ny_times_us_counties
Data license: LICENSE · Data source: The New York Times · About: simonw/covid-19-datasette
65 rows where "date" is on date 2020-04-05 and state = "Pennsylvania" sorted by date descending
This data as json, yaml, Notebook, copyable, CSV (advanced)
Suggested facets: deaths
fips >30
county >30
- Adams 1
- Allegheny 1
- Armstrong 1
- Beaver 1
- Bedford 1
- Berks 1
- Blair 1
- Bradford 1
- Bucks 1
- Butler 1
- Cambria 1
- Cameron 1
- Carbon 1
- Centre 1
- Chester 1
- Clarion 1
- Clearfield 1
- Clinton 1
- Columbia 1
- Crawford 1
- Cumberland 1
- Dauphin 1
- Delaware 1
- Erie 1
- Fayette 1
- Forest 1
- Franklin 1
- Fulton 1
- Greene 1
- Huntingdon 1
- …
state 1
- Pennsylvania · 65 ✖
Link | rowid | date ▲ | county | state | fips | cases | deaths |
---|---|---|---|---|---|---|---|
34916 | 34916 | 2020-04-05 | Adams | Pennsylvania | 42001 | 22 | 0 |
34917 | 34917 | 2020-04-05 | Allegheny | Pennsylvania | 42003 | 605 | 4 |
34918 | 34918 | 2020-04-05 | Armstrong | Pennsylvania | 42005 | 12 | 0 |
34919 | 34919 | 2020-04-05 | Beaver | Pennsylvania | 42007 | 84 | 6 |
34920 | 34920 | 2020-04-05 | Bedford | Pennsylvania | 42009 | 4 | 0 |
34921 | 34921 | 2020-04-05 | Berks | Pennsylvania | 42011 | 276 | 3 |
34922 | 34922 | 2020-04-05 | Blair | Pennsylvania | 42013 | 6 | 0 |
34923 | 34923 | 2020-04-05 | Bradford | Pennsylvania | 42015 | 10 | 0 |
34924 | 34924 | 2020-04-05 | Bucks | Pennsylvania | 42017 | 634 | 17 |
34925 | 34925 | 2020-04-05 | Butler | Pennsylvania | 42019 | 87 | 2 |
34926 | 34926 | 2020-04-05 | Cambria | Pennsylvania | 42021 | 7 | 0 |
34927 | 34927 | 2020-04-05 | Cameron | Pennsylvania | 42023 | 1 | 0 |
34928 | 34928 | 2020-04-05 | Carbon | Pennsylvania | 42025 | 50 | 1 |
34929 | 34929 | 2020-04-05 | Centre | Pennsylvania | 42027 | 43 | 0 |
34930 | 34930 | 2020-04-05 | Chester | Pennsylvania | 42029 | 269 | 2 |
34931 | 34931 | 2020-04-05 | Clarion | Pennsylvania | 42031 | 5 | 0 |
34932 | 34932 | 2020-04-05 | Clearfield | Pennsylvania | 42033 | 7 | 0 |
34933 | 34933 | 2020-04-05 | Clinton | Pennsylvania | 42035 | 1 | 0 |
34934 | 34934 | 2020-04-05 | Columbia | Pennsylvania | 42037 | 22 | 0 |
34935 | 34935 | 2020-04-05 | Crawford | Pennsylvania | 42039 | 7 | 0 |
34936 | 34936 | 2020-04-05 | Cumberland | Pennsylvania | 42041 | 58 | 2 |
34937 | 34937 | 2020-04-05 | Dauphin | Pennsylvania | 42043 | 118 | 1 |
34938 | 34938 | 2020-04-05 | Delaware | Pennsylvania | 42045 | 708 | 14 |
34939 | 34939 | 2020-04-05 | Erie | Pennsylvania | 42049 | 19 | 1 |
34940 | 34940 | 2020-04-05 | Fayette | Pennsylvania | 42051 | 27 | 1 |
34941 | 34941 | 2020-04-05 | Forest | Pennsylvania | 42053 | 3 | 0 |
34942 | 34942 | 2020-04-05 | Franklin | Pennsylvania | 42055 | 30 | 0 |
34943 | 34943 | 2020-04-05 | Fulton | Pennsylvania | 42057 | 1 | 0 |
