I performed Data Analysis on COVID 19 dataset by John Hopkins University and World Happiness Report and found really interesting results. It shows that people living in developed countries are more prone to infection of the Corona Virus than people living in less developed countries.
I performed Data Analysis on COVID 19 dataset by John Hopkins University and World Happiness Report and found really interesting results. It shows that people living in developed countries are more prone to infection of the Corona Virus than people living in less developed countries.
Calculating Correleation Matrix for the final Data
final_data.corr()
max_infection_rates
GDP per capita
Social support
Healthy life expectancy
Freedom to make life choices
max_infection_rates
1.000000
0.207071
0.158977
0.218118
0.071825
GDP per capita
0.207071
1.000000
0.757521
0.859431
0.394799
Social support
0.158977
0.757521
1.000000
0.751632
0.456317
Healthy life expectancy
0.218118
0.859431
0.751632
1.000000
0.423146
Freedom to make life choices
0.071825
0.394799
0.456317
0.423146
1.000000
Visualizing our final result
Plotting GDP vs Maximum Infection Rate
x=final_data["GDP per capita"]
y=final_data["max_infection_rates"]
sns.regplot(x,np.log(y)).set_title("Relationship Between Corona Infection Rate and GDP per Capita")
Text(0.5, 1.0, 'Relationship Between Corona Infection Rate and GDP per Capita')
Plotting Social support vs Maximum Infection Rate
x=final_data["Social support"]
y=final_data["max_infection_rates"]
sns.regplot(x,np.log(y)).set_title("Relationship Between Corona Infection Rate and Social Support")
Text(0.5, 1.0, 'Relationship Between Corona Infection Rate and Social Support')
Plotting Social support vs Health Life Expectancy
x=final_data["Healthy life expectancy"]
y=final_data["max_infection_rates"]
sns.regplot(x,np.log(y)).set_title("Relationship Between Corona Infection Rate and Health Life Expectancy")
Text(0.5, 1.0, 'Relationship Between Corona Infection Rate and Health Life Expectancy')
Plotting Social support vs Freedom to make life choices
x=final_data["Freedom to make life choices"]
y=final_data["max_infection_rates"]
sns.regplot(x,np.log(y)).set_title("Relationship Between Corona Infection Rate and Freedom to make life choices")
Text(0.5, 1.0, 'Relationship Between Corona Infection Rate and Freedom to make life choices')
I performed Data Analysis on COVID 19 dataset by John Hopkins University and World Happiness Report and found really interesting results. It shows that people living in developed countries are more prone to infection of the Corona Virus than people living in less developed countries.