Pandemic has been spread all over the world for the last few years. It has become very important to understand about this spread. Corona Virus is a family of viruses that causes many types of diseases which can be from common cold and cough to something very severe disease. As the Middle East Respiratory Syndrome and Severe Acute Respiratory Syndrome are some severe cases that the world has already faced.
Coronavirus was first discovered in 2019. It is a contiguous virus that started from Wuhan in December 2019, which was later declared a Pandemic by WHO due to its high spreading rate.
This case study is an effort to do an analysis of the cumulative data of confirmed, deaths, recovered cases and active cases over time.
You can collect the data from the link given below:
- For Confirmed Cases: time_series_covid19_confirmed_global.csv
- For Recovered Cases: time_series_covid19_recoverd_global.csv
- For Death Cases: time_series_covid19_deaths_global.csv
This is the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) which get updated on daily basis.
For Practising all these codes you can use Google Colaboratory which is a Google cloud-based service that is similar to Jupyter Notebook in the cloud. It is a free version of the Jupyter Notebook which is built on the cloud. You don't need to download or install this.
You should have the basic knowledge of Python and also the understanding of the importance of analysis. Basic knowledge of Google Colaboratory is also required. You can refer to Google Colaboratory for gaining some prior knowledge if required.
Some Basic Instructions
- Firstly you should understand the data. Read the data properly and try to gain some knowledge about it and what it is trying to represent.
- Secondly, it will be better if you check the data after each step to see if the applied command has been applied in the same way as you want it to be.