johns_hopkins_csse_daily_reports
Data source: Johns Hopkins CSSE · About: simonw/covid-19-datasette
27 rows where country_or_region = "Brazil" and "last_update" is on date 2022-01-30 sorted by day descending
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Suggested facets: last_update (date)
province_or_state 27
- Acre 1
- Alagoas 1
- Amapa 1
- Amazonas 1
- Bahia 1
- Ceara 1
- Distrito Federal 1
- Espirito Santo 1
- Goias 1
- Maranhao 1
- Mato Grosso 1
- Mato Grosso do Sul 1
- Minas Gerais 1
- Para 1
- Paraiba 1
- Parana 1
- Pernambuco 1
- Piaui 1
- Rio Grande do Norte 1
- Rio Grande do Sul 1
- Rio de Janeiro 1
- Rondonia 1
- Roraima 1
- Santa Catarina 1
- Sao Paulo 1
- Sergipe 1
- Tocantins 1
country_or_region 1
- Brazil · 27 ✖
Link | rowid | day ▲ | country_or_region | province_or_state | admin2 | fips | confirmed | deaths | recovered | active | latitude | longitude | last_update | combined_key |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3061711 | 3061711 | 2022-01-29 | Brazil | Acre | 97829 | 1866 | 0 | -9.0238 | -70.812 | 2022-01-30 04:21:26 | Acre, Brazil | |||
3061712 | 3061712 | 2022-01-29 | Brazil | Alagoas | 257136 | 6431 | 0 | -9.5713 | -36.782 | 2022-01-30 04:21:26 | Alagoas, Brazil | |||
3061713 | 3061713 | 2022-01-29 | Brazil | Amapa | 150433 | 2049 | 0 | 0.902 | -52.003 | 2022-01-30 04:21:26 | Amapa, Brazil | |||
3061714 | 3061714 | 2022-01-29 | Brazil | Amazonas | 526320 | 13929 | 0 | -3.4168 | -65.8561 | 2022-01-30 04:21:26 | Amazonas, Brazil | |||
3061715 | 3061715 | 2022-01-29 | Brazil | Bahia | 1355500 | 27907 | 0 | -12.5797 | -41.7007 | 2022-01-30 04:21:26 | Bahia, Brazil | |||
3061716 | 3061716 | 2022-01-29 | Brazil | Ceara | 1107160 | 25237 | 0 | -5.4984 | -39.3206 | 2022-01-30 04:21:26 | Ceara, Brazil | |||
3061717 | 3061717 | 2022-01-29 | Brazil | Distrito Federal | 595257 | 11164 | 0 | -15.7998 | -47.8645 | 2022-01-30 04:21:26 | Distrito Federal, Brazil | |||
3061718 | 3061718 | 2022-01-29 | Brazil | Espirito Santo | 827360 | 13487 | 0 | -19.1834 | -40.3089 | 2022-01-30 04:21:26 | Espirito Santo, Brazil | |||
3061719 | 3061719 | 2022-01-29 | Brazil | Goias | 1035258 | 25002 | 0 | -15.827 | -49.8362 | 2022-01-30 04:21:26 | Goias, Brazil | |||
3061720 | 3061720 | 2022-01-29 | Brazil | Maranhao | 385884 | 10477 | 0 | -4.9609 | -45.2744 | 2022-01-30 04:21:26 | Maranhao, Brazil | |||
3061721 | 3061721 | 2022-01-29 | Brazil | Mato Grosso | 624006 | 14269 | 0 | -12.6819 | -56.9211 | 2022-01-30 04:21:26 | Mato Grosso, Brazil | |||
3061722 | 3061722 | 2022-01-29 | Brazil | Mato Grosso do Sul | 419274 | 9857 | 0 | -20.7722 | -54.7852 | 2022-01-30 04:21:26 | Mato Grosso do Sul, Brazil | |||
3061723 | 3061723 | 2022-01-29 | Brazil | Minas Gerais | 2680134 | 57214 | 0 | -18.5122 | -44.555 | 2022-01-30 04:21:26 | Minas Gerais, Brazil | |||
