Choropleth – Centroid


Centroid choropleths are another common type of visualisation tool. Similar to classic choropleth maps, centroid choropleths differ in the central point (“centroid”) of an area (“polygon” on a map is represented, with varying colour and symbol size, rather than the entire area being shaded according to the variable. The centroid is shown in proportion to the measurement of a variable being displayed on the map, such as population density or average income, or as shown below, percentage of the population involved in volunteering. It allows for two datasets to be overlaid on top of each other, such the one below showing the rate of Type 2 Diabetes across Sydney (yellow to red polygons) and the rate of Circulatory System Diseases across Sydney (green circles)

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Choropleth centroid maps can be created quickly and easily in the AURIN Portal and provide a useful first pass at detecting and visualising interesting spatial patterns in your data.

We will illustrate it’s use by creating a choropleth centroid map similar to the one above. To do this

  • Select Sydney GCCSA as your area
  • Select SA2 Chronic Disease – Modelled Estimate as your dataset, selecting SA2 Name, SA2 Code and Circulatory System Diseases – Rate per 100  as you variables

Once you have accessed this data, open the Choropleth Centroid tool (Maps, Charts and Graphs → Map Visualisations → Choropleth – Centroid) and enter the parameters as shown below. These are explained below the image.

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  • Select a dataset: Here you can choose which of the datasets you would like to display as a map. In this exercise we use SA2 Chronic Disease – Modelled Estimate
  • Select an attribute: This is the field that you want to map. If you want your map to make sense, and actually display the variable you are interested in, it is important to make sure you have selected the right attribute to map together with right classifier. For this example we choose Circulatory System Diseases – Rate per 100
  • Select a classifier: Here we define how we break up our range of values int he attribute. For an attribute that is numerical in format (either an integer or a decimal),  the default setting for this field is Jenks (Natural Breaks), which breaks your data up into intuitive groups based on the shape of distribution of values. You can select Quantiles or Equal Intervals. If your attribute is categorical – that is, if it is a description or a word (such as a land use zone, or a name, or any kind of “string”) then the parameter will automatically set to Pre-classified. For this example we choose Quantile.
  • Number of Classes: This slider allows you to define the number of breaks in your data (minimum of 3, maximum of 12). The number that you choose should depend on the distribution of your values, the number of data points (areas) and the information that you are trying to portray with your data. For this example we choose 6
  • Select a palette type: Here you can choose the type of colour scheme for your data – Sequential, which shifts from a shade of one colour to another;  Qualitative, where the colours are unique along the palette (used for Pre-classified) ; and Diverging, where colours shift to two colours from a central point  along a natural spectrum. For this instance we choose Sequential.
  • Palette: This allows you to choose the actual colours of your palette (you can switch the ends of the palette around by clicking the Reverse Palette box at the bottom of the box. AURIN uses colours generated by Colour Brewer. For this example we select Greens
  • Default Opacity: This slider allows you to define how opaque your map is over the base map. 0.00 indicates completely transparent, 1.00 indicates completely opaque. Here we select 0.85
  • Set minimum radius: The size that the smallest circle will take on your map. Here we select the minimum of 1
  • Set maximum radius: The size that the largest circle will take on your map. Here we select the minimum of 20
  • Select a scaling method: This determines how the circles will be increased in size from the smallest to the largest. You can select from Perceptual, Mathematical and Range-graded. Here we select Range-graded, but have a play around to find what you think looks best on your map.
  • Name: The default for this field is “Choropleth-Centroid-X”. It’s a good idea to change the name of this to something that reflects the data, particularly if you plan on having multiple choropleth maps from different datasets. The name that you choose here will also be displayed in the legend automatically generated for your map. Here we use the name: Rate of Circulatory System Diseases by SA2 in Sydney

Once you have selected your parameters click Add and Display.


Your map should automatically appear on the screen, and should look something like the image below. It will also appear under your Visualise pane on the right. You can turn the map on and off by clicking on the little map icon to the left of the name of it in that pane.

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You can edit aspects of the choropleth, such as the parameters you’ve chosen for its visualisation, or changing its name, by clicking on the spanner symbol to the right of the map name in the Visualise pane