This case study is the capstone project of my Google Data Analytics Professional Certificate course. The course offered two sample datasets and scenarios to pick from, but I thought some originality would be excellent, plus the additional challenges would motivate me throughout the project. Eventually, I have decided to base my case study on the electric vehicle market and trends.
The project included six steps of the data analysis process: ask, prepare, process, analyse, share, and act. Below is a short preview of the case study, techniques/tools used and data visualizations.
Access the R notebook file Here
Alternatively, Github repo could be found here: Github.
My client is an industry-leading energy infrastructure provider based in Europe. Following Europe’s energy crisis (Popkostova, 2022), they are securing more funding from investors and investing in energy projects in Europe to meet the ever-growing electricity demand. Their renewable energy project team is eager to discover insights from the EV market. They would like to know if the EV market is impacting the electricity demand in Europe and by what magnitude, so that data-driven decisions could be made based on conclusions drawn from this data analysis project. Once we produce actionable recommendations, they could conduct a feasibility study based on our conclusion and advise their board and stakeholders.
The datasets used are sourced from IEA (International Energy Agency), a Paris-based autonomous intergovernmental organisation that serves as a policy adviser on energy issues for 30 member countries. The datasets contain records of EV sales, publicly available EV chargers and EV electricity demand sorted by countries and regions between 2010-2020 (Global EV Data Explorer – Analysis - IEA, 2022). Considering that the EV market is still in its infancy, as the first mass-produced EV was only released in 1997 (The History of the Electric Car, 2022), we can assume that the dataset used would be relevant and up to date to reflect recent market trends.
This project will not include the original dataset as a downloadable file as to adhere to IEA's terms and conditions, which states anything greater than 5 (five) numerical data points (but still an Insubstantial Amount) from the Material must not be made available in a separate downloadable format and must be presented either in graphical format or aggregated (in such a manner that the reader cannot reverse engineer or extract the original underlying numerical data). This also means that the analysis process will only include the summary or head of a dataset, where appropriate.
Data cleaning, pre-processing and validating in R
Univariate analysis
Simple linear regression and multiple regression analysis
Time-series analysis
ARIMA modelling
Visualization with R libraries: ggplot2 and plotly
Visualization with Tableau
IEA. 2022. Global EV Data Explorer – Analysis - IEA. [online] Available at:
Energy.gov. 2022. The History of the Electric Car. [online] Available at:
Popkostova, Y., 2022. EUROPE’S ENERGY CRISIS CONUNDRUM. [online] Iss.europa.eu. Available at: