Introduction
Electricity is an essential aspect of our daily lives, and power plants play a crucial role in providing energy to homes and industries. On the fourth day of dashboard week we were given the challenge to work with the Global Power Plant data.
Data Preparation
After getting my hands on the dataset, I had to do some cleaning and transposing to make it more manageable. Then, I added some country-specific data, including world regions, population, GDP, and demographic data, to see if we could uncover some interesting correlations.
The primary fuels were grouped into three categories – renewable, fossil fuel, and nuclear – to analyze their distribution across different countries.
Visualisation
My first visualization was a stacked bar chart showing the number of power plants per region, with the color indicating the primary fuel category. The chart shows the distribution of power plants across different regions of the world.
I also created a butterfly chart to compare the population and capacity of different countries. In most cases countries with higher populations tend to have a higher power plant capacity but not always.
I created a scatter plot to visualize the correlation between GDP and power plant capacity. It was no surprise that countries with higher GDP tend to have a higher power plant capacity. However there were some outliers too.
And finally, I used a map to visualize the distribution of power plants across different countries. And because I was feeling a little adventurous, I added a parameter to switch the map to a bar chart, allowing us to see the distribution of power plants according to their primary fuel.
Conclusion
In conclusion, my exploration of the global power plants dataset was an enlightening experience. By adding country-specific data and using various visualizations, I uncovered some interesting correlations between power plants and population, GDP, and primary fuel sources. Who knew that data could be so much fun?!