Python Exercise: Get the latest number of confirmed, deaths, recovered and active cases of Novel Coronavirus Country wise
Python Project: COVID-19 Exercise-2 with Solution
Write a Python program to get the latest number of confirmed, deaths, recovered and active cases of Novel Coronavirus (COVID-19) Country wise.
Sample Solution:
Python Code:
import pandas as pd
covid_data= pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/03-17-2020.csv')
covid_data['Active'] = covid_data['Confirmed'] - covid_data['Deaths'] - covid_data['Recovered']
result = covid_data.groupby('Country/Region')['Confirmed', 'Deaths', 'Recovered', 'Active'].sum().reset_index()
print(result)
Sample Output:
Country/Region Confirmed Deaths Recovered Active 0 Afghanistan 22 0 1 21 1 Albania 55 1 0 54 2 Algeria 60 4 12 44 3 Andorra 39 0 1 38 4 Antigua and Barbuda 1 0 0 1 5 Argentina 68 2 3 63 6 Armenia 78 0 1 77 7 Aruba 3 0 0 3 8 Australia 452 5 23 424 9 Austria 1332 3 1 1328 10 Azerbaijan 28 1 6 21 11 Bahrain 228 1 81 146 12 Bangladesh 10 0 3 7 13 Barbados 2 0 0 2 14 Belarus 36 0 3 33 15 Belgium 1243 10 1 1232 16 Benin 1 0 0 1 17 Bhutan 1 0 0 1 18 Bolivia 11 0 0 11 19 Bosnia and Herzegovina 26 0 2 24 20 Brazil 321 1 2 318 21 Brunei 56 0 0 56 22 Bulgaria 67 2 0 65 23 Burkina Faso 15 0 0 15 24 Cambodia 33 0 1 32 25 Cameroon 10 0 0 10 26 Canada 478 5 9 464 27 Central African Republic 1 0 0 1 28 Chile 201 0 0 201 29 China 81058 3230 68798 9030 30 Colombia 65 0 1 64 31 Congo (Brazzaville) 1 0 0 1 32 Congo (Kinshasa) 3 0 0 3 33 Costa Rica 41 0 0 41 34 Cote d'Ivoire 5 0 1 4 35 Croatia 65 0 4 61 36 Cruise Ship 696 7 325 364 37 Cuba 5 0 0 5 38 Cyprus 46 0 0 46 39 Czechia 396 0 3 393 40 Denmark 1024 4 1 1019 41 Dominican Republic 21 1 0 20 42 Ecuador 58 2 0 56 43 Egypt 196 4 32 160 44 Equatorial Guinea 1 0 0 1 45 Estonia 225 0 1 224 46 Eswatini 1 0 0 1 47 Ethiopia 5 0 0 5 48 Finland 321 0 10 311 49 France 7683 148 12 7523 50 French Guiana 11 0 0 11 51 Gabon 1 0 0 1 52 Georgia 34 0 1 33 53 Germany 9257 24 67 9166 54 Ghana 7 0 0 7 55 Greece 387 5 8 374 56 Greenland 1 0 0 1 57 Guadeloupe 18 0 0 18 58 Guam 3 0 0 3 59 Guatemala 6 1 0 5 60 Guernsey 0 0 0 0 61 Guinea 1 0 0 1 62 Guyana 7 1 0 6 63 Holy See 1 0 0 1 64 Honduras 8 0 0 8 65 Hungary 50 1 2 47 66 Iceland 220 1 0 219 67 India 142 3 14 125 68 Indonesia 172 5 8 159 69 Iran 16169 988 5389 9792 70 Iraq 154 11 32 111 71 Ireland 223 2 5 216 72 Israel 337 0 11 326 73 Italy 31506 2503 2941 26062 74 Jamaica 12 0 2 10 75 Japan 878 29 144 705 76 Jersey 0 0 0 0 77 Jordan 34 0 1 33 78 Kazakhstan 33 0 0 33 79 Kenya 3 0 0 3 80 Korea, South 8320 81 1407 