Covid Healthcare Country Analysis

Goal: Make conclusions on how different factors such as GDP, unemployment rate, and political instability scores affect covid death ratios in different countries.

Method: Use Python and pandas data frame to make graphs to showcase data for different countries using bar graphs, scatterplot, and etc. with the help of ChatGTP. I was able to get GDP, unemployment rate, and political instability score using ChatGTP prompting.

Analysis: While exploring the data, I realized that many high death ratio countries had higher unemployment rate than the low death ratio countries. I plotted GDP against countries using bar charts for clearer categorical data representation. I further explored the correlation between GDP and unemployment ratios, using a pandas data frame in Python. The resulting scatter plot depicted high death ratio countries as blue circles and low death ratio countries as red crosses. Another scatter plot showed the relationship betweenGDP and Political Instability Score, using the same color coding.

Conclusion: High political instability score countries were mostly high death ratio countries with low GDP as shown in the Figure 1.The unemployment ratio did not show significant correlation with COVID death ratios as shown in Figure 2. While high death ratio countries tended to have higher unemployment rates, outliers disrupted the pattern. Conversely, data accessed via ChatGPT revealed a clear relationship between political instability score and COVID death ratios.. To enhance clarity, I created a bar chart displaying countries against their political instability scores and added a legend distinguishing low death from high death countries.