How to use points, spikes and arrows in the Projection map
Our Projection map template features a powerful Points layer that can help you visualize information about specific locations on your map. In contrast to a traditional region map, a point map uses latitude and longitude coordinates to display area-specific information.
You might want to create a point map if you want to:
- Visualize data associated with specific locations, not whole areas
- Show patterns associated with the location of the data points
This help doc will show you how to create a point map, as well as how to customize the appearance of your points.
In this article
Circles vs spikes vs arrows – what's the difference?
The Projection map template allows you to use circles, spikes or arrows to visualize your points. While it's very easy to switch between the three in the Flourish editor, these symbols can serve different purposes.
While circles are a very popular way of indicating specific locations and their respective values, they come with a few downsides. Due to the fact that the bubbles grow in all directions, circles tend to cluster and obscure the map more than other shapes.
In contrast, spikes only grow in height, making lower values easier to spot.
Swing arrow maps, on the other hand, are a popular way to visualize election results – read more about them here.
How to create a point map
TIP: Struggling to find the right regions for your map? Check out our GeoJSON repository where we've sourced, checked, and resized various region files ready for you to download and use in Flourish.
TIP: If your data doesn't come with longitude and latitude values, you can use generic coordinates for countries. The Gapminder Foundation has created a freely available spreadsheet with basic information on a country by country bases.
Plotting negative values
Plotting negative values is something you cannot achieve with points. Instead, you'll have to use arrows or spikes.
Since spikes increase in height, negative values will cause spikes to be rendered downwards, rather than upwards.
Customizing the Points layer
Once you've imported your data and added the relevant column bindings, you should have a perfectly adequate point map. However, there are several things you can do to improve it or to focus on different aspects of your data.
If your data has a relevant numeric variable, you can bind that column to the Size by column binding to scale your points based on it. This will morph your map from a point map to a proportional symbol map. See the story below for a practical example:
TIP: Sometimes, spikes positioned at the top or bottom of your map may get cropped. To fix this, add padding to the top or bottom of your visualization under the Projection settings in the template.
WARNING: By default, points are colored categorically, meaning that the template will assign a different hue to each unique value in the column, whether that is a number or a string of text. However, you can create a "fake" numeric color scale using spreadsheets and a fake legend following the steps outlined in our help docs.
You may also have to adjust the data type of the column you color by, since the template only supports string data format for this setting – learn how to do this here.