In this project, we implement K-Means with Python. We use this algorithm to analyse and evaluate the correlations between energy efficiency, energy productivity, energy consumption and economic growth.
In order to conduct this research, we have used data provided by Eurostat, which is the statistical office that collects data for the European Union. The analyzed data includes all EU-27 member states:Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Ireland, Greece, Spain, France,Croatia, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, Netherlands, Austria, Poland,Portugal, Romania, Slovenia, Slovakia, Finland and Sweden. We must mention that our project employs a more varied approach, taking into account different type of countries (developed and underdeveloped), the observed period being from 2011 to 2021. This aspect leads to a large variety of values for the considered variables. The macroeconomic indicators analyzed in this project are:
- PEC (Primary energy consumption)
- FEC (Final energy consumption)
- Gross domestic product per capita (GDP per capita)
- IR (Inflation rate)
- EM (Employment)
- EE (Energy efficiency)
- EP (Energy productivity)
We will perform a clustering analysis on the countries considered, taking into account different macroeconomic parameters.