JHU CSSE COVID-19 Daily Updates
Dataset published by xristosk
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Global daily updates (aggregated)
29 commits1,066,430 rows153.9MBcsv
HEAD Znt1geE updated structure, readme, and body
11 days ago
Readme
JHU CSSE COVID-19 Daily Reports (aggregated)
Taken from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, this dataset is an aggregation of all the CSV files in the daily updates folder.
Meta
Standard Metadata
| description | Global daily updates (aggregated) |
| keywords | covid-19 |
| title | JHU CSSE COVID-19 Daily Updates |
Additional Metadata
| describe | Global daily updates (aggregated) |
Structure
CSV
146.76 MB
1,066,430
8,531,440
2
CSV Configuration
This table contains a header row
This table has rows with different lengths
This table uses different quotes to indicate strings
Schema
| title | type | description |
|---|---|---|
| fips | string | |
| admin2 | string | |
| confirmed | number | |
| deaths | number | |
| recovered | number | |
| active | number | |
| combined_key | string | |
| incidence_rate | number | |
| case-fatality_ratio | number | |
| lat | number | |
| long_ | number | |
| province_state | string | |
| country_region | string | |
| last_update | string |
Body Preview
| qri-row-number | fips | admin2 | confirmed | deaths | recovered | active | combined_key | incidence_rate | case-fatality_ratio | lat | long_ | province_state | country_region | last_update |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 51526.0 | 2191.0 | 41727.0 | 5.0 | Afghanistan | 0.30312106030924874 | 4.2522221790940495 | 33.93911 | 67.709953 | nan | ||||
| 2 | 58991.0 | 1190.0 | 34353.0 | 23448.0 | Albania | 2049.8644798109667 | 2.0172568696919866 | 41.1533 | 20.1683 | nan | ||||
| 3 | 100159.0 | 2769.0 | 67611.0 | 29779.0 | Algeria | 228.4073379964988 | 2.764604279196078 | 28.0339 | 1.6596 | nan | ||||
| 4 | 8166.0 | 84.0 | 7463.0 | 619.0 | Andorra | 10568.821588041155 | 1.0286554004408524 | 42.5063 | 1.5218 | nan | ||||
| 5 | 17608.0 | 407.0 | 11189.0 | 6012.0 | Angola | 53.57468636232139 | 2.311449341208541 | -11.2027 | 17.8739 | nan | ||||
| 6 | 159.0 | 5.0 | 148.0 | 6.0 | Antigua and Barbuda | 162.36418593252185 | 3.1446540880503147 | 17.0608 | -61.7964 | nan | ||||
| 7 | 1634834.0 | 43375.0 | 1447092.0 | 144367.0 | Argentina | 3617.227335199924 | 2.653174573075921 | -38.4161 | -63.6167 | nan | ||||
| 8 | 159798.0 | 2836.0 | 143640.0 | 13322.0 | Armenia | 5392.689203755086 | 1.7747406100201504 | 40.0691 | 45.0382 | nan | ||||
| 9 | 118.0 | 3.0 | 114.0 | 1.0 | Australian Capital Territory, Australia | 27.563653352020555 | 2.5423728813559316 | -35.4735 | 149.0124 | Australian Capital Territory | ||||
| 10 | 4958.0 | 54.0 | 3197.0 | 1707.0 | New South Wales, Australia | 61.074156196107424 | 1.08914885034288 | -33.8688 | 151.2093 | New South Wales | ||||
| 11 | 81.0 | 0.0 | 71.0 | 10.0 | Northern Territory, Australia | 32.98045602605863 | 0.0 | -12.4634 | 130.8456 | Northern Territory | ||||
