Data Science Portfolio

These charts are taken from Rapid Charts and they show the UK's Covid-19 cases by regions, the UK's productivity over time and the aging population of various countries.

The data for these charts were obtained from the UK Government, one from an API and one as a CSV download saved to my GitHub.

For the sixth chart, I manually encoded data points into JSON code. For the seventh chart, I created a GDP per capita chart using data on China’s GDP and population and manipulating the data in Excel.

For the eighth chart I used an API about carbon emissions and for the ninth chart I used the World Bank API to look at the poverty gap in Malaysia.

These four charts were constructed using a loop in Python to batch download the data from FRED. These JSON files were then uploaded to GitHub. The loop used can be found here.

This chart was created using pandas to scrape Wikipedia to gather data on the Social Mobility index for G7 countries. The scraper can be found here.

In the 'Working from home or not working at all' talk at Talking Economics, Helen Simpson (UoB) stated that women are more likely to choose jobs with shorter commutes than men in order to fit their job around child-care and domestic responsibilities. The chart below uses data from ONS to look at the impact of commute time on the probability of leaving a current job. The chart supports Simpson’s claim, comparing to a group with a 10 minute commute, women always have a higher probability of leaving their current job compared to men. The probability difference only widens as the commute time increases.

I regressed social mobility against life expectancy and found that there was a positive correlation with an R² of 0.37. Python code can be found here.

Chart seventeen shows the relationship between GDP per capita and life expectancy in Europe. Hover over the dots to see that specific country data. Chart eighteen is an interactive chart looking at the working age population in various countries.