johns_hopkins_csse_daily_reports
Data source: Johns Hopkins CSSE · About: simonw/covid-19-datasette
27 rows where country_or_region = "Brazil" and "day" is on date 2022-01-03 sorted by day descending
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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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1700062 | 1700062 | 2022-01-03 | Brazil | Acre | 88395 | 1851 | 0 | -9.0238 | -70.812 | 2022-01-04 04:22:17 | Acre, Brazil | |||
1700063 | 1700063 | 2022-01-03 | Brazil | Alagoas | 242108 | 6383 | 0 | -9.5713 | -36.782 | 2022-01-04 04:22:17 | Alagoas, Brazil | |||
1700064 | 1700064 | 2022-01-03 | Brazil | Amapa | 127080 | 2023 | 0 | 0.902 | -52.003 | 2022-01-04 04:22:17 | Amapa, Brazil | |||
1700065 | 1700065 | 2022-01-03 | Brazil | Amazonas | 433970 | 13838 | 0 | -3.4168 | -65.8561 | 2022-01-04 04:22:17 | Amazonas, Brazil | |||
1700066 | 1700066 | 2022-01-03 | Brazil | Bahia | 1271250 | 27519 | 0 | -12.5797 | -41.7007 | 2022-01-04 04:22:17 | Bahia, Brazil | |||
1700067 | 1700067 | 2022-01-03 | Brazil | Ceara | 957373 | 24815 | 0 | -5.4984 | -39.3206 | 2022-01-04 04:22:17 | Ceara, Brazil | |||
1700068 | 1700068 | 2022-01-03 | Brazil | Distrito Federal | 520538 | 11110 | 0 | -15.7998 | -47.8645 | 2022-01-04 04:22:17 | Distrito Federal, Brazil | |||
1700069 | 1700069 | 2022-01-03 | Brazil | Espirito Santo | 630389 | 13335 | 0 | -19.1834 | -40.3089 | 2022-01-04 04:22:17 | Espirito Santo, Brazil | |||
1700070 | 1700070 | 2022-01-03 | Brazil | Goias | 948282 | 24699 | 0 | -15.827 | -49.8362 | 2022-01-04 04:22:17 | Goias, Brazil | |||
1700071 | 1700071 | 2022-01-03 | Brazil | Maranhao | 370747 | 10381 | 0 | -4.9609 | -45.2744 | 2022-01-04 04:22:17 | Maranhao, Brazil | |||
1700072 | 1700072 | 2022-01-03 | Brazil | Mato Grosso | 558344 | 14064 | 0 | -12.6819 | -56.9211 | 2022-01-04 04:22:17 | Mato Grosso, Brazil | |||
1700073 | 1700073 | 2022-01-03 | Brazil | Mato Grosso do Sul | 380653 | 9732 | 0 | -20.7722 | -54.7852 | 2022-01-04 04:22:17 | Mato Grosso do Sul, Brazil | |||
1700074 | 1700074 | 2022-01-03 | Brazil | Minas Gerais | 2226164 | 56668 | 0 | -18.5122 | -44.555 | 2022-01-04 04:22:17 | Minas Gerais, Brazil | |||
1700075 | 1700075 | 2022-01-03 | Brazil | Para | 625982 | 17098 | 0 | -1.9981 | -54.9306 | 2022-01-04 04:22:17 | Para, Brazil | |||
1700076 | 1700076 | 2022-01-03 | Brazil | Paraiba | 464590 | 9600 | 0 | -7.24 | -36.782 | 2022-01-04 04:22:17 | Paraiba, Brazil | |||
1700077 | 1700077 | 2022-01-03 | Brazil | Parana | 1600140 | 40891 | 0 | -25.2521 | -52.0215 | 2022-01-04 04:22:17 | Parana, Brazil | |||
1700078 | 1700078 | 2022-01-03 | Brazil | Pernambuco | 646004 | 20465 | 0 | -8.8137 | -36.9541 | 2022-01-04 04:22:17 | Pernambuco, Brazil | |||
1700079 | 1700079 | 2022-01-03 | Brazil | Piaui | 334582 | 7281 | 0 | -7.7183 | -42.7289 | 2022-01-04 04:22:17 | Piaui, Brazil | |||
1700080 | 1700080 | 2022-01-03 | Brazil | Rio Grande do Norte | 387542 | 7573 | 0 | -5.4026 | -36.9541 | 2022-01-04 04:22:17 | Rio Grande do Norte, Brazil | |||
1700081 | 1700081 | 2022-01-03 | Brazil | Rio Grande do Sul | 1508446 | 36445 | 0 | -30.0346 | -51.2177 | 2022-01-04 04:22:17 | Rio Grande do Sul, Brazil | |||
1700082 | 1700082 | 2022-01-03 | Brazil | Rio de Janeiro | 1356863 | 69472 | 0 | -22.9068 | -43.1729 | 2022-01-04 04:22:17 | Rio de Janeiro, Brazil | |||
1700083 | 1700083 | 2022-01-03 | Brazil | Rondonia | 284783 | 6742 | 0 | -11.5057 | -63.5806 | 2022-01-04 04:22:17 | Rondonia, Brazil | |||
1700084 | 1700084 | 2022-01-03 | Brazil | Roraima | 129086 | 2078 | 0 | -2.7376 | -62.0751 | 2022-01-04 04:22:17 | Roraima, Brazil | |||
1700085 | 1700085 | 2022-01-03 | Brazil | Santa Catarina | 1244569 | 20194 | 0 | -27.2423 | -50.2189 | 2022-01-04 04:22:17 | Santa Catarina, Brazil | |||
1700086 | 1700086 | 2022-01-03 | Brazil | Sao Paulo | 4456745 | 155216 | 0 | -23.5505 | -46.6333 | 2022-01-04 04:22:17 | Sao Paulo, Brazil | |||
1700087 | 1700087 | 2022-01-03 | Brazil | Sergipe | 278539 | 6058 | 0 | -10.5741 | -37.3857 | 2022-01-04 04:22:17 | Sergipe, Brazil | |||
1700088 | 1700088 | 2022-01-03 | Brazil | Tocantins | 235917 | 3942 | 0 | -10.1753 | -48.2982 | 2022-01-04 04:22:17 | 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]);