| 12 | 1255.0 | 6.0 | 1232.0 | 17.0 | Queensland, Australia | 24.533281204183364 | 0.4780876494023905 | -27.4698 | 153.0251 | Queensland | ||||
| 13 | 580.0 | 4.0 | 566.0 | 10.0 | South Australia, Australia | 33.020210646171364 | 0.6896551724137931 | -34.9285 | 138.6007 | South Australia | ||||
| 14 | 234.0 | 13.0 | 221.0 | 0.0 | Tasmania, Australia | 43.69747899159664 | 5.5555555555555545 | -42.8821 | 147.3272 | Tasmania | ||||
| 15 | 20391.0 | 820.0 | 19539.0 | 32.0 | Victoria, Australia | 307.56120001809984 | 4.02138198224707 | -37.8136 | 144.9631 | Victoria | ||||
| 16 | 867.0 | 9.0 | 838.0 | 20.0 | Western Australia, Australia | 32.958260472895915 | 1.038062283737024 | -31.9505 | 115.8605 | Western Australia | ||||
| 17 | 364302.0 | 6275.0 | 336922.0 | 21105.0 | Austria | 4044.9236098774213 | 1.7224720149765853 | 47.5162 | 14.5501 | nan | ||||
| 18 | 219462.0 | 2703.0 | 191925.0 | 24834.0 | Azerbaijan | 2164.4956320410683 | 1.2316483035787518 | 40.1431 | 47.5769 | nan | ||||
| 19 | 7887.0 | 171.0 | 6239.0 | 1477.0 | Bahamas | 2005.6046057449755 | 2.1681247622670217 | 25.025885 | -78.035889 | nan | ||||
| 20 | 93184.0 | 352.0 | 90558.0 | 2274.0 | Bahrain | 5476.312351498576 | 0.3777472527472528 | 26.0275 | 50.55 | nan | ||||
| 21 | 515184.0 | 7599.0 | 459620.0 | 47965.0 | Bangladesh | 312.8216225085985 | 1.475006987794652 | 23.685 | 90.3563 | nan | ||||
| 22 | 395.0 | 7.0 | 319.0 | 69.0 | Barbados | 137.45297890183772 | 1.7721518987341771 | 13.1939 | -59.5432 | nan | ||||
| 23 | 198125.0 | 1442.0 | 181109.0 | 15574.0 | Belarus | 2096.7114991648605 | 0.7278233438485805 | 53.7098 | 27.9534 | nan | ||||
| 24 | 79829.0 | 0.0 | 0.0 | 79829.0 | Antwerp, Belgium | 4296.533988953631 | 0.0 | 51.2195 | 4.4024 | Antwerp | ||||
| 25 | 81663.0 | 0.0 | 0.0 | 81663.0 | Brussels, Belgium | 6757.1503514151755 | 0.0 | 50.8503 | 4.3517 | Brussels | ||||
| 26 | 65351.0 | 0.0 | 0.0 | 65351.0 | East Flanders, Belgium | 4313.415142858652 | 0.0 | 51.0362 | 3.7373 | East Flanders | ||||
| 27 | 49320.0 | 0.0 | 0.0 | 49320.0 | Flemish Brabant, Belgium | 4303.007830392392 | 0.0 | 50.9167 | 4.5833 | Flemish Brabant | ||||
| 28 | 102333.0 | 0.0 | 0.0 | 102333.0 | Hainaut, Belgium | 7612.6974255360465 | 0.0 | 50.5257 | 4.0621 | Hainaut | ||||
| 29 | 97071.0 | 0.0 | 0.0 | 97071.0 | Liege, Belgium | 8768.898058883895 | 0.0 | 50.4496 | 5.8492 | Liege | ||||
| 30 | 29434.0 | 0.0 | 0.0 | 29434.0 | Limburg, Belgium | 3367.549608259501 | 0.0 | 50.9739 | 5.3420000000000005 | Limburg | ||||
| 31 | 18457.0 | 0.0 | 0.0 | 18457.0 | Luxembourg, Belgium | 6484.376646828604 | 0.0 | 50.0547 | 5.4677 | Luxembourg | ||||
| 32 | 35495.0 | 0.0 | 0.0 | 35495.0 | Namur, Belgium | 7180.498659788601 | 0.0 | 50.331 | 4.8221 | Namur | ||||
| 33 | 25167.0 | 0.0 | 0.0 | 25167.0 | Walloon Brabant, Belgium | 6235.644786037627 | 0.0 | 50.4 | 4.35 | Walloon Brabant | ||||
| 34 | 54326.0 | 0.0 | 0.0 | 54326.0 | West Flanders, Belgium | 4543.082599373137 | 0.0 | 51.0536 | 3.1458 | West Flanders | ||||
| 35 | 10807.0 | 249.0 | 9950.0 | 608.0 | Belize | 2717.9147982626673 | 2.3040621819191265 | 17.1899 | -88.4976 | nan | ||||
