London’s Efficient Energy Consumers

The Dataset

On the second day of our Dashboard Week, we are given a dataset about smart meters in London from Kaggle. It has household energy consumption data that has granularity of either daily or every half hour. I chose the daily grain because I want to get the daily energy consumption per household. I used that measure to compare households of different Acorn category and group. Are these enough for me to find who is London’s efficient energy consumers?

External Dataset

One of the dataset in Kaggle has Acorn information about the index for different measures like population and household. The problem is it is only in a group level and not in a category level. I need both so I decided to download and use the Acorn knowledge worksheet.

Alteryx Workflow

My data preparation is so simple that an Alterook can do it. I used four input files and produced four hyper files. I will create relationships on Tableau using the hyper files. Here’s what my workflow looks like:

London's Efficient Energy Consumers

Charts Used in Tableau

I used lots of bar charts and a radial bar chart. It’s my first time creating a circular bar chart and I followed Luke Stanke’s tutorial. The radial bar chart looks cool but a bit difficult to interpret. Use it with caution.

Highlighting Data on Sheet in Tooltip

When we add a sheet in a tooltip, the default is filtering all field by the data where we hover our mouse onto. What if we just want to highlight and not filter? This tutorial helped me do that.

The Finished Product

Here’s a preview on my dashboard and you can always view it in Tableau Public:

London's Efficient Energy Consumers

So Who’s Efficient and Why?

If you visit my viz, hover on any purple bar. These bars represent the Acorn category Rising Prosperity and is composed of Acorn groups City Sophisticates and Career Climbers. They are second in terms of daily energy consumption per household. Their consumption is just a little higher than the Comfortable Communities (rank 3) but much less compared to the Affluent Achievers (rank 1).

An Acorn category’s household annual income index is proportional to their consumption and is true for all Acorn categories. Rising Prosperity is very close to rank 1 but way ahead of rank 3. On the other hand, the number of bedrooms in a house is also proportional to their consumption. This is true for everyone except for the Rising Prosperity. They have high income but most of them live in one-bedroom houses. This is a big factor why their consumption is not too high.

Based on the Acorn knowledge worksheet, households under the Rising Prosperity category are composed of either young people who are in the early stage of their career, has young family or first time home owners. They live in small modern homes in metropolitan areas.

JB Reyes
Author: JB Reyes

JB hails from the Philippines where he was an anti-malware engineer for 5 years. After moving to Australia in 2017, he worked his way up in a school supply company starting with a role as a despatcher and then taking on roles in IT support and bookkeeping. His passion for data is so deep that he can spend hours exploring and analysing data without tiring or getting bored. When JB is not all over data, he spends his time playing basketball, Pokémon cards with his daughter and building robot plastic models. If there is one dish that he would have to eat for the rest of his life, it would be Lechon, a Filipino delicacy (roasted pig) that reminds him of home.