Python Exercise: Get the Chinese province wise cases of confirmed, deaths and recovered cases of Novel Coronavirus
Python Project: COVID-19 Exercise-4 with Solution
Write a Python program to get the Chinese province wise cases of confirmed, deaths and recovered cases of Novel Coronavirus (COVID-19).
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')
c_data = covid_data[covid_data['Country/Region']=='China']
c_data = c_data[['Province/State', 'Confirmed', 'Deaths', 'Recovered']]
result = c_data.sort_values(by='Confirmed', ascending=False)
result = result.reset_index(drop=True)
print(result)
Sample Output:
Dataset information: <class 'pandas.core.frame.DataFrame'> Province/State Confirmed Deaths Recovered 0 Hubei 67799 3111 56003 1 Guangdong 1364 8 1307 2 Henan 1273 22 1250 3 Zhejiang 1232 1 1216 4 Hunan 1018 4 1014 5 Anhui 990 6 984 6 Jiangxi 935 1 934 7 Shandong 761 7 746 8 Jiangsu 631 0 631 9 Chongqing 576 6 570 10 Sichuan 540 3 520 11 Heilongjiang 482 13 456 12 Beijing 456 8 369 13 Shanghai 358 3 325 14 Hebei 318 6 310 15 Fujian 296 1 295 16 Guangxi 253 2 248 17 Shaanxi 246 3 236 18 Yunnan 176 2 172 19 Hainan 168 6 161 20 Hong Kong 162 4 88 21 Guizhou 147 2 144 22 Tianjin 136 3 133 23 Gansu 133 2 91 24 Shanxi 133 0 133 25 Liaoning 125 1 120 26 Jilin 93 1 92 27 Xinjiang 76 3 73 28 Inner Mongolia 75 1 73 29 Ningxia 75 0 75 30 Qinghai 18 0 18 31 Macau 12 0 10 32 Tibet 1 0 1
Python Code Editor:
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Previous: 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.
Next: Write a Python program to get the latest country wise deaths cases of Novel Coronavirus (COVID-19).
What is the difficulty level of this exercise?
Python: Tips of the Day
Groups the elements of a list based on the given function.
Example:
def tips_group_by(lst, fn): return {key : [el for el in lst if fn(el) == key] for key in map(fn, lst)} from math import floor print(tips_group_by([5.5, 4.2, 6.3], floor)) print(tips_group_by(['mango', 'apple', 'banana'], len))
Output:
{5: [5.5], 4: [4.2], 6: [6.3]} {5: ['mango', 'apple'], 6: ['banana']}
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