3061724 | 3061724 | 2022-01-29 | Brazil | Para | 647628 | 17340 | 0 | -1.9981 | -54.9306 | 2022-01-30 04:21:26 | Para, Brazil | |||
3061725 | 3061725 | 2022-01-29 | Brazil | Paraiba | 494098 | 9695 | 0 | -7.24 | -36.782 | 2022-01-30 04:21:26 | Paraiba, Brazil | |||
3061726 | 3061726 | 2022-01-29 | Brazil | Parana | 1941986 | 41185 | 0 | -25.2521 | -52.0215 | 2022-01-30 04:21:26 | Parana, Brazil | |||
3061727 | 3061727 | 2022-01-29 | Brazil | Pernambuco | 695094 | 20627 | 0 | -8.8137 | -36.9541 | 2022-01-30 04:21:26 | Pernambuco, Brazil | |||
3061728 | 3061728 | 2022-01-29 | Brazil | Piaui | 342655 | 7368 | 0 | -7.7183 | -42.7289 | 2022-01-30 04:21:26 | Piaui, Brazil | |||
3061729 | 3061729 | 2022-01-29 | Brazil | Rio Grande do Norte | 423505 | 7696 | 0 | -5.4026 | -36.9541 | 2022-01-30 04:21:26 | Rio Grande do Norte, Brazil | |||
3061730 | 3061730 | 2022-01-29 | Brazil | Rio Grande do Sul | 1814198 | 36853 | 0 | -30.0346 | -51.2177 | 2022-01-30 04:21:26 | Rio Grande do Sul, Brazil | |||
3061731 | 3061731 | 2022-01-29 | Brazil | Rio de Janeiro | 1747887 | 69849 | 0 | -22.9068 | -43.1729 | 2022-01-30 04:21:26 | Rio de Janeiro, Brazil | |||
3061732 | 3061732 | 2022-01-29 | Brazil | Rondonia | 314027 | 6827 | 0 | -11.5057 | -63.5806 | 2022-01-30 04:21:26 | Rondonia, Brazil | |||
3061733 | 3061733 | 2022-01-29 | Brazil | Roraima | 141628 | 2096 | 0 | -2.7376 | -62.0751 | 2022-01-30 04:21:26 | Roraima, Brazil | |||
3061734 | 3061734 | 2022-01-29 | Brazil | Santa Catarina | 1435746 | 20542 | 0 | -27.2423 | -50.2189 | 2022-01-30 04:21:26 | Santa Catarina, Brazil | |||
3061735 | 3061735 | 2022-01-29 | Brazil | Sao Paulo | 4638360 | 157817 | 0 | -23.5505 | -46.6333 | 2022-01-30 04:21:26 | Sao Paulo, Brazil | |||
3061736 | 3061736 | 2022-01-29 | Brazil | Sergipe | 290298 | 6089 | 0 | -10.5741 | -37.3857 | 2022-01-30 04:21:26 | Sergipe, Brazil | |||
3061737 | 3061737 | 2022-01-29 | Brazil | Tocantins | 267537 | 3997 | 0 | -10.1753 | -48.2982 | 2022-01-30 04:21:26 | Tocantins, Brazil |
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CREATE TABLE [johns_hopkins_csse_daily_reports] ( [day] TEXT, [country_or_region] TEXT, [province_or_state] TEXT, [admin2] TEXT, [fips] TEXT, [confirmed] INTEGER, [deaths] INTEGER, [recovered] INTEGER, [active] TEXT, [latitude] TEXT, [longitude] TEXT, [last_update] TEXT, [combined_key] TEXT ); CREATE INDEX [idx_johns_hopkins_csse_daily_reports_day] ON [johns_hopkins_csse_daily_reports] ([day]); CREATE INDEX [idx_johns_hopkins_csse_daily_reports_province_or_state] ON [johns_hopkins_csse_daily_reports] ([province_or_state]); CREATE INDEX [idx_johns_hopkins_csse_daily_reports_country_or_region] ON [johns_hopkins_csse_daily_reports] ([country_or_region]); CREATE INDEX [idx_johns_hopkins_csse_daily_reports_combined_key] ON [johns_hopkins_csse_daily_reports] ([combined_key]);