ny_times_us_counties
Data license: LICENSE · Data source: The New York Times · About: simonw/covid-19-datasette
67 rows where "date" is on date 2022-01-02 and state = "Pennsylvania" sorted by date descending
This data as json, yaml, Notebook, copyable, CSV (advanced)
Link | rowid | date ▲ | county | state | fips | cases | deaths |
---|---|---|---|---|---|---|---|
2075629 | 2075629 | 2022-01-02 | Adams | Pennsylvania | 42001 | 18658 | 274 |
2075630 | 2075630 | 2022-01-02 | Allegheny | Pennsylvania | 42003 | 181874 | 2725 |
2075631 | 2075631 | 2022-01-02 | Armstrong | Pennsylvania | 42005 | 12037 | 275 |
2075632 | 2075632 | 2022-01-02 | Beaver | Pennsylvania | 42007 | 30017 | 604 |
2075633 | 2075633 | 2022-01-02 | Bedford | Pennsylvania | 42009 | 8813 | 226 |
2075634 | 2075634 | 2022-01-02 | Berks | Pennsylvania | 42011 | 78112 | 1320 |
2075635 | 2075635 | 2022-01-02 | Blair | Pennsylvania | 42013 | 23202 | 499 |
2075636 | 2075636 | 2022-01-02 | Bradford | Pennsylvania | 42015 | 10973 | 154 |
2075637 | 2075637 | 2022-01-02 | Bucks | Pennsylvania | 42017 | 93942 | 1554 |
2075638 | 2075638 | 2022-01-02 | Butler | Pennsylvania | 42019 | 33456 | 614 |
2075639 | 2075639 | 2022-01-02 | Cambria | Pennsylvania | 42021 | 25674 | 621 |
2075640 | 2075640 | 2022-01-02 | Cameron | Pennsylvania | 42023 | 649 | 13 |
2075641 | 2075641 | 2022-01-02 | Carbon | Pennsylvania | 42025 | 12045 | 232 |
2075642 | 2075642 | 2022-01-02 | Centre | Pennsylvania | 42027 | 26658 | 289 |
2075643 | 2075643 | 2022-01-02 | Chester | Pennsylvania | 42029 | 68556 | 967 |
2075644 | 2075644 | 2022-01-02 | Clarion | Pennsylvania | 42031 | 6574 | 171 |
2075645 | 2075645 | 2022-01-02 | Clearfield | Pennsylvania | 42033 | 14600 | 260 |
2075646 | 2075646 | 2022-01-02 | Clinton | Pennsylvania | 42035 | 6882 | 105 |
2075647 | 2075647 | 2022-01-02 | Columbia | Pennsylvania | 42037 | 11115 | 191 |
2075648 | 2075648 | 2022-01-02 | Crawford | Pennsylvania | 42039 | 15413 | 260 |
2075649 | 2075649 | 2022-01-02 | Cumberland | Pennsylvania | 42041 | 37529 | 721 |
2075650 | 2075650 | 2022-01-02 | Dauphin | Pennsylvania | 42043 | 44721 | 758 |
2075651 | 2075651 | 2022-01-02 | Delaware | Pennsylvania | 42045 | 82044 | 1582 |
2075652 | 2075652 | 2022-01-02 | Elk | Pennsylvania | 42047 | 5382 | 76 |
2075653 | 2075653 | 2022-01-02 | Erie | Pennsylvania | 42049 | 42583 | 630 |
2075654 | 2075654 | 2022-01-02 | Fayette | Pennsylvania | 42051 | 23259 | 539 |
2075655 | 2075655 | 2022-01-02 | Forest | Pennsylvania | 42053 | 1862 | 31 |
2075656 | 2075656 | 2022-01-02 | Franklin | Pennsylvania | 42055 | 30133 | 550 |
2075657 | 2075657 | 2022-01-02 | Fulton | Pennsylvania | 42057 | 3170 | 49 |
2075658 | 2075658 | 2022-01-02 | Greene | Pennsylvania | 42059 | 6395 | 80 |
2075659 | 2075659 | 2022-01-02 | Huntingdon | Pennsylvania | 42061 | 8547 | 203 |
2075660 | 2075660 | 2022-01-02 | Indiana | Pennsylvania | 42063 | 12654 | 298 |
