36 | 9128 | 3943 | 231814 |
2022-05-13 | Brooks | Texas | 48047 | 1642 | 52 | 7093 | 7331 | 231495 |
2022-05-13 | Midland | Texas | 48329 | 40910 | 496 | 176832 | 2804 | 231349 |
2022-05-13 | Jones | Texas | 48253 | 4643 | 93 | 20083 | 4630 | 231190 |
2022-05-13 | Winkler | Texas | 48495 | 1846 | 34 | 8010 | 4244 | 230461 |
2022-05-13 | Burnet | Texas | 48053 | 11095 | 171 | 48155 | 3551 | 230401 |
2022-05-13 | Guadalupe | Texas | 48187 | 38361 | 398 | 166847 | 2385 | 229917 |
2022-05-13 | Williamson | Texas | 48491 | 135522 | 935 | 590551 | 1583 | 229483 |
2022-05-13 | Matagorda | Texas | 48321 | 8374 | 175 | 36643 | 4775 | 228529 |
2022-05-13 | Cottle | Texas | 48101 | 319 | 9 | 1398 | 6437 | 228183 |
2022-05-13 | Upton | Texas | 48461 | 833 | 18 | 3657 | 4922 | 227782 |
2022-05-13 | McMullen | Texas | 48311 | 169 | 9 | 743 | 12113 | 227456 |
2022-05-13 | Gonzales | Texas | 48177 | 4736 | 99 | 20837 | 4751 | 227287 |
2022-05-13 | Terry | Texas | 48445 | 2790 | 84 | 12337 | 6808 | 226148 |
2022-05-13 | Ector | Texas | 48135 | 37544 | 703 | 166223 | 4229 | 225865 |
2022-05-13 | Sutton | Texas | 48435 | 848 | 12 | 3776 | 3177 | 224576 |
2022-05-13 | Reagan | Texas | 48383 | 859 | 14 | 3849 | 3637 | 223174 |
2022-05-13 | Comal | Texas | 48091 | 34812 | 551 | 156209 | 3527 | 222855 |
2022-05-13 | Lipscomb | Texas | 48295 | 720 | 16 | 3233 | 4948 | 222703 |
2022-05-13 | Young | Texas | 48503 | 4002 | 94 | 18010 | 5219 | 222209 |
2022-05-13 | Bosque | Texas | 48035 | 4130 | 70 | 18685 | 3746 | 221032 |
2022-05-13 | Wharton | Texas | 48481 | 9175 | 214 | 41556 | 5149 | 220786 |
2022-05-13 | Jackson | Texas | 48239 | 3258 | 59 | 14760 | 3997 | 220731 |
2022-05-13 | Falls | Texas | 48145 | 3797 | 65 | 17297 | 3757 | 219517 |
2022-05-13 | Camp | Texas | 48063 | 2873 | 75 | 13094 | 5727 | 219413 |
2022-05-13 | Harris | Texas | 48201 | 1032781 | 10972 | 4713325 | 2327 | 219119 |
2022-05-13 | Hood | Texas | 48221 | 13472 | 274 | 61643 | 4444 | 218548 |
2022-05-13 | Mitchell | Texas | 48335 | 1864 | 49 | 8545 | 5734 | 218139 |
2022-05-13 | Dallas | Texas | 48113 | 573644 | 6772 | 2635516 | 2569 | 217659 |
2022-05-13 | Limestone | Texas | 48293 | 5100 | 124 | 23437 | 5290 | 217604 |
2022-05-13 | Bowie | Texas | 48037 | 20222 | 432 | 93245 | 4632 | 216869 |
2022-05-13 | Wilson | Texas | 48493 | 11032 | 157 | 51070 | 3074 | 216017 |
2022-05-13 | Bailey | Texas | 48017 | 1511 | 39 | 7000 | 5571 | 215857 |
2022-05-13 | Blanco | Texas | 48031 | 2568 | 34 | 11931 | 2849 | 215237 |
2022-05-13 | Leon | Texas | 48289 | 3728 | 93 | 17404 | 5343 | 214203 |
2022-05-13 | Kenedy | Texas | 48261 | 86 | 2 | 404 | 4950 | 212871 |
2022-05-13 | Lavaca | Texas | 48285 | 4271 | 120 | 20154 | 5954 | 211918 |
2022-05-13 | Shackelford | Texas | 48417 | 691 | 12 | 3265 | 3675 | 211638 |
2022-05-13 | Hardin | Texas | 48199 | 12078 | 251 | 57602 | 4357 | 209680 |
2022-05-13 | Callahan | Texas | 48059 | 2920 | 72 | 13943 | 5163 | 209424 |
2022-05-13 | Martin | Texas | 48317 | 1207 | 26 | 5771 | 4505 | 209149 |
2022-05-13 | Collin | Texas | 48085 | 215831 | 1507 | 1034730 | 1456 | 208586 |
