State of the EV: An Early Case Study
Electric Vehicles have always been a source of endless fascination to me. I love this technology. Every time I see one on the road, I couldn’t help but feel excited for the future. I love it so much that I’ve decided scratch this itch by building a Python application on the subject.
Admittedly, as infatuated as I am with EVs, I really don’t know much about it, ironically enough. To top it off, I am not a “car person”. I don’t even drive, which, of course, made the initial research a bit more complicated.
Nevertheless, I persisted. Introducing a working proof of concept of… State of the EV, a web-based dashboard that allows you to compare a variety of commercially available models of Electric Vehicles (UK/USA) through price, drive/power and battery technology! Proudly built with Figma, Jupyter Notebook, Python and Streamlit.
Practicality, at the heart and center of it all.
What would users care most about with a dashboard like this one? Specifically for Electric Vehicles, price would be a top priority. Most people would be interested in seeing, comparing and analyzing EVs with a budget in mind. It is no surprise that articles like this are gaining a lot of attention even with casual readers.
What can I afford? What will make more sense with my budget? What is a good value-for-money especially for this emerging (is it still?) technology?
Product thinking, a marriage of design and data.
The design process was quite simple: what is the problem I am trying to solve… and can I support this with actual data? The end product was clear from the very beginning. I needed a way to tell a story about Electric Vehicles in a way that matters to an imagined end user.
What can the user gain from this? How can this potentially influence their current and future buying behaviors? How can this empower their choices? What kinds of data should I use in order to make this happen?
It started with an idea: “What do I want to achieve with data?” then followed shortly by actual dataset research, an area wherein I realized very quickly that I don’t really know as much about but that’s ok because it only helped me out for the last milestone: execution.
For more of the lessons learned, please read my last article on the subject, ‘Four Lessons From Learning Python’.
Deploying modern tools, equal parts tactical, equal parts strategic.
I am not a software engineer, this was my first real Python project. Obviously, on top of a short bootcamp training, I had to resort to a lot of hacks… and mistakes. In an effort to maximize my full capacity as both a designer and supremely amateur coder, I used every _free_ resource imaginable: Youtube, Jupyter Notebook, Kaggle, Figma, Freecodecamp, geeksforgeeks and Streamlit. For a fun little experiment, this was extremely satisfying (and frustrating).
It also would not have been possible without the generosity of these BRILLIANT youtube channels. I would highly recommend these folks!
Naval Ravikant wasn’t kidding when he tweeted, “The best teachers are on the Internet. The best books are on the Internet. The best peers are on the Internet.” A 100% TRUTH BOMB RIGHT HERE.
While I was happy with the results, it is still far from usable. It’s more of a proof of concept, less of a solid MVP, really. Which is why I can’t publicly share the link just yet. It’s a mess but if you are interested to know more, please contact me. I’m happy to have a couple of people explore this privately.
Until then, thank you for reading this early case study!
To creating more softwares that fulfill curiosities, may we all ship one small thing everyday. No matter how feeble and irrelevant it may seem at times.
Extended Credits
Aside from the tools mentioned above, I would love to thank the following for all the help. A big THANK YOU!
Data source: @koustubhk from Kaggle, scraped from ev-database
Frontend: Streamlit and Plotly Express
The author is a User Experience Designer and a Qualitative Researcher who recently concluded an Intro to Python Bootcamp. Many thanks to General Assembly and Craig Sakuma. She would highly recommend the course for anyone who wants to learn Python and a little bit of Data Science.
More about the author
Nikki is a Sr. UX Designer working for a data company in New Jersey. In the last 2 years, she has helped design & build a holographic platform, contracted for a research team inside Fidelity Investments, worked in the Design Operations side of an e-commerce company, mentored brilliant design students/career-changers, advocated for UX best practices at RookieUp, have co-taught UX courses at General Assembly and have also contributed directly to the growth of the Mentorship program on UXPA-New York. Designing for a better world is her life. She also runs her own newsletter, working title, about her thoughts on the future and more.
