For this challenge, I decided to answer the following question: Are demographics properly represented in London’s smart meter experiment?
Interestingly, affluent groups account for 39% of the sample size in the experiment while these groups only account for 12% of London’s 8 million population. My suspicion for the relatively high representation of affluent groups is that the latter tend to consume more energy hence why a higher proportion was included in the sample. Among the affluent groups, the career climbers accounted for most of the sample size (between 70-80%). Yet, I have identified that the city sophisticates consume more energy on average compared to other affluent groups apart from the lavish lifestyle group.
Below is a snapshot of my dashboard, which you can access here:
And now, I would like to outline the approach that I have taken to merge the required datasets to power the dashboard:
Step 1 – Combine daily energy consumption and household attributes.
Step 2 – Summarise the spatial data and split it into 2 groups: affluent vs other groups.
Next steps
I was not able to find out why the city sophisticates consumed more energy. So, there is room for more investigation. To do so, the index dataset needs to be re-shaped and wrangled and fed into the association analysis tool – which allow me to obtain Pearson correlation measures across all index categories.
Author: Fabrice Joseph
Originally from Mauritius, Fabrice moved to Australia to complete a Bachelor of Commerce (Accounting) at the University of Queensland. Since graduating, Fabrice accumulated 7+ years of experience in primarily management accounting roles and a couple of entrepreneurial projects. Having encountered data in the accounting profession, Fabrice had developed a passion for analysing data, extracting insights and findings ways to improve his workflow. Such is his passion for data that he has data projects as hobbies. Data School was the natural next step for him to launch his career in data. Besides data, Fabrice has other interests such as yoga, reading books on ancient history and philosophy.