ny_times_us_counties
Data license: LICENSE · Data source: The New York Times · About: simonw/covid-19-datasette
67 rows where date = "2021-08-16" 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 |
---|---|---|---|---|---|---|---|
1623956 | 1623956 | 2021-08-16 | Adams | Pennsylvania | 42001 | 10118 | 190 |
1623957 | 1623957 | 2021-08-16 | Allegheny | Pennsylvania | 42003 | 105805 | 2038 |
1623958 | 1623958 | 2021-08-16 | Armstrong | Pennsylvania | 42005 | 6143 | 148 |
1623959 | 1623959 | 2021-08-16 | Beaver | Pennsylvania | 42007 | 16191 | 395 |
1623960 | 1623960 | 2021-08-16 | Bedford | Pennsylvania | 42009 | 4859 | 142 |
1623961 | 1623961 | 2021-08-16 | Berks | Pennsylvania | 42011 | 49634 | 1045 |
1623962 | 1623962 | 2021-08-16 | Blair | Pennsylvania | 42013 | 13725 | 346 |
1623963 | 1623963 | 2021-08-16 | Bradford | Pennsylvania | 42015 | 6222 | 97 |
1623964 | 1623964 | 2021-08-16 | Bucks | Pennsylvania | 42017 | 62895 | 1338 |
1623965 | 1623965 | 2021-08-16 | Butler | Pennsylvania | 42019 | 18221 | 425 |
1623966 | 1623966 | 2021-08-16 | Cambria | Pennsylvania | 42021 | 15101 | 442 |
1623967 | 1623967 | 2021-08-16 | Cameron | Pennsylvania | 42023 | 323 | 10 |
1623968 | 1623968 | 2021-08-16 | Carbon | Pennsylvania | 42025 | 6591 | 176 |
1623969 | 1623969 | 2021-08-16 | Centre | Pennsylvania | 42027 | 17294 | 229 |
1623970 | 1623970 | 2021-08-16 | Chester | Pennsylvania | 42029 | 42388 | 827 |
1623971 | 1623971 | 2021-08-16 | Clarion | Pennsylvania | 42031 | 3289 | 96 |
1623972 | 1623972 | 2021-08-16 | Clearfield | Pennsylvania | 42033 | 8935 | 160 |
1623973 | 1623973 | 2021-08-16 | Clinton | Pennsylvania | 42035 | 3820 | 68 |
1623974 | 1623974 | 2021-08-16 | Columbia | Pennsylvania | 42037 | 6047 | 136 |
1623975 | 1623975 | 2021-08-16 | Crawford | Pennsylvania | 42039 | 7786 | 158 |
1623976 | 1623976 | 2021-08-16 | Cumberland | Pennsylvania | 42041 | 21441 | 532 |
1623977 | 1623977 | 2021-08-16 | Dauphin | Pennsylvania | 42043 | 27245 | 570 |
1623978 | 1623978 | 2021-08-16 | Delaware | Pennsylvania | 42045 | 54092 | 1425 |
1623979 | 1623979 | 2021-08-16 | Elk | Pennsylvania | 42047 | 2928 | 41 |
1623980 | 1623980 | 2021-08-16 | Erie | Pennsylvania | 42049 | 21855 | 422 |
1623981 | 1623981 | 2021-08-16 | Fayette | Pennsylvania | 42051 | 13719 | 334 |
1623982 | 1623982 | 2021-08-16 | Forest | Pennsylvania | 42053 | 1444 | 21 |
1623983 | 1623983 | 2021-08-16 | Franklin | Pennsylvania | 42055 | 15947 | 377 |
1623984 | 1623984 | 2021-08-16 | Fulton | Pennsylvania | 42057 | 1408 | 17 |
1623985 | 1623985 | 2021-08-16 | Greene | Pennsylvania | 42059 | 3463 | 42 |
1623986 | 1623986 | 2021-08-16 | Huntingdon | Pennsylvania | 42061 | 5257 | 136 |
1623987 | 1623987 | 2021-08-16 | Indiana | Pennsylvania | 42063 | 6625 | 179 |
