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 2022-02-09 and state = "Pennsylvania" sorted by date descending
This data as json, yaml, Notebook, copyable, CSV (advanced)
Link | rowid | date ▲ | county | state | fips | cases | deaths |
---|---|---|---|---|---|---|---|
2199233 | 2199233 | 2022-02-09 | Adams | Pennsylvania | 42001 | 24122 | 343 |
2199234 | 2199234 | 2022-02-09 | Allegheny | Pennsylvania | 42003 | 255702 | 3091 |
2199235 | 2199235 | 2022-02-09 | Armstrong | Pennsylvania | 42005 | 14809 | 315 |
2199236 | 2199236 | 2022-02-09 | Beaver | Pennsylvania | 42007 | 38786 | 688 |
2199237 | 2199237 | 2022-02-09 | Bedford | Pennsylvania | 42009 | 10626 | 257 |
2199238 | 2199238 | 2022-02-09 | Berks | Pennsylvania | 42011 | 100289 | 1533 |
2199239 | 2199239 | 2022-02-09 | Blair | Pennsylvania | 42013 | 28571 | 581 |
2199240 | 2199240 | 2022-02-09 | Bradford | Pennsylvania | 42015 | 14454 | 189 |
2199241 | 2199241 | 2022-02-09 | Bucks | Pennsylvania | 42017 | 120177 | 1777 |
2199242 | 2199242 | 2022-02-09 | Butler | Pennsylvania | 42019 | 43310 | 689 |
2199243 | 2199243 | 2022-02-09 | Cambria | Pennsylvania | 42021 | 33506 | 683 |
2199244 | 2199244 | 2022-02-09 | Cameron | Pennsylvania | 42023 | 798 | 19 |
2199245 | 2199245 | 2022-02-09 | Carbon | Pennsylvania | 42025 | 15516 | 271 |
2199246 | 2199246 | 2022-02-09 | Centre | Pennsylvania | 42027 | 33998 | 329 |
2199247 | 2199247 | 2022-02-09 | Chester | Pennsylvania | 42029 | 88764 | 1090 |
2199248 | 2199248 | 2022-02-09 | Clarion | Pennsylvania | 42031 | 8011 | 193 |
2199249 | 2199249 | 2022-02-09 | Clearfield | Pennsylvania | 42033 | 18527 | 308 |
2199250 | 2199250 | 2022-02-09 | Clinton | Pennsylvania | 42035 | 8753 | 120 |
2199251 | 2199251 | 2022-02-09 | Columbia | Pennsylvania | 42037 | 14431 | 223 |
2199252 | 2199252 | 2022-02-09 | Crawford | Pennsylvania | 42039 | 19302 | 293 |
2199253 | 2199253 | 2022-02-09 | Cumberland | Pennsylvania | 42041 | 49367 | 835 |
2199254 | 2199254 | 2022-02-09 | Dauphin | Pennsylvania | 42043 | 57770 | 889 |
2199255 | 2199255 | 2022-02-09 | Delaware | Pennsylvania | 42045 | 107503 | 1768 |
2199256 | 2199256 | 2022-02-09 | Elk | Pennsylvania | 42047 | 6914 | 90 |
2199257 | 2199257 | 2022-02-09 | Erie | Pennsylvania | 42049 | 55413 | 706 |
2199258 | 2199258 | 2022-02-09 | Fayette | Pennsylvania | 42051 | 29666 | 597 |
2199259 | 2199259 | 2022-02-09 | Forest | Pennsylvania | 42053 | 2175 | 34 |
2199260 | 2199260 | 2022-02-09 | Franklin | Pennsylvania | 42055 | 39393 | 641 |
2199261 | 2199261 | 2022-02-09 | Fulton | Pennsylvania | 42057 | 3968 | 60 |
2199262 | 2199262 | 2022-02-09 | Greene | Pennsylvania | 42059 | 8081 | 94 |
2199263 | 2199263 | 2022-02-09 | Huntingdon | Pennsylvania | 42061 | 11112 | 233 |
2199264 | 2199264 | 2022-02-09 | Indiana | Pennsylvania | 42063 | 16685 | 328 |