2075661 | 2075661 | 2022-01-02 | Jefferson | Pennsylvania | 42065 | 6923 | 185 |
2075662 | 2075662 | 2022-01-02 | Juniata | Pennsylvania | 42067 | 3840 | 148 |
2075663 | 2075663 | 2022-01-02 | Lackawanna | Pennsylvania | 42069 | 30356 | 599 |
2075664 | 2075664 | 2022-01-02 | Lancaster | Pennsylvania | 42071 | 93158 | 1555 |
2075665 | 2075665 | 2022-01-02 | Lawrence | Pennsylvania | 42073 | 14807 | 334 |
2075666 | 2075666 | 2022-01-02 | Lebanon | Pennsylvania | 42075 | 27856 | 400 |
2075667 | 2075667 | 2022-01-02 | Lehigh | Pennsylvania | 42077 | 65466 | 1047 |
2075668 | 2075668 | 2022-01-02 | Luzerne | Pennsylvania | 42079 | 54392 | 1071 |
2075669 | 2075669 | 2022-01-02 | Lycoming | Pennsylvania | 42081 | 21979 | 443 |
2075670 | 2075670 | 2022-01-02 | McKean | Pennsylvania | 42083 | 6359 | 114 |
2075671 | 2075671 | 2022-01-02 | Mercer | Pennsylvania | 42085 | 18471 | 430 |
2075672 | 2075672 | 2022-01-02 | Mifflin | Pennsylvania | 42087 | 9311 | 238 |
2075673 | 2075673 | 2022-01-02 | Monroe | Pennsylvania | 42089 | 26825 | 417 |
2075674 | 2075674 | 2022-01-02 | Montgomery | Pennsylvania | 42091 | 113906 | 1996 |
2075675 | 2075675 | 2022-01-02 | Montour | Pennsylvania | 42093 | 3330 | 81 |
2075676 | 2075676 | 2022-01-02 | Northampton | Pennsylvania | 42095 | 60175 | 882 |
2075677 | 2075677 | 2022-01-02 | Northumberland | Pennsylvania | 42097 | 17243 | 471 |
2075678 | 2075678 | 2022-01-02 | Perry | Pennsylvania | 42099 | 6910 | 154 |
2075679 | 2075679 | 2022-01-02 | Philadelphia | Pennsylvania | 42101 | 228936 | 4258 |
2075680 | 2075680 | 2022-01-02 | Pike | Pennsylvania | 42103 | 7287 | 73 |
2075681 | 2075681 | 2022-01-02 | Potter | Pennsylvania | 42105 | 2591 | 79 |
2075682 | 2075682 | 2022-01-02 | Schuylkill | Pennsylvania | 42107 | 26470 | 554 |
2075683 | 2075683 | 2022-01-02 | Snyder | Pennsylvania | 42109 | 6313 | 127 |
2075684 | 2075684 | 2022-01-02 | Somerset | Pennsylvania | 42111 | 14188 | 330 |
2075685 | 2075685 | 2022-01-02 | Sullivan | Pennsylvania | 42113 | 807 | 28 |
2075686 | 2075686 | 2022-01-02 | Susquehanna | Pennsylvania | 42115 | 5878 | 86 |
2075687 | 2075687 | 2022-01-02 | Tioga | Pennsylvania | 42117 | 6280 | 172 |
2075688 | 2075688 | 2022-01-02 | Union | Pennsylvania | 42119 | 9048 | 133 |
2075689 | 2075689 | 2022-01-02 | Venango | Pennsylvania | 42121 | 9042 | 200 |
2075690 | 2075690 | 2022-01-02 | Warren | Pennsylvania | 42123 | 5620 | 180 |
2075691 | 2075691 | 2022-01-02 | Washington | Pennsylvania | 42125 | 36014 | 513 |
2075692 | 2075692 | 2022-01-02 | Wayne | Pennsylvania | 42127 | 7715 | 140 |
2075693 | 2075693 | 2022-01-02 | Westmoreland | Pennsylvania | 42129 | 60200 | 1121 |
2075694 | 2075694 | 2022-01-02 | Wyoming | Pennsylvania | 42131 | 3875 | 89 |
2075695 | 2075695 | 2022-01-02 | York | Pennsylvania | 42133 | 88124 | 1196 |
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);