14-day cumulative number of COVID-19 cases per 100 000¶
At the end of the page, we provide a detailed description of how the numbers are calculated.
Compute data¶
In [1]:
import pandas as pd
pd.set_option("display.max_rows", None)
from oscovida import get_incidence_rates_countries
Table for all countries¶
In [2]:
cases_incidence, deaths_incidence = get_incidence_rates_countries()
Downloaded data: last data point 5/23/22 from https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv Downloaded data: last data point 5/23/22 from https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv
In [3]:
cases_incidence
Out[3]:
14-day-sum | population | 14-day-incidence-rate | |
---|---|---|---|
Country | |||
Afghanistan | 706 | 38928341 | 1.8 |
Albania | 509 | 2877800 | 17.7 |
Algeria | 55 | 43851043 | 0.1 |
Andorra | 855 | 77265 | 1106.6 |
Angola | 0 | 32866268 | 0.0 |
Antarctica | 0 | 0 | NaN |
Antigua and Barbuda | 319 | 97928 | 325.7 |
Argentina | 77476 | 45195777 | 171.4 |
Armenia | 43 | 2963234 | 1.5 |
Australia | 690958 | 25459700 | 2713.9 |
Austria | 51582 | 9006400 | 572.7 |
Azerbaijan | 82 | 10139175 | 0.8 |
Bahamas | 555 | 393248 | 141.1 |
Bahrain | 8109 | 1701583 | 476.6 |
Bangladesh | 435 | 164689383 | 0.3 |
Barbados | 5193 | 287371 | 1807.1 |
Belarus | 536 | 9449321 | 5.7 |
Belgium | 41326 | 11492641 | 359.6 |
Belize | 942 | 397621 | 236.9 |
Benin | 0 | 12123198 | 0.0 |
Bhutan | 102 | 771612 | 13.2 |
Bolivia | 1854 | 11673029 | 15.9 |
Bosnia and Herzegovina | 400 | 3280815 | 12.2 |
Botswana | 414 | 2351625 | 17.6 |
Brazil | 229750 | 212559409 | 108.1 |
Brunei | 3668 | 437483 | 838.4 |
Bulgaria | 3781 | 6948445 | 54.4 |
Burkina Faso | 0 | 20903278 | 0.0 |
Burma | 171 | 54409794 | 0.3 |
Burundi | 1005 | 11890781 | 8.5 |
Cabo Verde | 97 | 555988 | 17.4 |
Cambodia | 0 | 16718971 | 0.0 |
Cameroon | 0 | 26545864 | 0.0 |
Canada | 53732 | 38246108 | 140.5 |
Central African Republic | 0 | 4829764 | 0.0 |
Chad | 3 | 16425859 | 0.0 |
Chile | 65987 | 19116209 | 345.2 |
China | 83049 | 1411778724 | 5.9 |
Colombia | 5466 | 50882884 | 10.7 |
Comoros | 7 | 869595 | 0.8 |
Congo (Brazzaville) | 0 | 5518092 | 0.0 |
Congo (Kinshasa) | 610 | 89561404 | 0.7 |
Costa Rica | 20243 | 5094114 | 397.4 |
Cote d'Ivoire | 96 | 26378275 | 0.4 |
Croatia | 6470 | 4105268 | 157.6 |
Cuba | 959 | 11326616 | 8.5 |
Cyprus | 4525 | 1207361 | 374.8 |
Czechia | 6050 | 10708982 | 56.5 |
Denmark | 7056 | 5837213 | 120.9 |
Diamond Princess | 0 | 0 | NaN |
Djibouti | 44 | 988002 | 4.5 |
Dominica | 1259 | 71991 | 1748.8 |
Dominican Republic | 1721 | 10847904 | 15.9 |
Ecuador | 3690 | 17643060 | 20.9 |
Egypt | 0 | 102334403 | 0.0 |
El Salvador | 0 | 6486201 | 0.0 |
Equatorial Guinea | 0 | 1402985 | 0.0 |
Eritrea | 17 | 3546427 | 0.5 |
Estonia | 2612 | 1326539 | 196.9 |
Eswatini | 987 | 1160164 | 85.1 |
