Covid-19-Analysis

PROJECT NAME :- Covid-19-analysis

Table Overview :

• Reason to choose these project
• Pandas Methods which are used in these project
• Graph which are used
• Workdone
• Conclusion
• Result

1. Reason to Choose these Project-: when evaluating covid-19 data easy to decision-making govrnment as well as private sector. Use to number of cases active,number of cases discharge , number of cases deaths also rate.

2. • info(),desribe(),isna(),sum() -drop() -value_counts(),groupby()

3. Graph which are used-: ->For plotting i have used matplotlib.pyplot and seaborn Bar graph Pie chart Countplot Heat map

4. Workdone-: - By using isna().sum() find out missing values. - By using describe give descriptive statistic. - By using info() give information. - I used masking technique,groupby,unique method,countplot.

5. Conclusion- This data has represented a study of covid-19 disease affect on India. -> The spread of covid-19 in India almost all state and union territory. -> From above analysis i have concluded highest total number of covid19 cases in Maharastra state where as lowest number of covid19 cases in Andaman and Nicobar. -> Kerala state is a high active cases where as Dadra and Nagar Haveli and Daman and Diu territoryis low active cases in India. -> Highest number of death in state of Maharastra and lowest number of death in Dadra and Nagar Haveli and Daman and Diu. -> Utter pradesh state is a highest population state in India

6. Result- After my analysis if any state or territory total number of cases increases number of death is increses -> Number of total cases is directly proportional to the deaths. -> Number of cases decreses deaths and deaths ratio aslo decreses.