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 2022-01-15 and state = "Pennsylvania" sorted by date descending
This data as json, yaml, Notebook, copyable, CSV (advanced)
Link | rowid | date ▲ | county | state | fips | cases | deaths |
---|---|---|---|---|---|---|---|
2117899 | 2117899 | 2022-01-15 | Adams | Pennsylvania | 42001 | 21276 | 300 |
2117900 | 2117900 | 2022-01-15 | Allegheny | Pennsylvania | 42003 | 224385 | 2842 |
2117901 | 2117901 | 2022-01-15 | Armstrong | Pennsylvania | 42005 | 13415 | 290 |
2117902 | 2117902 | 2022-01-15 | Beaver | Pennsylvania | 42007 | 33870 | 642 |
2117903 | 2117903 | 2022-01-15 | Bedford | Pennsylvania | 42009 | 9481 | 236 |
2117904 | 2117904 | 2022-01-15 | Berks | Pennsylvania | 42011 | 91157 | 1407 |
2117905 | 2117905 | 2022-01-15 | Blair | Pennsylvania | 42013 | 25027 | 535 |
2117906 | 2117906 | 2022-01-15 | Bradford | Pennsylvania | 42015 | 12436 | 176 |
2117907 | 2117907 | 2022-01-15 | Bucks | Pennsylvania | 42017 | 110048 | 1622 |
2117908 | 2117908 | 2022-01-15 | Butler | Pennsylvania | 42019 | 38496 | 643 |
2117909 | 2117909 | 2022-01-15 | Cambria | Pennsylvania | 42021 | 28936 | 644 |
2117910 | 2117910 | 2022-01-15 | Cameron | Pennsylvania | 42023 | 693 | 15 |
2117911 | 2117911 | 2022-01-15 | Carbon | Pennsylvania | 42025 | 14024 | 245 |
2117912 | 2117912 | 2022-01-15 | Centre | Pennsylvania | 42027 | 30105 | 305 |
2117913 | 2117913 | 2022-01-15 | Chester | Pennsylvania | 42029 | 80208 | 1020 |
2117914 | 2117914 | 2022-01-15 | Clarion | Pennsylvania | 42031 | 7177 | 181 |
2117915 | 2117915 | 2022-01-15 | Clearfield | Pennsylvania | 42033 | 16031 | 286 |
2117916 | 2117916 | 2022-01-15 | Clinton | Pennsylvania | 42035 | 7648 | 115 |
2117917 | 2117917 | 2022-01-15 | Columbia | Pennsylvania | 42037 | 12458 | 203 |
2117918 | 2117918 | 2022-01-15 | Crawford | Pennsylvania | 42039 | 17160 | 270 |
2117919 | 2117919 | 2022-01-15 | Cumberland | Pennsylvania | 42041 | 42842 | 755 |
2117920 | 2117920 | 2022-01-15 | Dauphin | Pennsylvania | 42043 | 51825 | 809 |
2117921 | 2117921 | 2022-01-15 | Delaware | Pennsylvania | 42045 | 98803 | 1631 |
2117922 | 2117922 | 2022-01-15 | Elk | Pennsylvania | 42047 | 6002 | 82 |
2117923 | 2117923 | 2022-01-15 | Erie | Pennsylvania | 42049 | 49897 | 652 |
2117924 | 2117924 | 2022-01-15 | Fayette | Pennsylvania | 42051 | 25629 | 563 |
2117925 | 2117925 | 2022-01-15 | Forest | Pennsylvania | 42053 | 1967 | 33 |
2117926 | 2117926 | 2022-01-15 | Franklin | Pennsylvania | 42055 | 34399 | 589 |
2117927 | 2117927 | 2022-01-15 | Fulton | Pennsylvania | 42057 | 3487 | 55 |
2117928 | 2117928 | 2022-01-15 | Greene | Pennsylvania | 42059 | 7026 | 85 |
2117929 | 2117929 | 2022-01-15 | Huntingdon | Pennsylvania | 42061 | 9426 | 212 |
2117930 | 2117930 | 2022-01-15 | Indiana | Pennsylvania | 42063 | 14255 | 316 |