Ethiopia | 663 | 114963583 | 0.6 |
Fiji | 173 | 896444 | 19.3 |
Finland | 28458 | 5540718 | 513.6 |
France | 395520 | 65249843 | 606.2 |
Gabon | 14 | 2225728 | 0.6 |
Gambia | 3 | 2416664 | 0.1 |
Georgia | 0 | 3989175 | 0.0 |
Germany | 703097 | 83155031 | 845.5 |
Ghana | 82 | 31072945 | 0.3 |
Greece | 57635 | 10423056 | 553.0 |
Grenada | 1751 | 112519 | 1556.2 |
Guatemala | 7024 | 17915567 | 39.2 |
Guinea | 112 | 13132792 | 0.9 |
Guinea-Bissau | 31 | 1967998 | 1.6 |
Guyana | 711 | 786559 | 90.4 |
Haiti | 39 | 11402533 | 0.3 |
Holy See | 0 | 809 | 0.0 |
Honduras | 494 | 9904608 | 5.0 |
Hungary | 11497 | 9660350 | 119.0 |
Iceland | 1301 | 341250 | 381.2 |
India | 32379 | 1380004385 | 2.3 |
Indonesia | 4079 | 273523621 | 1.5 |
Iran | 4562 | 83992953 | 5.4 |
Iraq | 1647 | 40222503 | 4.1 |
Ireland | 27280 | 4937796 | 552.5 |
Israel | 29614 | 8655541 | 342.1 |
Italy | 441154 | 60461828 | 729.6 |
Jamaica | 3333 | 2961161 | 112.6 |
Japan | 506306 | 126476458 | 400.3 |
Jordan | 698 | 10203140 | 6.8 |
Kazakhstan | 171 | 18776707 | 0.9 |
Kenya | 374 | 53771300 | 0.7 |
Kiribati | 5 | 117606 | 4.3 |
Korea, North | 1 | 25778815 | 0.0 |
Korea, South | 379090 | 51269183 | 739.4 |
Kosovo | 163 | 1810366 | 9.0 |
Kuwait | 883 | 4270563 | 20.7 |
Kyrgyzstan | 0 | 6524191 | 0.0 |
Laos | 985 | 7275556 | 13.5 |
Latvia | 2566 | 1886202 | 136.0 |
Lebanon | 1065 | 6825442 | 15.6 |
Lesotho | 154 | 2142252 | 7.2 |
Liberia | 21 | 5057677 | 0.4 |
Libya | 68 | 6871287 | 1.0 |
Liechtenstein | 126 | 38137 | 330.4 |
Lithuania | 1952 | 2722291 | 71.7 |
Luxembourg | 3022 | 625976 | 482.8 |
MS Zaandam | 0 | 0 | NaN |
Madagascar | 78 | 27691019 | 0.3 |
Malawi | 124 | 19129955 | 0.6 |
Malaysia | 31729 | 32365998 | 98.0 |
Maldives | 179 | 540542 | 33.1 |
Mali | 117 | 20250834 | 0.6 |
Malta | 1160 | 441539 | 262.7 |
Marshall Islands | 0 | 58413 | 0.0 |
Mauritania | 290 | 4649660 | 6.2 |
Mauritius | 1874 | 1271767 | 147.4 |
Mexico | 14121 | 127792286 | 11.0 |
Micronesia | 0 | 113815 | 0.0 |
Moldova | 739 | 4027690 | 18.3 |
Monaco | 199 | 39244 | 507.1 |
Mongolia | 1837 | 3278292 | 56.0 |
Montenegro | 925 | 628062 | 147.3 |
Morocco | 1433 | 36910558 | 3.9 |
Mozambique | 156 | 31255435 | 0.5 |
Namibia | 5675 | 2540916 | 223.3 |
Nepal | 128 | 29136808 | 0.4 |
Netherlands | 18714 | 17134873 | 109.2 |
New Zealand | 108391 | 4822233 | 2247.7 |
Nicaragua | 0 | 6624554 | 0.0 |
Niger | 45 | 24206636 | 0.2 |
Nigeria | 171 | 206139587 | 0.1 |
North Macedonia | 1052 | 2083380 | 50.5 |
Norway | 3362 | 5421242 | 62.0 |
Oman | 167 | 5106622 | 3.3 |
Pakistan | 1004 | 220892331 | 0.5 |
Palau | 235 | 18008 | 1305.0 |
Panama | 42215 | 4314768 | 978.4 |
Papua New Guinea | 576 | 8947027 | 6.4 |
Paraguay | 565 | 7132530 | 7.9 |
Peru | 6527 | 32971846 | 19.8 |
Philippines | 1935 | 109581085 | 1.8 |