6832 81 Kosovo 2 0 0 2 82 Kuwait 130 0 9 121 83 Latvia 49 0 1 48 84 Lebanon 120 3 3 114 85 Liberia 1 0 0 1 86 Liechtenstein 7 0 0 7 87 Lithuania 25 0 1 24 88 Luxembourg 140 1 0 139 89 Malaysia 673 2 49 622 90 Maldives 13 0 0 13 91 Malta 38 0 2 36 92 Martinique 16 1 0 15 93 Mauritania 1 0 0 1 94 Mayotte 1 0 0 1 95 Mexico 82 0 4 78 96 Moldova 30 0 1 29 97 Monaco 7 0 0 7 98 Mongolia 5 0 0 5 99 Montenegro 2 0 0 2 100 Morocco 38 2 1 35 101 Namibia 2 0 0 2 102 Nepal 1 0 1 0 103 Netherlands 1708 43 2 1663 104 New Zealand 12 0 0 12 105 Nigeria 3 0 0 3 106 North Macedonia 26 0 1 25 107 Norway 1463 3 1 1459 108 Oman 24 0 9 15 109 Pakistan 236 0 2 234 110 Panama 69 1 0 68 111 Paraguay 9 0 0 9 112 Peru 117 0 1 116 113 Philippines 187 12 5 170 114 Poland 238 5 13 220 115 Portugal 448 1 3 444 116 Puerto Rico 0 0 0 0 117 Qatar 439 0 4 435 118 Republic of the Congo 0 0 0 0 119 Reunion 9 0 0 9 120 Romania 184 0 16 168 121 Russia 114 0 8 106 122 Rwanda 7 0 0 7 123 Saint Lucia 2 0 0 2 124 Saint Vincent and the Grenadines 1 0 0 1 125 San Marino 109 7 4 98 126 Saudi Arabia 171 0 6 165 127 Senegal 26 0 2 24 128 Serbia 65 0 1 64 129 Seychelles 4 0 0 4 130 Singapore 266 0 114 152 131 Slovakia 72 0 0 72 132 Slovenia 275 1 0 274 133 Somalia 1 0 0 1 134 South Africa 62 0 0 62 135 Spain 11748 533 1028 10187 136 Sri Lanka 44 0 1 43 137 Sudan 1 1 0 0 138 Suriname 1 0 0 1 139 Sweden 1190 7 1 1182 140 Switzerland 2700 27 4 2669 141 Taiwan* 77 1 22 54 142 Tanzania 1 0 0 1 143 Thailand 177 1 41 135 144 The Bahamas 1 0 0 1 145 The Gambia 1 0 0 1 146 Togo 1 0 0 1 147 Trinidad and Tobago 5 0 0 5 148 Tunisia 24 0 0 24 149 Turkey 47 1 0 46 150 US 6421 108 17 6296 151 Ukraine 14 2 0 12 152 United Arab Emirates 98 0 23 75 153 United Kingdom 1960 56 53 1851 154 Uruguay 29 0 0 29 155 Uzbekistan 10 0 0 10 156 Venezuela 33 0 0 33 157 Vietnam 66 0 16 50 158 occupied Palestinian territory 0 0 0 0
Python Code Editor:
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Previous: Write a Python program to display first 5 rows from COVID-19 dataset.
Next: Write a Python program to get the latest number of confirmed deaths and recovered people of Novel Coronavirus (COVID-19) cases Country/Region - Province/State wise.
What is the difficulty level of this exercise?
Python: Tips of the Day
Returns True if all the values in a list are unique, False otherwise.
Example:
def tips_allunique(lst): return len(lst) == len(set(lst)) x = [1, 2, 3, 4, 5, 6, 7] y = [1, 2, 3, 3, 4, 5, 6] print(tips_allunique(x)) print(tips_allunique(y))
Output:
True False
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