2117931 | 2117931 | 2022-01-15 | Jefferson | Pennsylvania | 42065 | 7520 | 195 |
2117932 | 2117932 | 2022-01-15 | Juniata | Pennsylvania | 42067 | 4107 | 156 |
2117933 | 2117933 | 2022-01-15 | Lackawanna | Pennsylvania | 42069 | 36035 | 627 |
2117934 | 2117934 | 2022-01-15 | Lancaster | Pennsylvania | 42071 | 107154 | 1639 |
2117935 | 2117935 | 2022-01-15 | Lawrence | Pennsylvania | 42073 | 16607 | 357 |
2117936 | 2117936 | 2022-01-15 | Lebanon | Pennsylvania | 42075 | 32197 | 426 |
2117937 | 2117937 | 2022-01-15 | Lehigh | Pennsylvania | 42077 | 80779 | 1108 |
2117938 | 2117938 | 2022-01-15 | Luzerne | Pennsylvania | 42079 | 63796 | 1136 |
2117939 | 2117939 | 2022-01-15 | Lycoming | Pennsylvania | 42081 | 24211 | 469 |
2117940 | 2117940 | 2022-01-15 | McKean | Pennsylvania | 42083 | 6913 | 121 |
2117941 | 2117941 | 2022-01-15 | Mercer | Pennsylvania | 42085 | 20660 | 446 |
2117942 | 2117942 | 2022-01-15 | Mifflin | Pennsylvania | 42087 | 10132 | 249 |
2117943 | 2117943 | 2022-01-15 | Monroe | Pennsylvania | 42089 | 32835 | 445 |
2117944 | 2117944 | 2022-01-15 | Montgomery | Pennsylvania | 42091 | 132830 | 2066 |
2117945 | 2117945 | 2022-01-15 | Montour | Pennsylvania | 42093 | 3748 | 83 |
2117946 | 2117946 | 2022-01-15 | Northampton | Pennsylvania | 42095 | 71600 | 935 |
2117947 | 2117947 | 2022-01-15 | Northumberland | Pennsylvania | 42097 | 19309 | 485 |
2117948 | 2117948 | 2022-01-15 | Perry | Pennsylvania | 42099 | 7562 | 163 |
2117949 | 2117949 | 2022-01-15 | Philadelphia | Pennsylvania | 42101 | 277656 | 4424 |
2117950 | 2117950 | 2022-01-15 | Pike | Pennsylvania | 42103 | 8617 | 77 |
2117951 | 2117951 | 2022-01-15 | Potter | Pennsylvania | 42105 | 2741 | 80 |
2117952 | 2117952 | 2022-01-15 | Schuylkill | Pennsylvania | 42107 | 29761 | 591 |
2117953 | 2117953 | 2022-01-15 | Snyder | Pennsylvania | 42109 | 6930 | 133 |
2117954 | 2117954 | 2022-01-15 | Somerset | Pennsylvania | 42111 | 15676 | 356 |
2117955 | 2117955 | 2022-01-15 | Sullivan | Pennsylvania | 42113 | 899 | 32 |
2117956 | 2117956 | 2022-01-15 | Susquehanna | Pennsylvania | 42115 | 6699 | 96 |
2117957 | 2117957 | 2022-01-15 | Tioga | Pennsylvania | 42117 | 6860 | 176 |
2117958 | 2117958 | 2022-01-15 | Union | Pennsylvania | 42119 | 9844 | 135 |
2117959 | 2117959 | 2022-01-15 | Venango | Pennsylvania | 42121 | 9785 | 211 |
2117960 | 2117960 | 2022-01-15 | Warren | Pennsylvania | 42123 | 6228 | 188 |
2117961 | 2117961 | 2022-01-15 | Washington | Pennsylvania | 42125 | 42894 | 548 |
2117962 | 2117962 | 2022-01-15 | Wayne | Pennsylvania | 42127 | 8745 | 147 |
2117963 | 2117963 | 2022-01-15 | Westmoreland | Pennsylvania | 42129 | 67953 | 1178 |
2117964 | 2117964 | 2022-01-15 | Wyoming | Pennsylvania | 42131 | 4345 | 92 |
2117965 | 2117965 | 2022-01-15 | York | Pennsylvania | 42133 | 102239 | 1282 |
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);