Python Exercise: Latest number of confirmed deaths and recovered people of Novel Coronavirus cases Country wise
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.
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/03-16-2020.csv')
data = covid_data.groupby(['Country/Region', 'Province/State'])['Confirmed', 'Deaths', 'Recovered'].max()
pd.set_option('display.max_rows', None)
print(data)
Sample Output:
Dataset information:
<class 'pandas.core.frame.DataFrame'>
Confirmed Deaths Recovered
Country/Region Province/State
Australia Australian Capital Territory 2 0 0
From Diamond Princess 0 0 0
New South Wales 210 4 4
Northern Territory 1 0 0
Queensland 78 0 8
South Australia 29 0 3
Tasmania 7 0 0
Victoria 94 0 8
Western Australia 31 1 0
Canada Alberta 74 0 0
British Columbia 103 4 4
Grand Princess 8 0 0
Manitoba 8 0 0
New Brunswick 8 0 0
Newfoundland and Labrador 3 0 0
Nova Scotia 7 0 0
Ontario 185 1 5
Prince Edward Island 1 0 0
Quebec 74 0 0
Saskatchewan 7 0 0
China Anhui 990 6 984
Beijing 456 8 369
Chongqing 576 6 570
Fujian 296 1 295
Gansu 133 2 91
Guangdong 1364 8 1307
Guangxi 253 2 248
Guizhou 147 2 144
Hainan 168 6 161
Hebei 318 6 310
Heilongjiang 482 13 456
Henan 1273 22 1250
Hong Kong 162 4 88
Hubei 67799 3111 56003
Hunan 1018 4 1014
Inner Mongolia 75 1 73
Jiangsu 631 0 631
Jiangxi 935 1 934
Jilin 93 1 92
Liaoning 125 1 120
Macau 12 0 10
Ningxia 75 0 75
Qinghai 18 0 18
Shaanxi 246 3 236
Shandong 761 7 746
Shanghai 358 3 325
Shanxi 133 0 133
Sichuan 540 3 520
Tianjin 136 3 133
Tibet 1 0 1
Xinjiang 76 3 73
Yunnan 176 2 172
Zhejiang 1232 1 1216
Cruise Ship Diamond Princess 696 7 325
Denmark Denmark 977 4 1
Faroe Islands 47 0 0
France France 7652 148 12
French Guiana 7 0 0
French Polynesia 3 0 0
Guadeloupe 6 0 0
Mayotte 1 0 0
Reunion 9 0 0
Saint Barthelemy 3 0 0
St Martin 2 0 0
Netherlands Curacao 3 0 0
Netherlands 1705 43 2
US Alabama 39 0 0
Alaska 3 0 0
Arizona 20 0 1
Arkansas 22 0 0
California 698 12 6
Colorado 160 2 0
Connecticut 68 0 0
Delaware 16 0 0
Diamond Princess 47 0 0
District of Columbia 22 0 0
Florida 216 6 0
Georgia 146 1 0
Grand Princess 21 0 0
Guam 3 0 0
Hawaii 10 0 0
Idaho 8 0 0
Illinois 161 1 2
Indiana 30 2 0
Iowa 23 0 0
Kansas 18 1 0
Kentucky 26 1 1
Louisiana 196 4 0
Maine 32 0 0
Maryland 60 0 3
Massachusetts 218 0 1
Michigan 65 0 0
Minnesota 60 0 0
Mississippi 21 0 0
Missouri 11 0 0
Montana 9 0 0
Nebraska 21 0 0
Nevada 56 1 0
New Hampshire 26 0 0
New Jersey 267 3 1
New Mexico 23 0 0
New York 1706 13 0
North Carolina 64 0 0
North Dakota 3 0 0
Ohio 67 0 0
Oklahoma 19 0 0
Oregon 66 1 0
Pennsylvania 112 0 0
Puerto Rico 5 0 0
Rhode Island 23 0 0
South Carolina 47 1 0
South Dakota 11 1 0
Tennessee 74 0 0
Texas 110 1 0
Utah 51 0 0
Vermont 12 0 0
Virgin Islands 2 0 0
Virginia 67 2 0
Washington 1076 55 1
West Virginia 1 0 0
Wisconsin 72 0 1
Wyoming 11 0 0
United Kingdom Cayman Islands 1 1 0
Channel Islands 6 0 0
Gibraltar 3 0 1
United Kingdom 1950 55 52
Python Code Editor:
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