| Question |
The aim of this assignment is to investigate and visualise data using various data science tools. It will test your ability to: 1. read data files in Python and extract related data from those files; 2. wrangle and process data into the required formats; 3. use various graphical and non-graphical tools to performing exploratory data analysis and visualisation; 4. use basic tools for managing and processing big data; and 5. communicate your findings in your report. You will need to submit two separate files (Note: Submitting a zipped file will attract penalty of 10%): 1. A report in PDF containing your answers to all the questions. Note that you can use Word or other word processing software to format your submission. Just save the final copy to a PDF before submitting. Make sure to include code, the output and any screenshots/images of the graphs you generate in order to justify your answers to all the questions. (Marks will be assigned to reports based on their correctness and clarity. — For example, higher marks will be given to reports containing graphs with appropriately labelled axes.) 2. The Python code is a Jupyter notebook file (idnumber_FIT5145_A1.ipynb) that you wrote to analyse and plot the data. (Note that the entire assignment should be completed using python) Assignment Tasks: The way we supply and use energy in Australia is changing. To understand these changes, to plan for Australia’s energy future, and to make sound policy and investment decisions, we need timely, accurate, comprehensive and readily-accessible energy data. The Department of Industry, Science, Energy and Resources is responsible for compiling and publishing Australia’s official energy statistics and balances . 1 The is updated annually and consists of historical energy consumption, production and trade statistics. In this task, you are required to explore the statistics covering all electricity generation in Australia. This includes by power plants, and by businesses and households for their own use, in all states and territories. This also includes both on and off grid generation. We have extracted the data from the original files and restricted it to a specific time period. download the dataset for this assignment from the following link: |
