⚠️ Consult the README for warnings about using and building on this data. Also review Why It’s So Freaking Hard To Make A Good COVID-19 Model and Ten Considerations Before You Create Another Chart About COVID-19.

Data license: LICENSE · Data source: The New York Times · About: simonw/covid-19-datasette

19,946 rows where state = "Pennsylvania" sorted by date descending

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Suggested facets: date (date)

fips

county

state

  • Pennsylvania · 19,946
Link rowid date ▲ county state fips cases deaths
926025 2021-01-13 Adams Pennsylvania 42001 5508 116
926026 2021-01-13 Allegheny Pennsylvania 42003 62439 1253
926027 2021-01-13 Armstrong Pennsylvania 42005 4113 85
926028 2021-01-13 Beaver Pennsylvania 42007 9854 283
926029 2021-01-13 Bedford Pennsylvania 42009 3289 103
926030 2021-01-13 Berks Pennsylvania 42011 27452 652
926031 2021-01-13 Blair Pennsylvania 42013 9026 196
926032 2021-01-13 Bradford Pennsylvania 42015 3475 60
926033 2021-01-13 Bucks Pennsylvania 42017 35125 952
926034 2021-01-13 Butler Pennsylvania 42019 11222 265
926035 2021-01-13 Cambria Pennsylvania 42021 9824 307
926036 2021-01-13 Cameron Pennsylvania 42023 200 5
926037 2021-01-13 Carbon Pennsylvania 42025 3626 99
926038 2021-01-13 Centre Pennsylvania 42027 9973 162
926039 2021-01-13 Chester Pennsylvania 42029 23914 596
926040 2021-01-13 Clarion Pennsylvania 42031 2289 53
926041 2021-01-13 Clearfield Pennsylvania 42033 4940 60
926042 2021-01-13 Clinton Pennsylvania 42035 2278 37
926043 2021-01-13 Columbia Pennsylvania 42037 3542 92
926044 2021-01-13 Crawford Pennsylvania 42039 5425 107
926045 2021-01-13 Cumberland Pennsylvania 42041 12187 357
926046 2021-01-13 Dauphin Pennsylvania 42043 15965 373
926047 2021-01-13 Delaware Pennsylvania 42045 33407 1049
926048 2021-01-13 Elk Pennsylvania 42047 1745 25
926049 2021-01-13 Erie Pennsylvania 42049 13609 278
926050 2021-01-13 Fayette Pennsylvania 42051 8704 160
926051 2021-01-13 Forest Pennsylvania 42053 571 8
926052 2021-01-13 Franklin Pennsylvania 42055 10263 265
926053 2021-01-13 Fulton Pennsylvania 42057 885 12
926054 2021-01-13 Greene Pennsylvania 42059 2081 23
926055 2021-01-13 Huntingdon Pennsylvania 42061 3518 93
926056 2021-01-13 Indiana Pennsylvania 42063 4416 136
926057 2021-01-13 Jefferson Pennsylvania 42065 2188 56
926058 2021-01-13 Juniata Pennsylvania 42067 1540 68
926059 2021-01-13 Lackawanna Pennsylvania 42069 10627 294
926060 2021-01-13 Lancaster Pennsylvania 42071 32641 806
926061 2021-01-13 Lawrence Pennsylvania 42073 4934 143
926062 2021-01-13 Lebanon Pennsylvania 42075 10355 186
926063 2021-01-13 Lehigh Pennsylvania 42077 24383 580
926064 2021-01-13 Luzerne Pennsylvania 42079 19913 513
926065 2021-01-13 Lycoming Pennsylvania 42081 7114 163
926066 2021-01-13 McKean Pennsylvania 42083 2141 41
926067 2021-01-13 Mercer Pennsylvania 42085 6801 179
926068 2021-01-13 Mifflin Pennsylvania 42087 3851 131
926069 2021-01-13 Monroe Pennsylvania 42089 7353 221
926070 2021-01-13 Montgomery Pennsylvania 42091 41961 1250
