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Python Project - Covid Visualization Assignment Sample

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Python Project - Covid Visualization Assignment

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Introduction - Python Project - Covid Visualization

As part of this project, as previously mentioned, we have used the Python programming language in conjunction with specific internally and externally developed packages to obtain, organise, and display a COVID-19 dataset, which has been used to create a prototype dashboard. In this dashboard we are plotting various metrics related to the COVID-19 for different countries. One can also make comparison between different countries on these various metrics related to the COVID-19 for different countries.

Dataset

The dataset has been acquired from the GitHub repositories of COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. Located at the Johns Hopkins University Center for Systems Science and Engineering, this is the data repository for the Novel Coronavirus Visual Dashboard, which was launched in 2019. (JHU CSSE). Additionally, the ESRI Living Atlas Team and the Johns Hopkins University Applied Physics Lab have provided support (JHU APL).

Implementation Process

We use Pandas to acquire the of COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University dataset from the GitHub URLs. Then we code the Pythonic GUI interface using the tkinter module. We compose different frames to hold the different plots. We provide the user with a set of buttons to generate different plots for different countries and make relevant comparisons.

Results

In combination with specific internally and externally created packages, the Python programming language was used to gather, organise, and display a COVID-19 dataset, which was then utilised to produce a prototype dashboard as part of this project, as previously described in the introduction. With the help of this dashboard, we can visualise several parameters linked to the COVID-19 for various nations. Based on these many measures connected to the COVID-19 for different nations, one may create comparisons between multiple countries. The Center for Systems Science and Engineering (CSSE) at Johns Hopkins University obtained it via the COVID-19 Data Repository GitHub repository to get the dataset.

In the Johns Hopkins University Center for Systems Science and Engineering, this data repository serves as the Novel Coronavirus Visual Dashboard repository, which was introduced in April of this year. The CSSE at Johns Hopkins University. Also contributing to this effort were the ESRI Living Atlas Team members and researchers from the Johns Hopkins University Applied Physics Lab (JHU APL). We utilise the Pandas programming language to get the COVID-19 Data Repository from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University dataset from the GitHub URLs. The Tkinter module is then used to create the Pythonic GUI interface. For each plot, we create a new frame that holds it. Users may produce various charts for different nations and make pertinent comparisons by clicking on a set of buttons.

Python Project - Covid Visualization

Dashboard (Without any plots)

Python Project - Covid Visualization

Dashboard (Belgium plots)

Python Project - Covid Visualization

Dashboard (Belgium and France plots, superimposed)

Insights

In the Federal Republic of Germany, three per cent of the population has had their first immunisation against Corona, with just 1.4 per cent having received two vaccinations against the disease. As a result, Germany is well behind the curve when compared to other countries. In Israel, for example, over 43 per cent of the population has been vaccinated at least once. In contrast, 39 per cent of the people in Seychelles and nearly 20 per cent of the people in the United Kingdom have been vaccinated at least once. The United Arab Emirates, which is part of the UNITED STATES, Bahrain, and Serbia are examples. Several EU member nations, including Denmark, Malta, Romania, Lithuania, Ireland, Spain, and Poland, have vaccinated more individuals than the Federal Republic of Germany in ratio to their population. These countries include Denmark, Malta, Romania, Lithuania, Ireland, Spain, and Poland. Since the onset of the pandemic, Denmark, which has a population of one million people, has conducted around 2.5 million HIV tests. Luxembourg and the United Arab Emirates share comparable values.

There are about 1.2 million tests performed in the United Kingdom, and more than 990,000 tests are performed in the United States. With its nearly 497,000 tests per million population, Germany does not come close to these figures and hence does not rank among the top 30 countries that test the most often. Comparing Germany's 768 deaths per million inhabitants to countries such as Belgium, the United Kingdom, Slovenia, or the Czech Republic, where between 1600 and 1900 people have died from or with Corona for every million inhabitants, Germany is still in a relatively good position in terms of Corona mortality. In this case, the comparison with South Africa is fascinating because, despite having a significantly worse health system and, according to virologists, a much more dangerous "South Africa mutation," the country has only slightly more corona deaths to complain about – approximately 799 per million inhabitants. Occasionally, the University of Oxford has developed a lockdown index that attempts to assess the severity of particular measures ranging from school closures to contact blockades to the shutdown of stores and other commercial establishments. Germany has just climbed into the top 10 of the world's harshest nations, having previously ranked ninth. It is ahead of Cuba, Eritrea, and Honduras, with the Netherlands in second place.

Taiwan, Nicaragua, Macau, and New Zealand are now the countries with the fewest restrictions. According to the Chinese government's statistics, the Chinese economy grew by 2.3 per cent in the pandemic year 2020, making it the only major economy. According to economic predictions, the Chinese economy is expected to grow by between seven and eight per cent this year. Following a five per cent decline in the previous year, most analysts anticipate that the German economy will rebound in the current year. However, given that the lockdown has been prolonged again, this is likely to be less severe than first anticipated. The German government has already reduced its growth prediction by a substantial amount, from 4.4 per cent to three per cent.

According to the Organization for Economic Cooperation and Development's estimations, German economic production in the first week of February was still eight per cent lower than the same period the previous year. In contrast, bankers and economists predict that the United States will grow by four to five per cent this year and that the United Kingdom will grow by an even more significant percentage in certain circumstances. Figures on infection, fatalities, and testing rates are also available. The Australian Lowy Institute, a think tank established in 2003, has combined several such indicators into a comprehensive picture and developed an index for the best crisis management during the recent Corona disaster. Germany is just in the middle of the pack, ranking 55th out of almost 100 nations — just below Croatia and ahead of El Salvador – among the nearly 100 countries studied. Iran, Colombia, Mexico, and Brazil had the poorest performances, while New Zealand, Vietnam, Taiwan, and Thailand had the best.

References

Douglas, K. (2020). Python Programming Cookbook for Absolute Beginners: A Complete Crash Course and Tutorial for Everyone Including Dummies. Amazon Digital Services LLC - KDP Print US.

Kong, Q., Siauw, T. and Bayen, A. (2020). Python Programming and Numerical Methods: A Guide for Engineers and Scientists. Elsevier Science.

Matthes, E. (2019). Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to Programming. No Starch Press.

Miller, B.N., Ranum, D.L. and Anderson, J. (2019). Python Programming in Context. Jones & Bartlett Learning.

Panthy, K. (2019). Python Programming Hero: Leverage Your Time Learning Python. Independently Published.

Thareja, R. (2019). Python Programming: Using Problem Solving Approach. Oxford University Press.

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