Data-Analysis-Covid-cases

Data Analysis project on Covid The project is a course project at Indian Institute of Technology, Dharwad which uses the various techniques of data analysis covered in the course. It consists of mainly 3 sections and is built competely over jupyter notebook using Python 3:

Introduction

This section begins with a basic introductory paragraph to the virus and provides a basic idea of the current scenario faced by the world. The plots covered in here include :

• World cases data - daily count - line graph
• World deaths data - daily count - line graph
• World different countries data - heat map
• India cases data - daily count - line graph
• India deaths data - daily count - line graph

Hypothesis :

1. Cases Across Different Countries :

   Statement : We expect the situation to be about the same in IND and USA in regard to the cases of covid

   Math : H0,H1, calculations...

   Graphical representation of the above :
   

   • IND and USA cases data - daily count - line graph, box plot
   Conclusion : -----

2. Age Groups :

   (we cover 3 groups)

   Statement : We expect the older age group to be more adversely affected due to covid in terms of cases

   Math : H0,H1, calculations... (using categorical data)

   Graphical representation of the above :
   

   • cases across age groups - pie chart
   • cases across age groups - scatter plot with monthly data
   Conclusion : -----

3. Effect on other Diseases :

   (we cover 2 diseases)

   Statement : We expect countries with higher number of cases to have higher number in obesity and other diseases. We shall use IND and <> for the same.

   Math : H0,H1, calculations... (using categorical data)

   Graphical representation of the above :
   

   • obesity cases in IND and few other countries - bar graph
   • cases in corresponding countries - line graph (to be plotted in same graph as above)
   • Disease 2 cases in IND and few other countries - bar graph
   • cases in corresponding countries - line graph (to be plotted in same graph as above)
   Conclusion : -----

4. Altitude :

   Statement : We expect to see more cases in areas with higher altitude

   Math : H0,H1, calculations... (using categorical data)

   Graphical representation of the above :
   

   • Altitude of different countries - bar graph
   • cases in corresponding countries - line graph (to be plotted in same graph as above)
   Conclusion : -----

5. Economy :

   Statement :

   Math : H0,H1, calculations... (using categorical data)

   Graphical representation of the above :
   

   Conclusion : -----

6. Lockdown effects in different countries :

   Statement : We expect to see less rise in cases in areas with prolonged lockdowns

   Math : H0,H1, calculations... (using categorical data)

   Graphical representation of the above :
   

   • per day rise in cases in 3 countries - line graph (to be plotted in same graph as above) with 2 verticle lines symbolizing lockdown period
   Conclusion : -----

Conclusions

Here we provide the conclusions of the data in one place.

Sources :

A list of all the sources used fir gathering data