Information Visualisation

Petrol price comparison over financial years and state by state:

In this bar graph we are focusing on the different state petrol prices on a year to year basis. The different bars represent the different states and have the same color by year, making it easier to distinguish the different states from another. The y-axis presents value of petrol prices in cents. We can conclude that in 2008/09 the petrol prices were at its peak in all the states. Another conclusion would be that all states stay in the same petrol price range every year, creating a balance between the petrol prices in each state. Each state either raises or lowers its petrol prices each year but all states seem to agree upon the same price range every year.

State by state comparison of concession and full fare interurban train tickets: In this scatter-plot we are showing the capital city population size and the concession price of a public transport ticket and the full price of a public transport ticket. The size of the cross determines the gradual increase in price of ticket per state. The y-axis represents the population size of each state.

From the graph we can conclude that Adelaide charges the most money for both concession and full price of a public transport ticket, even though it is the second smallest state from our study. Sydney charges reasonable prices in contrast to the other states as it has the largest population size. Hobart charges less money for a public transport ticket which is reasonable considering it has the smallest population.

Average Suburban speeds and associated variability during AM, PM, Off Peak and the average of the three:

In this line graph we are presenting Melbourne’s average speed in AM, off peak, and PM average times with variability. The different colors of the lines represent the different times of the day. The graph is divided in two parts, the top half showing the speed and the second half the variability. This is purposefully done because of the different variables.

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Funding of roads and funding of rail over the last five financial years: This graph shows the road and rail funding in the different states over several years. The values on the y-axis are given in millions. We notice that Queensland has the highest road funding throughout the years. We can also conclude that Tasmania, South Australia and Victoria spend the least money on Road and Rail.

Individual costs of road vs rail for the daily commute. This graph shows the different times of the day (AM/PM) and the ticket costs of the road and rail in Melbourne. We have several variables as they are listed on the y-axis. The x-axis consist of inner rail, middle rail, outer rail, inner road, middle road and outer road. The different colors of the bars makes it easier to distinguish the different variables on the y-axis, but are also labeled for your convenience.

We aimed to compare two modes of getting to work that were in direct competition: train and car. We assumed that these modes are intended for longer distances so that bicycling and walking were not viable competitors. Our other main assumption is that all Australian capital cities have their Central Business District (where all the jobs are located) in one, central space. This can’t be said for some sectors such as manufacturing nor can it be applied to other cities in the world.

We set forth to look at the costs between the two modes; how long it takes to get from arbitrary distances from the Central Business District to the outer suburbs (in the afternoon and morning peak traffic jams) and as well as the prices of the tickets and the prices of petrol per litre for each car. These variables would assist in deciding what mode of transport to take to work.

Further, we examined the role of government in allocating money for infrastructure to see if there was any trend over the years between government funding and cost effectiveness on the day to day commute. When it comes to government funding, we were wary to avoid putting Federal Government funds down as that invalidates the data comparison between governments.

Our overarching theory is that government funding in favour of roads hasn’t delivered any tangible benefit for the day to day commute and appears to ignore the constant increase of petrol prices.

In our visualizations we are showing the distribution of coffee all over the world.
We grouped the overall yearly production of coffee in each country and added a
slider to illustrate the yearly changes. Then we grouped the different countries into
continents. We are showing the different continents coffee production on a year-by-
year basis. Again the slider will illustrate the change in production over time. We
delineated continents by color and coffee production by size. The larger the dot on
the map signifies the amount of coffee produced. Unsurprisingly Brazil is the largest
coffee producer in the world.

Our next few steps will be to plot multiple years across the same map. We intend to do this by adjusting the colour tone of each bubble over each country. Colour transparency could represent quantity of coffee produced (with an adjoining chart showing exact amounts), shape could provide a year and actual colour blocks for each continents as we have done below.