| 36 | 3251.0 | 44.0 | 3061.0 | 146.0 | Benin | 26.816356542225904 | 1.3534297139341742 | 9.3077 | 2.3158 | nan | ||||
| 37 | 710.0 | 0.0 | 450.0 | 260.0 | Bhutan | 92.01515787727509 | 0.0 | 27.5142 | 90.4336 | nan | ||||
| 38 | 162055.0 | 9186.0 | 133013.0 | 19856.0 | Bolivia | 1388.2857654170139 | 5.668445897997594 | -16.2902 | -63.5887 | nan | ||||
| 39 | 112143.0 | 4086.0 | 77682.0 | 30375.0 | Bosnia and Herzegovina | 3418.144576881049 | 3.6435622375003343 | 43.9159 | 17.6791 | nan | ||||
| 40 | 14805.0 | 42.0 | 12136.0 | 2627.0 | Botswana | 629.5646627332164 | 0.28368794326241137 | -22.3285 | 24.6849 | nan | ||||
| 41 | 41941.0 | 798.0 | 33693.0 | 7450.0 | Acre, Brazil | 4755.565886374846 | 1.9026728022698556 | -9.0238 | -70.812 | Acre | ||||
| 42 | 105361.0 | 2502.0 | 100531.0 | 2328.0 | Alagoas, Brazil | 3157.0191621693452 | 2.3746927231138657 | -9.5713 | -36.782 | Alagoas | ||||
| 43 | 68441.0 | 927.0 | 52777.0 | 14737.0 | Amapa, Brazil | 8092.52587406634 | 1.354451279203986 | 0.902 | -52.003 | Amapa | ||||
| 44 | 201867.0 | 5325.0 | 171819.0 | 24723.0 | Amazonas, Brazil | 4870.606237470133 | 2.63787543283449 | -3.4168 | -65.8561 | Amazonas | ||||
| 45 | 495286.0 | 9187.0 | 481009.0 | 5090.0 | Bahia, Brazil | 3330.0871965588262 | 1.854887882960552 | -12.5797 | -41.7007 | Bahia | ||||
| 46 | 336574.0 | 10015.0 | 270203.0 | 56356.0 | Ceara, Brazil | 3685.6233597654327 | 2.9755714939359548 | -5.4984 | -39.3206 | Ceara | ||||
| 47 | 252874.0 | 4268.0 | 241952.0 | 6654.0 | Distrito Federal, Brazil | 8386.451884210624 | 1.6877970847141264 | -15.7998 | -47.8645 | Distrito Federal | ||||
| 48 | 250227.0 | 5113.0 | 229191.0 | 15923.0 | Espirito Santo, Brazil | 6226.643275726922 | 2.0433446430640982 | -19.1834 | -40.3089 | Espirito Santo | ||||
| 49 | 309194.0 | 6805.0 | 298693.0 | 3696.0 | Goias, Brazil | 4405.505906370639 | 2.2008835876504715 | -15.827 | -49.8362 | Goias | ||||
| 50 | 200976.0 | 4513.0 | 190889.0 | 5574.0 | Maranhao, Brazil | 2840.5775060736964 | 2.2455417562296 | -4.9609 | -45.2744 | Maranhao | ||||
| 51 | 179938.0 | 4475.0 | 170648.0 | 4815.0 | Mato Grosso, Brazil | 5164.005044101449 | 2.486967733330369 | -12.6819 | -56.9211 | Mato Grosso | ||||
| 52 | 135361.0 | 2360.0 | 119295.0 | 13706.0 | Mato Grosso do Sul, Brazil | 4870.877363182111 | 1.7434859376038891 | -20.7722 | -54.7852 | Mato Grosso do Sul | ||||
| 53 | 549302.0 | 12023.0 | 496011.0 | 41268.0 | Minas Gerais, Brazil | 2594.867132468737 | 2.188777757954641 | -18.5122 | -44.555 | Minas Gerais | ||||
| 54 | 293807.0 | 7209.0 | 276014.0 | 10584.0 | Para, Brazil | 3415.222719408011 | 2.453651546763692 | -1.9981 | -54.9306 | Para | ||||
| 55 | 167615.0 | 3692.0 | 127509.0 | 36414.0 | Paraiba, Brazil | 4171.4709365831395 | 2.2026668257614177 | -7.24 | -36.782 | Paraiba | ||||
| 56 | 419615.0 | 8001.0 | 306432.0 | 105182.0 | Parana, Brazil | 3669.9018546247808 | 1.9067478521978483 | -25.2521 | -52.0215 | Parana | ||||
| 57 | 223325.0 | 9674.0 | 189942.0 | 23709.0 | Pernambuco, Brazil | 2336.751500538188 | 4.331803425500952 | -8.8137 | -36.9541 | Pernambuco | ||||
| 58 | 143210.0 | 2848.0 | 140229.0 | 133.0 | Piaui, Brazil | 4375.1930434400065 | 1.9886879407862577 | -7.7183 | -42.7289 | Piaui | ||||
| 59 | 118691.0 | 2995.0 | 68394.0 | 47302.0 | Rio Grande do Norte, Brazil | 3384.544490459109 | 2.5233589741429427 | -5.4026 | -36.9541 | Rio Grande do Norte | ||||
| 60 | 452920.0 | 8934.0 | 430061.0 | 13925.0 | Rio Grande do Sul, Brazil | 3980.930698564037 | 1.9725337808001413 | -30.0346 | -51.2177 | Rio Grande do Sul | ||||
| 61 | 435604.0 | 25608.0 | 405164.0 | 4832.0 | Rio de Janeiro, Brazil | 2523.0549559300603 | 5.878733895923821 | -22.9068 | -43.1729 | Rio de Janeiro | ||||
| 62 | 96433.0 | 1825.0 | 81914.0 | 12694.0 | Rondonia, Brazil | 5426.043410372913 | 1.8925056775170328 | -11.5057 | -63.5806 | Rondonia | ||||
| 63 | 68858.0 | 787.0 | 65405.0 | 2666.0 | Roraima, Brazil | 11367.18937006509 | 1.1429318307240988 | -2.7376 | -62.0751 | Roraima | ||||
| 64 | 496524.0 | 5294.0 | 469769.0 | 21461.0 | Santa Catarina, Brazil | 6930.0585027777515 | 1.0662123079649726 | -27.2423 | -50.2189 | Santa Catarina | ||||
| 65 | 1467953.0 | 46808.0 | 1294620.0 | 126525.0 | Sao Paulo, Brazil | 3196.827965666275 | 3.188657947495594 | -23.5505 | -46.6333 | Sao Paulo | ||||
| 66 | 113916.0 | 2500.0 | 99959.0 | 11457.0 | Sergipe, Brazil | 4955.679219870744 | 2.194599529477861 | -10.5741 | -37.3857 | Sergipe | ||||
| 67 | 90592.0 | 1239.0 | 81133.0 | 8220.0 | Tocantins, Brazil | 5759.676920983733 | 1.3676704344754504 | -10.1753 | -48.2982 | Tocantins | ||||
| 68 | 157.0 | 3.0 | 149.0 | 5.0 | Brunei | 35.88710875622596 | 1.9108280254777068 | 4.5353 | 114.7277 | nan | ||||
| 69 | 202880.0 | 7644.0 | 121467.0 | 73769.0 | Bulgaria | 2919.789967395582 | 3.767744479495268 | 42.7339 | 25.4858 | nan | ||||
| 70 | 6940.0 | 86.0 | 5253.0 | 1601.0 | Burkina Faso | 33.20053438508544 | 1.239193083573487 | 12.2383 | -1.5616 | nan | ||||
| 71 | 125616.0 | 2711.0 | 108660.0 | 14245.0 | Burma | 230.8701995820826 | 2.158164565023564 | 21.9162 | 95.956 | nan | ||||
| 72 | 822.0 | 2.0 | 687.0 | 133.0 | Burundi | 6.9129185038392365 | 0.24330900243309006 | -3.3731 | 29.9189 | nan | ||||
| 73 | 11883.0 | 113.0 | 11578.0 | 192.0 | Cabo Verde | 2137.2763440937574 | 0.9509383152402592 | 16.5388 | -23.0418 | nan | ||||
| 74 | 381.0 | 0.0 | 362.0 | 19.0 | Cambodia | 2.2788483812789675 | 0.0 | 11.55 | 104.9167 | nan | ||||
| 75 | 26848.0 | 448.0 | 24892.0 | 1508.0 | Cameroon | 101.13816600582298 | 1.66865315852205 | 3.8480000000000003 | 11.5021 | nan | ||||
| 76 | 100428.0 | 1046.0 | 84827.0 | 14555.0 | Alberta, Canada | 2275.6555074316598 | 1.0415421993866252 | 53.9333 | -116.5765 | Alberta | ||||
| 77 | 51990.0 | 901.0 | 42127.0 | 8962.0 | British Columbia, Canada | 1017.2342849629528 | 1.7330255818426619 | 53.7267 | -127.6476 | British Columbia | ||||
| 78 | 25026.0 | 678.0 | 19789.0 | 4559.0 | Manitoba, Canada | 1816.7470891466312 | 2.7091824502517383 | 53.7609 | -98.8139 | Manitoba | ||||
| 79 | 611.0 | 9.0 | 567.0 | 35.0 | New Brunswick, Canada | 78.33403633109529 | 1.4729950900163666 | 46.5653 | -66.4619 | New Brunswick | ||||
| 80 | 390.0 | 4.0 | 372.0 | 14.0 | Newfoundland and Labrador, Canada | 74.80364044383494 | 1.0256410256410255 | 53.1355 | -57.6604 | Newfoundland and Labrador | ||||
| 81 | 24.0 | 0.0 | 24.0 | 0.0 | Northwest Territories,Canada | 53.447354355959384 | 0.0 | 64.8255 | -124.8457 | Northwest Territories | ||||
| 82 | 1499.0 | 65.0 | 1407.0 | 27.0 | Nova Scotia, Canada | 153.35712977655282 | 4.3362241494329545 | 44.681999999999995 | -63.7443 | Nova Scotia | ||||
| 83 | 266.0 | 1.0 | 262.0 | 3.0 | Nunavut, Canada | 685.9205776173285 | 0.3759398496240601 | 70.2998 | -83.1076 | Nunavut | ||||
| 84 | 191035.0 | 4617.0 | 164923.0 | 21495.0 | Ontario, Canada | 1298.5130942608284 | 2.416834611458633 | 51.2538 | -85.3232 | Ontario | ||||
| 85 | 94.0 | 0.0 | 89.0 | 5.0 | Prince Edward Island, Canada | 59.43423664942652 | 0.0 | 46.5107 | -63.4168 | Prince Edward Island | ||||
| 86 | 202641.0 | 8226.0 | 170045.0 | 24370.0 | Quebec, Canada | 2373.491890179925 | 4.0593956800450055 | 52.9399 | -73.5491 | Quebec | ||||
| 87 | 15845.0 | 158.0 | 12975.0 | 2712.0 | Saskatchewan, Canada | 1340.9034363348019 | 0.9971599873777216 | 52.9399 | -106.4509 | Saskatchewan | ||||
| 88 | 60.0 | 1.0 | 59.0 | 0.0 | Yukon, Canada | 146.06358634792346 | 1.6666666666666667 | 64.2823 | -135.0 | Yukon | ||||
| 89 | 4963.0 | 63.0 | 1924.0 | 2976.0 | Central African Republic | 102.7586441076624 | 1.2693935119887163 | 6.6111 | 20.9394 | nan | ||||
| 90 | 2169.0 | 104.0 | 1710.0 | 355.0 | Chad | 13.204788863705698 | 4.79483633010604 | 15.4542 | 18.7322 | nan | ||||
| 91 | 24049.0 | 586.0 | 22773.0 | 690.0 | Antofagasta, Chile | 3958.461584043033 | 2.4366917543349 | -23.6509 | -70.3975 | Antofagasta | ||||
| 92 | 23395.0 | 314.0 | 21957.0 | 1124.0 | Araucania, Chile | 2444.046534562443 | 1.3421671297285744 | -38.9489 | -72.3311 | Araucania | ||||
| 93 | 10906.0 | 227.0 | 10433.0 | 246.0 | Arica y Parinacota, Chile | 4824.212183944654 | 2.0814230698697966 | -18.594 | -69.4785 | Arica y Parinacota | ||||
| 94 | 8554.0 | 113.0 | 8351.0 | 90.0 | Atacama, Chile | 2960.435240046514 | 1.3210194061257892 | -27.5661 | -70.0503 | Atacama | ||||
| 95 | 1609.0 | 15.0 | 1464.0 | 130.0 | Aysen, Chile | 1559.7433063843812 | 0.9322560596643878 | -45.9864 | -73.7669 | Aysen | ||||
| 96 | 48380.0 | 810.0 | 44842.0 | 2728.0 | Biobio, Chile | 3107.646750877598 | 1.674245556014882 | -37.4464 | -72.1416 | Biobio | ||||
| 97 | 14358.0 | 301.0 | 13794.0 | 263.0 | Coquimbo, Chile | 1895.23037648531 | 2.096392255188745 | -29.959 | -71.3389 | Coquimbo | ||||
| 98 | 26659.0 | 267.0 | 24613.0 | 1779.0 | Los Lagos, Chile | 3216.935277564595 | 1.0015379421583706 | -41.9198 | -72.1416 | Los Lagos | ||||
| 99 | 9193.0 | 98.0 | 8352.0 | 743.0 | Los Rios, Chile | 2388.8035713821696 | 1.0660284999456109 | -40.231 | -72.3311 | Los Rios | ||||
| 100 | 17104.0 | 233.0 | 16336.0 | 535.0 | Magallanes, Chile | 10270.637050914831 | 1.3622544434050514 | -52.368 | -70.9863 | Magallanes |
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