34944 | 34944 | 2020-04-05 | Greene | Pennsylvania | 42059 | 12 | 0 |
34945 | 34945 | 2020-04-05 | Huntingdon | Pennsylvania | 42061 | 4 | 0 |
34946 | 34946 | 2020-04-05 | Indiana | Pennsylvania | 42063 | 13 | 0 |
34947 | 34947 | 2020-04-05 | Juniata | Pennsylvania | 42067 | 7 | 0 |
34948 | 34948 | 2020-04-05 | Lackawanna | Pennsylvania | 42069 | 172 | 6 |
34949 | 34949 | 2020-04-05 | Lancaster | Pennsylvania | 42071 | 371 | 8 |
34950 | 34950 | 2020-04-05 | Lawrence | Pennsylvania | 42073 | 23 | 2 |
34951 | 34951 | 2020-04-05 | Lebanon | Pennsylvania | 42075 | 106 | 0 |
34952 | 34952 | 2020-04-05 | Lehigh | Pennsylvania | 42077 | 877 | 8 |
34953 | 34953 | 2020-04-05 | Luzerne | Pennsylvania | 42079 | 741 | 5 |
34954 | 34954 | 2020-04-05 | Lycoming | Pennsylvania | 42081 | 9 | 0 |
34955 | 34955 | 2020-04-05 | McKean | Pennsylvania | 42083 | 1 | 0 |
34956 | 34956 | 2020-04-05 | Mercer | Pennsylvania | 42085 | 18 | 0 |
34957 | 34957 | 2020-04-05 | Mifflin | Pennsylvania | 42087 | 9 | 0 |
34958 | 34958 | 2020-04-05 | Monroe | Pennsylvania | 42089 | 528 | 11 |
34959 | 34959 | 2020-04-05 | Montgomery | Pennsylvania | 42091 | 1111 | 22 |
34960 | 34960 | 2020-04-05 | Montour | Pennsylvania | 42093 | 37 | 0 |
34961 | 34961 | 2020-04-05 | Northampton | Pennsylvania | 42095 | 636 | 11 |
34962 | 34962 | 2020-04-05 | Northumberland | Pennsylvania | 42097 | 14 | 0 |
34963 | 34963 | 2020-04-05 | Perry | Pennsylvania | 42099 | 5 | 1 |
34964 | 34964 | 2020-04-05 | Philadelphia | Pennsylvania | 42101 | 3135 | 28 |
34965 | 34965 | 2020-04-05 | Pike | Pennsylvania | 42103 | 114 | 1 |
34966 | 34966 | 2020-04-05 | Potter | Pennsylvania | 42105 | 3 | 0 |
34967 | 34967 | 2020-04-05 | Schuylkill | Pennsylvania | 42107 | 90 | 0 |
34968 | 34968 | 2020-04-05 | Snyder | Pennsylvania | 42109 | 8 | 1 |
34969 | 34969 | 2020-04-05 | Somerset | Pennsylvania | 42111 | 4 | 0 |
34970 | 34970 | 2020-04-05 | Sullivan | Pennsylvania | 42113 | 1 | 0 |
34971 | 34971 | 2020-04-05 | Susquehanna | Pennsylvania | 42115 | 6 | 0 |
34972 | 34972 | 2020-04-05 | Tioga | Pennsylvania | 42117 | 3 | 0 |
34973 | 34973 | 2020-04-05 | Union | Pennsylvania | 42119 | 6 | 0 |
34974 | 34974 | 2020-04-05 | Venango | Pennsylvania | 42121 | 3 | 0 |
34975 | 34975 | 2020-04-05 | Warren | Pennsylvania | 42123 | 1 | 0 |
34976 | 34976 | 2020-04-05 | Washington | Pennsylvania | 42125 | 50 | 0 |
34977 | 34977 | 2020-04-05 | Wayne | Pennsylvania | 42127 | 33 | 0 |
34978 | 34978 | 2020-04-05 | Westmoreland | Pennsylvania | 42129 | 147 | 0 |
34979 | 34979 | 2020-04-05 | Wyoming | Pennsylvania | 42131 | 5 | 0 |
34980 | 34980 | 2020-04-05 | York | Pennsylvania | 42133 | 171 | 1 |
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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]); CREATE INDEX [idx_ny_times_us_counties_date] ON [ny_times_us_counties] ([date] desc);