Poland | 4996 | 37846605 | 13.2 |
Portugal | 517362 | 10196707 | 5073.8 |
Qatar | 1938 | 2881060 | 67.3 |
Romania | 6722 | 19237682 | 34.9 |
Russia | 63946 | 145934460 | 43.8 |
Rwanda | 116 | 12952209 | 0.9 |
Saint Kitts and Nevis | 80 | 53192 | 150.4 |
Saint Lucia | 1276 | 183629 | 694.9 |
Saint Vincent and the Grenadines | 141 | 110947 | 127.1 |
Samoa | 1456 | 196130 | 742.4 |
San Marino | 357 | 33938 | 1051.9 |
Sao Tome and Principe | 12 | 219161 | 5.5 |
Saudi Arabia | 7712 | 34813867 | 22.2 |
Senegal | 59 | 16743930 | 0.4 |
Serbia | 4887 | 8737370 | 55.9 |
Seychelles | 888 | 98340 | 903.0 |
Sierra Leone | 0 | 7976985 | 0.0 |
Singapore | 52193 | 5850343 | 892.1 |
Slovakia | 4824 | 5434712 | 88.8 |
Slovenia | 6618 | 2078932 | 318.3 |
Solomon Islands | 1733 | 652858 | 265.4 |
Somalia | 36 | 15893219 | 0.2 |
South Africa | 86909 | 59308690 | 146.5 |
South Sudan | 68 | 11193729 | 0.6 |
Spain | 175918 | 46754783 | 376.3 |
Sri Lanka | 204 | 21413250 | 1.0 |
Sudan | 80 | 43849269 | 0.2 |
Summer Olympics 2020 | 0 | 0 | NaN |
Suriname | 847 | 586634 | 144.4 |
Sweden | 3517 | 10099270 | 34.8 |
Switzerland | 23711 | 8654618 | 274.0 |
Syria | 22 | 17500657 | 0.1 |
Taiwan* | 989136 | 23816775 | 4153.1 |
Tajikistan | 0 | 9537642 | 0.0 |
Tanzania | 1482 | 59734213 | 2.5 |
Thailand | 82169 | 69799978 | 117.7 |
Timor-Leste | 11 | 1318442 | 0.8 |
Togo | 43 | 8278737 | 0.5 |
Tonga | 735 | 105697 | 695.4 |
Trinidad and Tobago | 6862 | 1399491 | 490.3 |
Tunisia | 1077 | 11818618 | 9.1 |
Turkey | 19299 | 84339067 | 22.9 |
US | 1381031 | 329466283 | 419.2 |
Uganda | 4 | 45741000 | 0.0 |
Ukraine | 0 | 43733759 | 0.0 |
United Arab Emirates | 4667 | 9890400 | 47.2 |
United Kingdom | 130483 | 67886004 | 192.2 |
Uruguay | 8355 | 3473727 | 240.5 |
Uzbekistan | 204 | 33469199 | 0.6 |
Vanuatu | 626 | 292680 | 213.9 |
Venezuela | 628 | 28435943 | 2.2 |
Vietnam | 31707 | 97338583 | 32.6 |
West Bank and Gaza | 380 | 5101416 | 7.4 |
Winter Olympics 2022 | 0 | 0 | NaN |
Yemen | 0 | 29825968 | 0.0 |
Zambia | 1038 | 18383956 | 5.6 |
Zimbabwe | 2166 | 14862927 | 14.6 |
Table sorted by 14-day-incidence¶
In [4]:
cases_incidence.sort_values(by=['14-day-incidence-rate'], ascending=False)
Out[4]:
14-day-sum | population | 14-day-incidence-rate | |
---|---|---|---|
Country | |||
Portugal | 517362 | 10196707 | 5073.8 |
Taiwan* | 989136 | 23816775 | 4153.1 |
Australia | 690958 | 25459700 | 2713.9 |
New Zealand | 108391 | 4822233 | 2247.7 |
Barbados | 5193 | 287371 | 1807.1 |
Dominica | 1259 | 71991 | 1748.8 |
Grenada | 1751 | 112519 | 1556.2 |
Palau | 235 | 18008 | 1305.0 |
Andorra | 855 | 77265 | 1106.6 |
San Marino | 357 | 33938 | 1051.9 |
Panama | 42215 | 4314768 | 978.4 |
Seychelles | 888 | 98340 | 903.0 |
Singapore | 52193 | 5850343 | 892.1 |
Germany | 703097 | 83155031 | 845.5 |
