Uploaded by Flourish team 7 days ago (Updated 7 days ago)
What's it for?
Use this template to visualise flows between locations, or journeys.
How to get started
- You'll need two CSV or Excel files. One will contain the locations of the points shown on your map - the start and end points of your arcs. The other will contain the details of the arcs themselves.
- The locations file will need (at a minimum) columns for the location identifier, latitude and longitude. Here's an example:
airport_id latitude longitude 1 -6.081689835 145.3919983 2 -5.207079887 145.7890015 3 -5.826789856 144.2960052
- The arcs file will need (at a minimum) columns for the source ID and target ID of the arc. You can also include columns that can be used to specify the colour or thickness of the arc. Here's an example:
source_id target_id airline 1 2 American Airlines 2 3 American Airlines 1 3 United Airlines
Not sure how to upload your data to Flourish? See our handy guide
How do I reset the initial zoom and centre of the map? For the moment, you need to do this: (1) Create a story from your visualisation (2) Zoom and pan the slide to adjust the zoom and centre of the map (3) In the left-hand menu, under "Navigation", choose "None" (4) Publish the story.
How do I change the colour of the arcs? Two methods. If you'd like them all to be the same colour, use the settings in the settings panel. If you'd like the colours to vary with some property of the data, select a "Category" column in the data panel. Then return to the settings panel and choose the Categorical colour option.
How do I change the thickness of the arcs? Two methods. If you'd like to make all the arcs thicker or thinner, just use the "Thickness" setting to do so. If you'd like the thickness to vary with some property of the data, select a "Value" column in the data panel. Then return to the settings panel and choose the Categorical colour option.
How can I highlight different points on the map? Create a story from your visualisation, then add multiple slides to highlight different views of the data. See the example story below.