To demonstrate the state-wise Covid19 cases in india. In this project I have fetch the live data from Ministry of Health Affairs Official Website using BeautifulSoup and requests. I have done the analysis of Covid19 cases across the states of India. When we look at the figures of cases of states we might make wrong assumptions based on highest and lowest figure but the actual scenario is different. The dataset is taken till 13 June 2:35 PM. I have added Population of each state and then calculated some required rates to analyse. Then I have plotted a bar graph to visualise data for conclusion.

Take Aways From This Project :

1. Scrapping data from website using BeautifulSoup and requests.
2. Making dataframe, calculations on columns, addinng columns, changing data type of columns using pandas
3. Plotting bar graphs and pie chart using matplotlib

Conclusion :

1. In spite of Maharashtra having most number of confirmed cases, it have comparatively less death rate and high cure rate.
2. In spite of Gujarat having comparatively less number of confirmed cases, it have highest infection fatality rate.
3. In spite of Delhi having comparatively less number of confirmed cases, it have highest death rate due to covid19 and highest active cases per lakh population.
4. In spite of Mizoram and Sikkim having comparatively less number of confirmed cases, it have least cure rate.
5. North-east states of India have comparatively less active cases.
6. Large states have the most number of active cases and small states have the least number of active cases. There are some exceptions.
7. The states Gujarat, Delhi, Maharashtra needs to be more careful.
8. The states Mizoram and Sikkim needs to focus on its cure rate.
9. 51.8% of Cases in India are now cured but still 45.3% active cases are there. From the conclusions, covid19 cases has many variations in India.