Plotting geo-location: are dual-layer maps the right chart for you?
Before creating a map in Tableau start by asking yourself whether you actually need a map to visualise your data. If your business is shifting from a P&L-centric approach to visualising the spread of your overall profitability then probably the answer to that question is yes. The same applies if you are looking at your profit by state, sales by region, product exports destinations by postal code, custom sales territories or simply your own custom geocoding.
Below you will find our step by step guide into creating a map with multiple layers using Tableau’s included Superstore data set.
Start by dragging State to Rows and select the filled map option from the Show me tab located on the top left of your workbook. Tableau has automatically generated and assigned the latitude and longitude to each data location based on data already found in the Tableau map server. Drag Country into Detail to generate the following view and zoom in to focus on US.
Next, drag profit into Colour to create our Profit versus Sales visualisation by choosing a colour palette that best fits your view. In this case, we’ll go with the red-blue diverging palette to better show the contrast between high and low or even negative profit generating states.
As seen in the image below you can easily spot the highly profitable states versus the least profitable ones.
Using a diverging colour palette for profit that has both positive and negative values is an effective way to display the difference between the two, however be careful when you’re dealing many states whose profit is close to 0 which, as in our example, will appear grey-ish. This means it's not only difficult to differentiate which was the most/less profitable but even to distinguish if these states have a positive or negative profit. In this case, it it suggested that using a stepped colour diverging palette with even number of steps could be applied to the view in order to eliminate grey shades between red and blue.
To duplicate the map on your visualisation, hold down Control and drag Latitude onto Rows. This way you can have two US maps looking like the following :
On your Marks card, keep the second Latitude selected and remove Profit from the Marks Shelf. That turns your second map into a uniformly grey coloured map. Next drag Sales onto Size, and select Circle from the available chart types instead of Map.
Change the colour of that circle to black.
Make sure you uncheck the show the hidden labels to remove marks from the second view.
To join these 2 different versions of maps into one, select the little menu on the right handside of the second Latitude pill and select Dual Axis from the options below.
Now you have both of the visualisation layered on top of each other looking like in the following picture:
Since Size represents your sales and Colour represents your profit make sure to increase the size of your circle to better see which are the highest sales generating states.
To remove the layers from the map since we are only focused on US, go to the Map menu and select Map Layers from the option below. Then uncheck all the boxes so that you’re only left with US in your visualisation.
At this point, you have created a dual layer map that helps you visualise the spread of profit and sales amongst your selected geographic location.
You can always consider using maps in combination with other data or utilize them as a layer to your charts on top of maps. By layering any chart on top of a map it is easy to interpret the geographical impact of different data points quickly.
Tableau is also helpful in customizing how your background map looks by offering you a choice to select from some predefined options. This is simply done by clicking the Style drop-down menu in the Map Layers pane on the left-hand side of the workspace and then selecting a background map style. However, if none of Tableau’s options satisfy your requirements you can always import your own background map.
Maps can easily be perceived as a great interactive tool to enhance your geographical analysis. Within the right context, and with the right colour and layers they are an efficient way to bring your geographical data to life. Similar to booking your vacation, you wouldn’t leave your house without unconsciously visualising the destination on a map, would you? Chances are you’d ask for the same informative view from your data.