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Python设计程序讲解、辅导program留学生编程、Python语言程序讲解 解析Haskell程序|讲解留学生Processing
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Project
Section A
Description
The world is now in a battle against Covid-19 (coronavirus), a disease caused by a previously unknown coronavirus that has spread to over 200 countries and regions. Every day, thousands of people have been infected and many of them have died due to Covid-19. Countries are working hard and have come out with various strategies to stop the spread of this virus including total home lock down, tracing the clusters of infected people and quarantine them for 2 weeks and so on. The World Health Organization (WHO) has created numerous action plans including vaccine development, and analyzing the current dataset provided by each country on Covid-19 in order to curb the spread of this virus. Therefore, real-time analyses of epidemiological data are needed to increase situational awareness and informed interventions. In this project, data on Covid-19 have been provided to analyse the questions given in Section B.
Data Source:
The data file attached with this document is named as 12-19-2020.csv
Field description
FIPS: US only. Federal Information Processing Standards code that uniquely identifies counties within the USA.
Admin2: County name. US only.
Province_State: Province, state or dependency name.
Country_Region: Country, region or sovereignty name. The names of locations included on the Website correspond with the official designations used by the U.S. Department of State.
Last Update: MM/DD/YYYY HH:mm:ss (24 hour format, in UTC).
Lat and Long_: Dot locations on the dashboard. All points (except for Australia) shown on the map are based on geographic centroids, and are not representative of a specific address, building or any location at a spatial scale finer than a province/state. Australian dots are located at the centroid of the largest city in each state.
Confirmed: Counts include confirmed and probable (where reported).
Deaths: Counts include confirmed and probable (where reported).
Recovered: Recovered cases are estimates based on local media reports, and state and local reporting when available, and therefore may be substantially lower than the true number. US state- level recovered cases are from COVID Tracking Project.
Active: Active cases = total cases - total recovered - total deaths.
Incident_Rate: Incidence Rate = cases per 100,000 persons.
Case_Fatality_Ratio (%): Case-Fatality Ratio (%) = Number recorded deaths / Number cases.
All cases, deaths, and recoveries reported are based on the date of initial report.
Section B
1.Write a Python program to get the latest number of confirmed, deaths, recovered and active cases of COVID-19 country-wise. [10 marks]
Sample Output:
2.Get the US province-wise cases of confirmed, deaths and recovered cases of COVID-19.
[10 marks]
Sample Output
3.Write a Python program to get the top 10 countries with highest number of confirmed COVID-19 cases.[10 marks]
Sample Output
4.Visualize the state/province-wise combined number of confirmed, deaths, recovered, active COVID-19 cases in Germany. [15 marks]
Sample Output
5.Write a Python program to create a plot (lines) of total deaths, confirmed, recovered and active cases, countrywise, where the number of deaths are greater than 100,000. [15 marks]
Sample Output
6.Write a Python program to list the countries which have the percentage of deaths to be more than 10% of confirmed cases. [10 marks]
Sample Output
7.Write a Python program to list countries which have no of percentage recovered is 80% out of confirmed case. [10 marks]
Sample Output
8.Visualize the confirmed cases based on the region as shown in the Figure below. [20 marks]
Students can define the region based on the link given below: https://meta.wikimedia.org/wiki/List_of_countries_by_regional_classification
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