ny_times_us_counties
Data license: LICENSE · Data source: The New York Times · About: simonw/covid-19-datasette
67 rows where date = "2021-05-21" and state = "Pennsylvania" sorted by date descending
This data as json, yaml, Notebook, copyable, CSV (advanced)
Suggested facets: date (date)
Link | rowid | date ▲ | county | state | fips | cases | deaths |
---|---|---|---|---|---|---|---|
1341492 | 1341492 | 2021-05-21 | Adams | Pennsylvania | 42001 | 9490 | 182 |
1341493 | 1341493 | 2021-05-21 | Allegheny | Pennsylvania | 42003 | 100719 | 1958 |
1341494 | 1341494 | 2021-05-21 | Armstrong | Pennsylvania | 42005 | 5940 | 138 |
1341495 | 1341495 | 2021-05-21 | Beaver | Pennsylvania | 42007 | 15322 | 382 |
1341496 | 1341496 | 2021-05-21 | Bedford | Pennsylvania | 42009 | 4557 | 138 |
1341497 | 1341497 | 2021-05-21 | Berks | Pennsylvania | 42011 | 47591 | 1022 |
1341498 | 1341498 | 2021-05-21 | Blair | Pennsylvania | 42013 | 13236 | 334 |
1341499 | 1341499 | 2021-05-21 | Bradford | Pennsylvania | 42015 | 5993 | 89 |
1341500 | 1341500 | 2021-05-21 | Bucks | Pennsylvania | 42017 | 60307 | 1290 |
1341501 | 1341501 | 2021-05-21 | Butler | Pennsylvania | 42019 | 17325 | 413 |
1341502 | 1341502 | 2021-05-21 | Cambria | Pennsylvania | 42021 | 14435 | 430 |
1341503 | 1341503 | 2021-05-21 | Cameron | Pennsylvania | 42023 | 301 | 6 |
1341504 | 1341504 | 2021-05-21 | Carbon | Pennsylvania | 42025 | 6309 | 170 |
1341505 | 1341505 | 2021-05-21 | Centre | Pennsylvania | 42027 | 16747 | 222 |
1341506 | 1341506 | 2021-05-21 | Chester | Pennsylvania | 42029 | 40410 | 804 |
1341507 | 1341507 | 2021-05-21 | Clarion | Pennsylvania | 42031 | 3163 | 92 |
1341508 | 1341508 | 2021-05-21 | Clearfield | Pennsylvania | 42033 | 8512 | 146 |
1341509 | 1341509 | 2021-05-21 | Clinton | Pennsylvania | 42035 | 3659 | 65 |
1341510 | 1341510 | 2021-05-21 | Columbia | Pennsylvania | 42037 | 5789 | 133 |
1341511 | 1341511 | 2021-05-21 | Crawford | Pennsylvania | 42039 | 7331 | 149 |
1341512 | 1341512 | 2021-05-21 | Cumberland | Pennsylvania | 42041 | 20275 | 520 |
1341513 | 1341513 | 2021-05-21 | Dauphin | Pennsylvania | 42043 | 25758 | 546 |
1341514 | 1341514 | 2021-05-21 | Delaware | Pennsylvania | 42045 | 51869 | 1432 |
1341515 | 1341515 | 2021-05-21 | Elk | Pennsylvania | 42047 | 2854 | 39 |
1341516 | 1341516 | 2021-05-21 | Erie | Pennsylvania | 42049 | 20831 | 411 |
1341517 | 1341517 | 2021-05-21 | Fayette | Pennsylvania | 42051 | 13060 | 315 |
1341518 | 1341518 | 2021-05-21 | Forest | Pennsylvania | 42053 | 1428 | 21 |
1341519 | 1341519 | 2021-05-21 | Franklin | Pennsylvania | 42055 | 15180 | 370 |
1341520 | 1341520 | 2021-05-21 | Fulton | Pennsylvania | 42057 | 1337 | 15 |
1341521 | 1341521 | 2021-05-21 | Greene | Pennsylvania | 42059 | 3252 | 40 |
1341522 | 1341522 | 2021-05-21 | Huntingdon | Pennsylvania | 42061 | 5079 | 131 |
1341523 | 1341523 | 2021-05-21 | Indiana | Pennsylvania | 42063 | 6258 | 175 |
1341524 | 1341524 | 2021-05-21 | Jefferson | Pennsylvania | 42065 | 3292 | 98 |
1341525 | 1341525 | 2021-05-21 | Juniata | Pennsylvania | 42067 | 2115 | 86 |
1341526 | 1341526 | 2021-05-21 | Lackawanna | Pennsylvania | 42069 | 18276 | 471 |
