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Categorical data is data that is divided into groups such as: age, gender, occupation etc.
To create a map of categorical data, you first need to plot the data points on a map. The previous page, , provides detailed instructions on how to add data points to the map.
Once you have created a point map, drag the column in your data that contains the different categories into the Point: Colour field of the visual. The map will automatically recolour the points based on the different categories in your data.
Up to 12 different categories within your data are currently supported.
The only way to change the colour of categorical data (points & polygons) is by specifying the relevant colour hex code (for example, #cdf1f0) in the data and dragging the column of data that represents the colours to be used into the relevant Points/Features Colour field in the visual. There is currently no way for users to customise the colours that are displayed for categories by default via the user interface.
Adding hex codes into your data to manipulate the point colours won’t update the category colours within the legend.
It’s quite common that a user will want to vary the size (radius) of the points on the map to represent an increase in occurrence or density (for example, larger points represent a greater number of crimes at that location)
To do this, having plotted points on a map, drag a data column containing numeric data into the Points: Size field of the visual.
Then click on the downward arrow of that field and select Count. Now the size of your points will be based off the total count of data points at the locations of your points.
You can combine the colouring of points based on categorical data and the size of points by another data attribute to represent two different variables in a single point within your data.
Point size only accepts a numeric data type.
See an example below showing a combination of categorical data (crime type) and point size variation (count of crime).
Additional information about a point can be displayed as a pop-up when a point on the map is clicked.
To add a pop-up to a point on the map, drag and drop data into the Points: Pop-ups field in the visualisation pane. Information included in the pop-up field should be shown when a user clicks on a point.
Multiple data columns can be shown under pop-ups.
By enabling point pop-ups based on different data attributes, points that appear in the same location can be filtered on the map (see screenshot below, where points can be filtered on the map by crime type data).
It’s quite common that points on a map will overlap, making the data more difficult to understand. For example, when considering crime data, a shoplifting crime and a violent crime may have been recorded to the same x, y coordinates; however, one point will be plotted above the other, therefore obscuring some of the data.
By dragging a relevant column of data into the Point: Pop-ups field then the user has the ability to click on a point on the map to reveal a ‘pop-up’ and paginate through all the underlying points that were originally obscured.
Below is an example of a pop-up where data representing crime type is being used to enable pagination of overlapping points. The pop-up shows there are 5 points representing different crime types in the same location.
By adding a column of data into the Points: Colour field containing textual data that represents categories (for example: School, Library, Gym) then the points on the map will automatically colour based on a default colour palette and a legend will be generated on the map showing what colour represents what category (e.g. School = Green).
However, the colours can also be customised by specifying hex codes within the data. The only way to change the colour of categorical data (points & polygons) is by specifying the relevant colour hex code (for example, #cdf1f0) in the data and dragging the column of data that represents the colours to be used into the relevant Points/Features Colour field in the visual. There is currently no way for users to customise the colours that are displayed for categories by default via the user interface.