926071 2021-01-13 Montour Pennsylvania 42093 1334 34
926072 2021-01-13 Northampton Pennsylvania 42095 19753 493
926073 2021-01-13 Northumberland Pennsylvania 42097 5935 258
926074 2021-01-13 Perry Pennsylvania 42099 2113 53
926075 2021-01-13 Philadelphia Pennsylvania 42101 101582 2671
926076 2021-01-13 Pike Pennsylvania 42103 1779 37
926077 2021-01-13 Potter Pennsylvania 42105 729 16
926078 2021-01-13 Schuylkill Pennsylvania 42107 9736 279
926079 2021-01-13 Snyder Pennsylvania 42109 2249 55
926080 2021-01-13 Somerset Pennsylvania 42111 5762 117
926081 2021-01-13 Sullivan Pennsylvania 42113 195 5
926082 2021-01-13 Susquehanna Pennsylvania 42115 1259 42
926083 2021-01-13 Tioga Pennsylvania 42117 2113 82
926084 2021-01-13 Union Pennsylvania 42119 3560 54
926085 2021-01-13 Venango Pennsylvania 42121 2817 58
926086 2021-01-13 Warren Pennsylvania 42123 1813 63
926087 2021-01-13 Washington Pennsylvania 42125 10831 165
926088 2021-01-13 Wayne Pennsylvania 42127 2308 30
926089 2021-01-13 Westmoreland Pennsylvania 42129 22510 502
926090 2021-01-13 Wyoming Pennsylvania 42131 925 32
926091 2021-01-13 York Pennsylvania 42133 27275 519
922779 2021-01-12 Adams Pennsylvania 42001 5434 115
922780 2021-01-12 Allegheny Pennsylvania 42003 61769 1208
922781 2021-01-12 Armstrong Pennsylvania 42005 4052 84
922782 2021-01-12 Beaver Pennsylvania 42007 9749 281
922783 2021-01-12 Bedford Pennsylvania 42009 3272 100
922784 2021-01-12 Berks Pennsylvania 42011 27070 632
922785 2021-01-12 Blair Pennsylvania 42013 8925 194
922786 2021-01-12 Bradford Pennsylvania 42015 3449 60
922787 2021-01-12 Bucks Pennsylvania 42017 34847 945
922788 2021-01-12 Butler Pennsylvania 42019 11056 256
922789 2021-01-12 Cambria Pennsylvania 42021 9760 293
922790 2021-01-12 Cameron Pennsylvania 42023 194 5
922791 2021-01-12 Carbon Pennsylvania 42025 3553 97
922792 2021-01-12 Centre Pennsylvania 42027 9840 158
922793 2021-01-12 Chester Pennsylvania 42029 23631 587
922794 2021-01-12 Clarion Pennsylvania 42031 2253 53
922795 2021-01-12 Clearfield Pennsylvania 42033 4883 59
922796 2021-01-12 Clinton Pennsylvania 42035 2248 34
922797 2021-01-12 Columbia Pennsylvania 42037 3474 91
922798 2021-01-12 Crawford Pennsylvania 42039 5397 104
922799 2021-01-12 Cumberland Pennsylvania 42041 12081 352
922800 2021-01-12 Dauphin Pennsylvania 42043 15809 365
922801 2021-01-12 Delaware Pennsylvania 42045 33132 1024
922802 2021-01-12 Elk Pennsylvania 42047 1712 23
922803 2021-01-12 Erie Pennsylvania 42049 13462 266
922804 2021-01-12 Fayette Pennsylvania 42051 8590 152
922805 2021-01-12 Forest Pennsylvania 42053 430 8
922806 2021-01-12 Franklin Pennsylvania 42055 10180 261
922807 2021-01-12 Fulton Pennsylvania 42057 878 12
922808 2021-01-12 Greene Pennsylvania 42059 2050 23
922809 2021-01-12 Huntingdon Pennsylvania 42061 3490 93
922810 2021-01-12 Indiana Pennsylvania 42063 4386 133
922811 2021-01-12 Jefferson Pennsylvania 42065 2171 55

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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]);