Purpose
The aim of this request is to investigate and visualize data. In particular, we will identify trends, gain insights from how those trends change over time.
The data we will use contains Airport traffic data and comes from the Australian Bureau of Infrastructure, Transport and Regional Economics.
The CSV file contains 30 years worth of monthly data listing international air traffic volumes in terms of passengers, freight and mail, to and from Australian airports.
The file is available on Moodle and publicly available from data.gov.au
Hand-in Requirements
Please hand in a PDF file containing your answers to all the questions.
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 screenshots/images of the graphs you generate in order to justify your answers to all the questions. (You will need to use screen-capture functionality to create appropriate images.)
We would like to see the Python code you write to format the data. Please include a copy your Python code in your submission, (either submitting scripts / Jupiter notebooks, or copying the code into your report).
Python Availability
You will need to use Python to complete the request. You can do this by either:
1) running a Jupyter Notebook on a computer in the labs; or
2) installing Python (we recommend Anaconda) on your own machine.
request Tasks
This request involves building a visualisation using Motion Chart and then answering a series of questions about the data.
Visualising Airport Traffic
The aim of the first part of the request is to build a Motion Chart showing passenger, freight and mail quantities over time for four different airports in Australia (Melbourne, Sydney, Brisbane and Perth). More specifically, you should:
Generate a Motion chart with Passengers_Total on the x-axis, Freight_Total_(tonnes) on the y-axis and where the color and size of the bubbles is given by the Mail_Total_(tonnes).
Note that the CSV file is both too big and not in the right format to visualise directly, so you will first need to aggregate the data using Python at both the ‘Year’ and ‘AustralianPort’ level. (Code to help you do this was discussed during the lectures.) You need to select only four Australian airports before the aggregation.
You can then output the data as a CSV file, which you can use in order to create the appropriate visualisation (see Activity: Motion Chart - Motion Chart in Python in Alexandria).
Having graphed the data as a Motion Chart, answer the following questions:
Why are the values lower in 2016 than they were in 2015?
Which city has the largest number of international air passengers traveling through it in 2015?
In which year did Brisbane have almost the same number of passenger numbers as Melbourne?
(Bonus question) Has the number of passengers travelling through Sydney airport ever decreased from one year to the next? If so, when did it happen? Any idea why that might have occurred?