2199265 | 2199265 | 2022-02-09 | Jefferson | Pennsylvania | 42065 | 8620 | 209 |
2199266 | 2199266 | 2022-02-09 | Juniata | Pennsylvania | 42067 | 4638 | 169 |
2199267 | 2199267 | 2022-02-09 | Lackawanna | Pennsylvania | 42069 | 41683 | 693 |
2199268 | 2199268 | 2022-02-09 | Lancaster | Pennsylvania | 42071 | 118376 | 1784 |
2199269 | 2199269 | 2022-02-09 | Lawrence | Pennsylvania | 42073 | 18483 | 384 |
2199270 | 2199270 | 2022-02-09 | Lebanon | Pennsylvania | 42075 | 35883 | 482 |
2199271 | 2199271 | 2022-02-09 | Lehigh | Pennsylvania | 42077 | 87898 | 1189 |
2199272 | 2199272 | 2022-02-09 | Luzerne | Pennsylvania | 42079 | 71390 | 1250 |
2199273 | 2199273 | 2022-02-09 | Lycoming | Pennsylvania | 42081 | 27655 | 489 |
2199274 | 2199274 | 2022-02-09 | McKean | Pennsylvania | 42083 | 7860 | 131 |
2199275 | 2199275 | 2022-02-09 | Mercer | Pennsylvania | 42085 | 22833 | 477 |
2199276 | 2199276 | 2022-02-09 | Mifflin | Pennsylvania | 42087 | 11888 | 261 |
2199277 | 2199277 | 2022-02-09 | Monroe | Pennsylvania | 42089 | 36142 | 491 |
2199278 | 2199278 | 2022-02-09 | Montgomery | Pennsylvania | 42091 | 147336 | 2215 |
2199279 | 2199279 | 2022-02-09 | Montour | Pennsylvania | 42093 | 4339 | 86 |
2199280 | 2199280 | 2022-02-09 | Northampton | Pennsylvania | 42095 | 77879 | 1031 |
2199281 | 2199281 | 2022-02-09 | Northumberland | Pennsylvania | 42097 | 22207 | 504 |
2199282 | 2199282 | 2022-02-09 | Perry | Pennsylvania | 42099 | 8605 | 174 |
2199283 | 2199283 | 2022-02-09 | Philadelphia | Pennsylvania | 42101 | 299711 | 4828 |
2199284 | 2199284 | 2022-02-09 | Pike | Pennsylvania | 42103 | 9582 | 90 |
2199285 | 2199285 | 2022-02-09 | Potter | Pennsylvania | 42105 | 3033 | 88 |
2199286 | 2199286 | 2022-02-09 | Schuylkill | Pennsylvania | 42107 | 33563 | 644 |
2199287 | 2199287 | 2022-02-09 | Snyder | Pennsylvania | 42109 | 7896 | 148 |
2199288 | 2199288 | 2022-02-09 | Somerset | Pennsylvania | 42111 | 18208 | 385 |
2199289 | 2199289 | 2022-02-09 | Sullivan | Pennsylvania | 42113 | 1028 | 32 |
2199290 | 2199290 | 2022-02-09 | Susquehanna | Pennsylvania | 42115 | 7438 | 103 |
2199291 | 2199291 | 2022-02-09 | Tioga | Pennsylvania | 42117 | 7665 | 187 |
2199292 | 2199292 | 2022-02-09 | Union | Pennsylvania | 42119 | 11310 | 142 |
2199293 | 2199293 | 2022-02-09 | Venango | Pennsylvania | 42121 | 10985 | 225 |
2199294 | 2199294 | 2022-02-09 | Warren | Pennsylvania | 42123 | 7044 | 202 |
2199295 | 2199295 | 2022-02-09 | Washington | Pennsylvania | 42125 | 49325 | 599 |
2199296 | 2199296 | 2022-02-09 | Wayne | Pennsylvania | 42127 | 9758 | 156 |
2199297 | 2199297 | 2022-02-09 | Westmoreland | Pennsylvania | 42129 | 77266 | 1282 |
2199298 | 2199298 | 2022-02-09 | Wyoming | Pennsylvania | 42131 | 4895 | 97 |
2199299 | 2199299 | 2022-02-09 | York | Pennsylvania | 42133 | 115909 | 1403 |
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);