2022-05-13 | Nolan | Texas | 48353 | 3065 | 99 | 14714 | 6728 | 208305 |
2022-05-13 | Franklin | Texas | 48159 | 2228 | 42 | 10725 | 3916 | 207738 |
2022-05-13 | Liberty | Texas | 48291 | 18210 | 404 | 88219 | 4579 | 206418 |
2022-05-13 | Erath | Texas | 48143 | 8790 | 123 | 42698 | 2880 | 205864 |
2022-05-13 | Victoria | Texas | 48469 | 18919 | 413 | 92084 | 4485 | 205453 |
2022-05-13 | Garza | Texas | 48169 | 1279 | 28 | 6229 | 4495 | 205329 |
2022-05-13 | San Saba | Texas | 48411 | 1242 | 35 | 6055 | 5780 | 205119 |
2022-05-13 | Roberts | Texas | 48393 | 175 | 2 | 854 | 2341 | 204918 |
2022-05-13 | Dickens | Texas | 48125 | 453 | 16 | 2211 | 7236 | 204884 |
2022-05-13 | Andrews | Texas | 48003 | 3822 | 72 | 18705 | 3849 | 204330 |
2022-05-13 | Denton | Texas | 48121 | 181158 | 1354 | 887207 | 1526 | 204189 |
2022-05-13 | Morris | Texas | 48343 | 2529 | 73 | 12388 | 5892 | 204149 |
2022-05-13 | Hudspeth | Texas | 48229 | 989 | 18 | 4886 | 3683 | 202415 |
2022-05-13 | Kinney | Texas | 48271 | 741 | 11 | 3667 | 2999 | 202072 |
2022-05-13 | Coleman | Texas | 48083 | 1646 | 71 | 8175 | 8685 | 201345 |
2022-05-13 | Gillespie | Texas | 48171 | 5426 | 109 | 26988 | 4038 | 201052 |
2022-05-13 | Harrison | Texas | 48203 | 13370 | 227 | 66553 | 3410 | 200892 |
2022-05-13 | Clay | Texas | 48077 | 2096 | 35 | 10471 | 3342 | 200171 |
2022-05-13 | Rusk | Texas | 48401 | 10870 | 233 | 54406 | 4282 | 199794 |
2022-05-13 | Grayson | Texas | 48181 | 27166 | 636 | 136212 | 4669 | 199439 |
2022-05-13 | Milam | Texas | 48331 | 4950 | 102 | 24823 | 4109 | 199411 |
2022-05-13 | Medina | Texas | 48325 | 10269 | 199 | 51584 | 3857 | 199073 |
2022-05-13 | Panola | Texas | 48365 | 4609 | 129 | 23194 | 5561 | 198715 |
2022-05-13 | Stephens | Texas | 48429 | 1846 | 46 | 9366 | 4911 | 197095 |
2022-05-13 | Freestone | Texas | 48161 | 3880 | 82 | 19717 | 4158 | 196784 |
2022-05-13 | Hale | Texas | 48189 | 6571 | 245 | 33406 | 7334 | 196701 |
2022-05-13 | Jefferson | Texas | 48245 | 49316 | 843 | 251565 | 3351 | 196036 |
2022-05-13 | Hopkins | Texas | 48223 | 7264 | 180 | 37084 | 4853 | 195879 |
2022-05-13 | Smith | Texas | 48423 | 45581 | 968 | 232751 | 4158 | 195835 |
2022-05-13 | San Jacinto | Texas | 48407 | 5611 | 102 | 28859 | 3534 | 194428 |
2022-05-13 | Fannin | Texas | 48147 | 6897 | 183 | 35514 | 5152 | 194205 |
2022-05-13 | Austin | Texas | 48015 | 5818 | 73 | 30032 | 2430 | 193726 |
2022-05-13 | Red River | Texas | 48387 | 2304 | 67 | 12023 | 5572 | 191632 |
2022-05-13 | Nacogdoches | Texas | 48347 | 12413 | 258 | 65204 | 3956 | 190371 |
2022-05-13 | Upshur | Texas | 48459 | 7926 | 186 | 41753 | 4454 | 189830 |
2022-05-13 | Sterling | Texas | 48431 | 245 | 6 | 1291 | 4647 | 189775 |
2022-05-13 | Fayette | Texas | 48149 | 4796 | 105 | 25346 | 4142 | 189221 |
2022-05-13 | Schleicher | Texas | 48413 | 528 | 9 | 2793 | 3222 | 189044 |
2022-05-13 | Howard | Texas | 48227 | 6876 | 184 | 36664 | 5018 | 187540 |
2022-05-13 | King | Texas | 48269 | 51 | 0 | 272 | 0 | 187500 |
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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;