Brunei | 3668 | 437483 | 838.4 |
Samoa | 1456 | 196130 | 742.4 |
Korea, South | 379090 | 51269183 | 739.4 |
Italy | 441154 | 60461828 | 729.6 |
Tonga | 735 | 105697 | 695.4 |
Saint Lucia | 1276 | 183629 | 694.9 |
France | 395520 | 65249843 | 606.2 |
Austria | 51582 | 9006400 | 572.7 |
Greece | 57635 | 10423056 | 553.0 |
Ireland | 27280 | 4937796 | 552.5 |
Finland | 28458 | 5540718 | 513.6 |
Monaco | 199 | 39244 | 507.1 |
Trinidad and Tobago | 6862 | 1399491 | 490.3 |
Luxembourg | 3022 | 625976 | 482.8 |
Bahrain | 8109 | 1701583 | 476.6 |
US | 1381031 | 329466283 | 419.2 |
Japan | 506306 | 126476458 | 400.3 |
Costa Rica | 20243 | 5094114 | 397.4 |
Iceland | 1301 | 341250 | 381.2 |
Spain | 175918 | 46754783 | 376.3 |
Cyprus | 4525 | 1207361 | 374.8 |
Belgium | 41326 | 11492641 | 359.6 |
Chile | 65987 | 19116209 | 345.2 |
Israel | 29614 | 8655541 | 342.1 |
Liechtenstein | 126 | 38137 | 330.4 |
Antigua and Barbuda | 319 | 97928 | 325.7 |
Slovenia | 6618 | 2078932 | 318.3 |
Switzerland | 23711 | 8654618 | 274.0 |
Solomon Islands | 1733 | 652858 | 265.4 |
Malta | 1160 | 441539 | 262.7 |
Uruguay | 8355 | 3473727 | 240.5 |
Belize | 942 | 397621 | 236.9 |
Namibia | 5675 | 2540916 | 223.3 |
Vanuatu | 626 | 292680 | 213.9 |
Estonia | 2612 | 1326539 | 196.9 |
United Kingdom | 130483 | 67886004 | 192.2 |
Argentina | 77476 | 45195777 | 171.4 |
Croatia | 6470 | 4105268 | 157.6 |
Saint Kitts and Nevis | 80 | 53192 | 150.4 |
Mauritius | 1874 | 1271767 | 147.4 |
Montenegro | 925 | 628062 | 147.3 |
South Africa | 86909 | 59308690 | 146.5 |
Suriname | 847 | 586634 | 144.4 |
Bahamas | 555 | 393248 | 141.1 |
Canada | 53732 | 38246108 | 140.5 |
Latvia | 2566 | 1886202 | 136.0 |
Saint Vincent and the Grenadines | 141 | 110947 | 127.1 |
Denmark | 7056 | 5837213 | 120.9 |
Hungary | 11497 | 9660350 | 119.0 |
Thailand | 82169 | 69799978 | 117.7 |
Jamaica | 3333 | 2961161 | 112.6 |
Netherlands | 18714 | 17134873 | 109.2 |
Brazil | 229750 | 212559409 | 108.1 |
Malaysia | 31729 | 32365998 | 98.0 |
Guyana | 711 | 786559 | 90.4 |
Slovakia | 4824 | 5434712 | 88.8 |
Eswatini | 987 | 1160164 | 85.1 |
Lithuania | 1952 | 2722291 | 71.7 |
Qatar | 1938 | 2881060 | 67.3 |
Norway | 3362 | 5421242 | 62.0 |
Czechia | 6050 | 10708982 | 56.5 |
Mongolia | 1837 | 3278292 | 56.0 |
Serbia | 4887 | 8737370 | 55.9 |
Bulgaria | 3781 | 6948445 | 54.4 |
North Macedonia | 1052 | 2083380 | 50.5 |
United Arab Emirates | 4667 | 9890400 | 47.2 |
Russia | 63946 | 145934460 | 43.8 |
Guatemala | 7024 | 17915567 | 39.2 |
Romania | 6722 | 19237682 | 34.9 |
Sweden | 3517 | 10099270 | 34.8 |
Maldives | 179 | 540542 | 33.1 |
Vietnam | 31707 | 97338583 | 32.6 |
Turkey | 19299 | 84339067 | 22.9 |
Saudi Arabia | 7712 | 34813867 | 22.2 |
Ecuador | 3690 | 17643060 | 20.9 |
Kuwait | 883 | 4270563 | 20.7 |
Peru | 6527 | 32971846 | 19.8 |
