We put great importance to data protection and therefore use the data you provide to us with upmost care. You can handle the data you provide to us in your personal dashboard. You will find our complete regulations on data protection and clarification of your rights in our privacy notice. By using the website and its offers and navigating further, you accept the regulations of our privacy notice and terms and conditions.
Use Case
Industry, Innovation And Infrastructure
Sustainable Cities And Communities
Dundee has the second largest fleet of electric vehicles (EV) in the UK and this is rapidly expanding, as is the number of EV charging points available to the public driving within and through the city.
As EV technology is more widely adopted, we need more insight into how users charge their vehicles and consume energy. This was identified as an area where data analysis could provide insight critical to ensuring the service is fit for purpose, efficient, and fully meets the needs of electric vehicle users.
Dundee recognises that Open Data is an important resource for data analysts and policy makers and should be fully utilised as a tool in service design.
DCC sought to gain a better insight into how EV charge points are being used and to identify any patterns in their usage - i.e. busiest charge points, busiest times of day/days of the week, are any charge points underutilized? Data analysis identified the following:
We analysed electric vehicle charge point energy consumption, published quarterly in CSV format. The analysis was carried out in Jupyter Notebooks using Pandas – a python data analysis library. The data was accessed via the CKAN datastore API.
Want to learn more about the lessons learned, financial details and results?
Log inPlanning time: 6 months to 1 year
Implementation time: 6 months to 1 year
Dundee City Council (DCC)
Dundee City Council (DCC)
Dundee City Council (DCC)