1623988 | 1623988 | 2021-08-16 | Jefferson | Pennsylvania | 42065 | 3426 | 99 |
1623989 | 1623989 | 2021-08-16 | Juniata | Pennsylvania | 42067 | 2186 | 88 |
1623990 | 1623990 | 2021-08-16 | Lackawanna | Pennsylvania | 42069 | 19015 | 487 |
1623991 | 1623991 | 2021-08-16 | Lancaster | Pennsylvania | 42071 | 57282 | 1177 |
1623992 | 1623992 | 2021-08-16 | Lawrence | Pennsylvania | 42073 | 8059 | 224 |
1623993 | 1623993 | 2021-08-16 | Lebanon | Pennsylvania | 42075 | 16621 | 299 |
1623994 | 1623994 | 2021-08-16 | Lehigh | Pennsylvania | 42077 | 41186 | 874 |
1623995 | 1623995 | 2021-08-16 | Luzerne | Pennsylvania | 42079 | 33050 | 835 |
1623996 | 1623996 | 2021-08-16 | Lycoming | Pennsylvania | 42081 | 12229 | 300 |
1623997 | 1623997 | 2021-08-16 | McKean | Pennsylvania | 42083 | 3880 | 75 |
1623998 | 1623998 | 2021-08-16 | Mercer | Pennsylvania | 42085 | 9932 | 269 |
1623999 | 1623999 | 2021-08-16 | Mifflin | Pennsylvania | 42087 | 5507 | 183 |
1624000 | 1624000 | 2021-08-16 | Monroe | Pennsylvania | 42089 | 15557 | 323 |
1624001 | 1624001 | 2021-08-16 | Montgomery | Pennsylvania | 42091 | 73209 | 1746 |
1624002 | 1624002 | 2021-08-16 | Montour | Pennsylvania | 42093 | 2044 | 67 |
1624003 | 1624003 | 2021-08-16 | Northampton | Pennsylvania | 42095 | 37422 | 723 |
1624004 | 1624004 | 2021-08-16 | Northumberland | Pennsylvania | 42097 | 9888 | 365 |
1624005 | 1624005 | 2021-08-16 | Perry | Pennsylvania | 42099 | 3966 | 101 |
1624006 | 1624006 | 2021-08-16 | Philadelphia | Pennsylvania | 42101 | 160366 | 3798 |
1624007 | 1624007 | 2021-08-16 | Pike | Pennsylvania | 42103 | 4238 | 54 |
1624008 | 1624008 | 2021-08-16 | Potter | Pennsylvania | 42105 | 1271 | 25 |
1624009 | 1624009 | 2021-08-16 | Schuylkill | Pennsylvania | 42107 | 15160 | 414 |
1624010 | 1624010 | 2021-08-16 | Snyder | Pennsylvania | 42109 | 3748 | 86 |
1624011 | 1624011 | 2021-08-16 | Somerset | Pennsylvania | 42111 | 8236 | 219 |
1624012 | 1624012 | 2021-08-16 | Sullivan | Pennsylvania | 42113 | 446 | 21 |
1624013 | 1624013 | 2021-08-16 | Susquehanna | Pennsylvania | 42115 | 2743 | 62 |
1624014 | 1624014 | 2021-08-16 | Tioga | Pennsylvania | 42117 | 3176 | 113 |
1624015 | 1624015 | 2021-08-16 | Union | Pennsylvania | 42119 | 6237 | 90 |
1624016 | 1624016 | 2021-08-16 | Venango | Pennsylvania | 42121 | 4226 | 104 |
1624017 | 1624017 | 2021-08-16 | Warren | Pennsylvania | 42123 | 2688 | 107 |
1624018 | 1624018 | 2021-08-16 | Washington | Pennsylvania | 42125 | 18569 | 313 |
1624019 | 1624019 | 2021-08-16 | Wayne | Pennsylvania | 42127 | 4317 | 84 |
1624020 | 1624020 | 2021-08-16 | Westmoreland | Pennsylvania | 42129 | 35371 | 785 |
1624021 | 1624021 | 2021-08-16 | Wyoming | Pennsylvania | 42131 | 2070 | 54 |
1624022 | 1624022 | 2021-08-16 | York | Pennsylvania | 42133 | 48557 | 840 |
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);