Fiji | 173 | 896444 | 19.3 |
Moldova | 739 | 4027690 | 18.3 |
Albania | 509 | 2877800 | 17.7 |
Botswana | 414 | 2351625 | 17.6 |
Cabo Verde | 97 | 555988 | 17.4 |
Bolivia | 1854 | 11673029 | 15.9 |
Dominican Republic | 1721 | 10847904 | 15.9 |
Lebanon | 1065 | 6825442 | 15.6 |
Zimbabwe | 2166 | 14862927 | 14.6 |
Laos | 985 | 7275556 | 13.5 |
Bhutan | 102 | 771612 | 13.2 |
Poland | 4996 | 37846605 | 13.2 |
Bosnia and Herzegovina | 400 | 3280815 | 12.2 |
Mexico | 14121 | 127792286 | 11.0 |
Colombia | 5466 | 50882884 | 10.7 |
Tunisia | 1077 | 11818618 | 9.1 |
Kosovo | 163 | 1810366 | 9.0 |
Cuba | 959 | 11326616 | 8.5 |
Burundi | 1005 | 11890781 | 8.5 |
Paraguay | 565 | 7132530 | 7.9 |
West Bank and Gaza | 380 | 5101416 | 7.4 |
Lesotho | 154 | 2142252 | 7.2 |
Jordan | 698 | 10203140 | 6.8 |
Papua New Guinea | 576 | 8947027 | 6.4 |
Mauritania | 290 | 4649660 | 6.2 |
China | 83049 | 1411778724 | 5.9 |
Belarus | 536 | 9449321 | 5.7 |
Zambia | 1038 | 18383956 | 5.6 |
Sao Tome and Principe | 12 | 219161 | 5.5 |
Iran | 4562 | 83992953 | 5.4 |
Honduras | 494 | 9904608 | 5.0 |
Djibouti | 44 | 988002 | 4.5 |
Kiribati | 5 | 117606 | 4.3 |
Iraq | 1647 | 40222503 | 4.1 |
Morocco | 1433 | 36910558 | 3.9 |
Oman | 167 | 5106622 | 3.3 |
Tanzania | 1482 | 59734213 | 2.5 |
India | 32379 | 1380004385 | 2.3 |
Venezuela | 628 | 28435943 | 2.2 |
Philippines | 1935 | 109581085 | 1.8 |
Afghanistan | 706 | 38928341 | 1.8 |
Guinea-Bissau | 31 | 1967998 | 1.6 |
Armenia | 43 | 2963234 | 1.5 |
Indonesia | 4079 | 273523621 | 1.5 |
Sri Lanka | 204 | 21413250 | 1.0 |
Libya | 68 | 6871287 | 1.0 |
Guinea | 112 | 13132792 | 0.9 |
Kazakhstan | 171 | 18776707 | 0.9 |
Rwanda | 116 | 12952209 | 0.9 |
Comoros | 7 | 869595 | 0.8 |
Timor-Leste | 11 | 1318442 | 0.8 |
Azerbaijan | 82 | 10139175 | 0.8 |
Congo (Kinshasa) | 610 | 89561404 | 0.7 |
Kenya | 374 | 53771300 | 0.7 |
Malawi | 124 | 19129955 | 0.6 |
Mali | 117 | 20250834 | 0.6 |
Uzbekistan | 204 | 33469199 | 0.6 |
Ethiopia | 663 | 114963583 | 0.6 |
South Sudan | 68 | 11193729 | 0.6 |
Gabon | 14 | 2225728 | 0.6 |
Eritrea | 17 | 3546427 | 0.5 |
Mozambique | 156 | 31255435 | 0.5 |
Togo | 43 | 8278737 | 0.5 |
Pakistan | 1004 | 220892331 | 0.5 |
Liberia | 21 | 5057677 | 0.4 |
Cote d'Ivoire | 96 | 26378275 | 0.4 |
Senegal | 59 | 16743930 | 0.4 |
Nepal | 128 | 29136808 | 0.4 |
Haiti | 39 | 11402533 | 0.3 |
Madagascar | 78 | 27691019 | 0.3 |
Bangladesh | 435 | 164689383 | 0.3 |
Ghana | 82 | 31072945 | 0.3 |
Burma | 171 | 54409794 | 0.3 |
Somalia | 36 | 15893219 | 0.2 |
Niger | 45 | 24206636 | 0.2 |
Sudan | 80 | 43849269 | 0.2 |
Syria | 22 | 17500657 | 0.1 |
Nigeria | 171 | 206139587 | 0.1 |
Gambia | 3 | 2416664 | 0.1 |
Algeria | 55 | 43851043 | 0.1 |
Nicaragua | 0 | 6624554 | 0.0 |
Marshall Islands | 0 | 58413 | 0.0 |
