The first case of the 2019-2020 Coronavirus pandemic in India was reported on January 30, 2020, originating in China. Experts suggest the number of infections could be much higher as India’s testing rates are among the lowest in the world. The infection rate of COVID-19 in India is 1.7, significantly lower than in the worst affected countries.
The World Health Organisation chief executive director of health emergencies program Michael Ryan said that India has “tremendous capacity” to deal with the coronavirus outbreak, and as the second most populous country, will have enormous impact on the world’s ability to deal with it.
Other commentators worried about the economic devastation caused by the lockdown that has huge effects on informal workers, micro and small enterprises and farmers and self employed people who are left without a livelihood in the absence of transportation and access to markets.
The lockdown was justified by the government and other agencies for being pre-emptive to prevent India from entering a higher stage which could make handling very difficult and cause even more losses thereafter. According to a study by Shiv Nadar University, India could have witnesses a surge of 31,000 cases between March 24 and April 14 without lockdown.
So we call a Jupyter Notebook in Python to study India’s COVID-19 story.
The data and code sheet used in this study can be found below.
We will first import all libraries like pandas and numpy. All the data has been taken from kaggle. We then take the data and work a dataframe on it. And then we generate an India map to study the spread of SARS-CoV-2.
Fig. 1.
For more on this, please watch the complete video attached herewith. This study was brought to you by DexLab Analytics. DexLab Analytics is a premiere Artificial Intelligence training institute in Gurgaon.
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