1341527 | 1341527 | 2021-05-21 | Lancaster | Pennsylvania | 42071 | 54797 | 1143 |
1341528 | 1341528 | 2021-05-21 | Lawrence | Pennsylvania | 42073 | 7513 | 210 |
1341529 | 1341529 | 2021-05-21 | Lebanon | Pennsylvania | 42075 | 15970 | 286 |
1341530 | 1341530 | 2021-05-21 | Lehigh | Pennsylvania | 42077 | 39388 | 851 |
1341531 | 1341531 | 2021-05-21 | Luzerne | Pennsylvania | 42079 | 31542 | 807 |
1341532 | 1341532 | 2021-05-21 | Lycoming | Pennsylvania | 42081 | 11755 | 284 |
1341533 | 1341533 | 2021-05-21 | McKean | Pennsylvania | 42083 | 3722 | 71 |
1341534 | 1341534 | 2021-05-21 | Mercer | Pennsylvania | 42085 | 9506 | 256 |
1341535 | 1341535 | 2021-05-21 | Mifflin | Pennsylvania | 42087 | 5359 | 178 |
1341536 | 1341536 | 2021-05-21 | Monroe | Pennsylvania | 42089 | 14600 | 312 |
1341537 | 1341537 | 2021-05-21 | Montgomery | Pennsylvania | 42091 | 69757 | 1708 |
1341538 | 1341538 | 2021-05-21 | Montour | Pennsylvania | 42093 | 1999 | 66 |
1341539 | 1341539 | 2021-05-21 | Northampton | Pennsylvania | 42095 | 35509 | 708 |
1341540 | 1341540 | 2021-05-21 | Northumberland | Pennsylvania | 42097 | 9536 | 356 |
1341541 | 1341541 | 2021-05-21 | Perry | Pennsylvania | 42099 | 3793 | 100 |
1341542 | 1341542 | 2021-05-21 | Philadelphia | Pennsylvania | 42101 | 151949 | 3633 |
1341543 | 1341543 | 2021-05-21 | Pike | Pennsylvania | 42103 | 3950 | 54 |
1341544 | 1341544 | 2021-05-21 | Potter | Pennsylvania | 42105 | 1167 | 23 |
1341545 | 1341545 | 2021-05-21 | Schuylkill | Pennsylvania | 42107 | 14611 | 404 |
1341546 | 1341546 | 2021-05-21 | Snyder | Pennsylvania | 42109 | 3636 | 84 |
1341547 | 1341547 | 2021-05-21 | Somerset | Pennsylvania | 42111 | 7903 | 208 |
1341548 | 1341548 | 2021-05-21 | Sullivan | Pennsylvania | 42113 | 428 | 20 |
1341549 | 1341549 | 2021-05-21 | Susquehanna | Pennsylvania | 42115 | 2587 | 62 |
1341550 | 1341550 | 2021-05-21 | Tioga | Pennsylvania | 42117 | 2993 | 107 |
1341551 | 1341551 | 2021-05-21 | Union | Pennsylvania | 42119 | 6094 | 86 |
1341552 | 1341552 | 2021-05-21 | Venango | Pennsylvania | 42121 | 3990 | 95 |
1341553 | 1341553 | 2021-05-21 | Warren | Pennsylvania | 42123 | 2607 | 102 |
1341554 | 1341554 | 2021-05-21 | Washington | Pennsylvania | 42125 | 17614 | 298 |
1341555 | 1341555 | 2021-05-21 | Wayne | Pennsylvania | 42127 | 4067 | 80 |
1341556 | 1341556 | 2021-05-21 | Westmoreland | Pennsylvania | 42129 | 33877 | 760 |
1341557 | 1341557 | 2021-05-21 | Wyoming | Pennsylvania | 42131 | 1919 | 52 |
1341558 | 1341558 | 2021-05-21 | York | Pennsylvania | 42133 | 45968 | 806 |
Advanced export
JSON shape: default, array, newline-delimited
CREATE TABLE [ny_times_us_counties] ( [date] TEXT, [county] TEXT, [state] TEXT, [fips] INTEGER, [cases] INTEGER, [deaths] INTEGER ); CREATE INDEX [idx_ny_times_us_counties_state] ON [ny_times_us_counties] ([state]); CREATE INDEX [idx_ny_times_us_counties_county] ON [ny_times_us_counties] ([county]); CREATE INDEX [idx_ny_times_us_counties_fips] ON [ny_times_us_counties] ([fips]); CREATE INDEX [idx_ny_times_us_counties_date] ON [ny_times_us_counties] ([date] desc);