Micronesia | 0 | 113815 | 0.0 |
Angola | 0 | 32866268 | 0.0 |
Korea, North | 1 | 25778815 | 0.0 |
Ukraine | 0 | 43733759 | 0.0 |
Yemen | 0 | 29825968 | 0.0 |
Kyrgyzstan | 0 | 6524191 | 0.0 |
Uganda | 4 | 45741000 | 0.0 |
Congo (Brazzaville) | 0 | 5518092 | 0.0 |
Benin | 0 | 12123198 | 0.0 |
Holy See | 0 | 809 | 0.0 |
Sierra Leone | 0 | 7976985 | 0.0 |
Burkina Faso | 0 | 20903278 | 0.0 |
Georgia | 0 | 3989175 | 0.0 |
Tajikistan | 0 | 9537642 | 0.0 |
Cambodia | 0 | 16718971 | 0.0 |
Cameroon | 0 | 26545864 | 0.0 |
Equatorial Guinea | 0 | 1402985 | 0.0 |
Central African Republic | 0 | 4829764 | 0.0 |
Egypt | 0 | 102334403 | 0.0 |
Chad | 3 | 16425859 | 0.0 |
El Salvador | 0 | 6486201 | 0.0 |
Antarctica | 0 | 0 | NaN |
Diamond Princess | 0 | 0 | NaN |
MS Zaandam | 0 | 0 | NaN |
Summer Olympics 2020 | 0 | 0 | NaN |
Winter Olympics 2022 | 0 | 0 | NaN |
Tutorial: Detailed calculation for one country¶
In [5]:
from oscovida import fetch_cases, get_population
import datetime
In [6]:
period = 14 # Days we compute the incidence rate over
In [7]:
cases = fetch_cases() # Get a DataFrame where each row is the country, and columns cumulative case numbers
cases = cases.groupby(cases.index).sum() # Merge the rows for different regions as we want the numbers for an entire country
In [8]:
cases_germany = cases.loc['Germany'][2:] # First 2 entries are lat/lon so we only take the subsequent ones
cases_germany.tail()
Out[8]:
5/19/22 25998085.0 5/20/22 26040460.0 5/21/22 26044283.0 5/22/22 26045528.0 5/23/22 26109965.0 Name: Germany, dtype: float64
In [9]:
yesterday = datetime.datetime.now() - datetime.timedelta(days=1)
x_days_ago = yesterday - datetime.timedelta(days=period)
In [10]:
period_mask = (
(yesterday > pd.to_datetime(cases_germany.index)) &
(pd.to_datetime(cases_germany.index) > x_days_ago)
) # Mask for dates between today and x days ago
In [11]:
cases_in_period_per_day_germany = cases_germany[period_mask].diff() # Apply the period mask and get the diff to get the daily new cases
cases_in_period_per_day_germany
Out[11]:
5/10/22 NaN 5/11/22 88961.0 5/12/22 68999.0 5/13/22 61859.0 5/14/22 6151.0 5/15/22 2305.0 5/16/22 86252.0 5/17/22 72051.0 5/18/22 58719.0 5/19/22 48910.0 5/20/22 42375.0 5/21/22 3823.0 5/22/22 1245.0 5/23/22 64437.0 Name: Germany, dtype: float64
In [12]:
cases_in_period_per_day_germany.plot() # We can easily look at new cases per day
Out[12]:
<AxesSubplot:>
In [13]:
population = get_population().population
In [14]:
population_germany = population.loc['Germany'] # Get the population of Germany
population_germany
Out[14]:
83155031.0
In [15]:
incidence_rate_germany = cases_in_period_per_day_germany.sum() / population_germany * 100_000
incidence_rate_germany # By convention this is total cases over period / population * 100_000
Out[15]:
728.8638976035016
In [ ]: