Smart meters are now installed at every property in Melbourne. The Victorian government has a current initiative to encourage households to examine their energy use and particularly to get a better deal on energy pricing. Their tool to compare suppliers is at If you use this tool between now and the Jun 30, you will get an energy rebate of $50.

In order to compare your energy, you need to download your own usage data, and upload it to the compare website. It is relatively straightforward. You need to go to your provider’s page, which can be determined by visiting If you have a recent bill, your meter number will be on it. You need this to create a login with your energy provider (for me this is citipower,, so that you can download your data.



About the data

The format of the data should csv and look something like mine, which is provided, meter_di_2019.csv. In addition, there should be a web page, like this one from citipower describing the format of the data, that will be useful when you are trying to tidy it. You should be able to see half hourly electricity usage.

You need at least one energy usage data set per group. Everyone in the group should work on this one. If you have problems getting your own data, we will provide you with ours.

To analyse the energy data, we will also pull weather data from the Bureau of Meterology, and merge the two. If your household has air conditioning we would expect that your usage would be higher on hot days.

The goal of this exercise is to practise wrangling data, work with time, and join data sets.

  1. Describe the steps that you will need to take to read in your electricity usage, and tidy it. Tidy your data, using the tidyverse functions. The end product should look something like this:
  date       halfhour   kwh
  <date>        <dbl> <dbl>
1 2017-11-24      0.5     0
2 2017-11-24      0.5     0
3 2017-11-24      1       0
4 2017-11-24      1       0
5 2017-11-24      1.5     0
6 2017-11-24      1.5     0

although your halfhour variable might be more explicit like 12:00-12:30, 12:30-01:00, 01:00-01:30, … And you might want to add week day, month, year variables.

  1. Subset your data to contain only records for January 1 through March 18, 2019.

  2. Aggregate your daily kwh usage. (This really assumes no missing data.) Make a side-by-side boxplot of usage by week day. Are there some days of the week that you typically use more electricity than others?

  3. Make a line plot of half-hourly usage for the days February 2-7. Describe what you learn about electricity use during this month.

  4. Extract temperature data at Melbourne airport from the Bureau of Meterology using the bomrang package. Colour the line plots from the previous question, based on the maximum daily temperature. What do you learn about the relationship between your energy use and the maximum daily tempoerature.

  5. Decide on one more plot, for each group member, to make to learn about your energy usage and weather. Make these plots and write some paragraphs describing what you have learned.

  6. Build your answers to these questions into a learnr interactive tutorial, with separate pages as appropriate for each question (2-6), and an interactive quiz on each page relating to the material on the page, to help the reader engage in your energy data analysis.