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9. Symbol Maps
Symbol maps provide much more granularity than fillable maps we showed in a previous lesson. Learn how to create symbol maps in this lesson.
- Used for plotting individual locations rather than regions
- More flexible than fillable maps as both color and size can be applied to categorize data points
- Typically rely on columns such as City and Zipcode to plot individual data points
- Tableau contains mapping layers that can be added to your visualization
- These layers (e.g. Place names) can provide great geographical context for users
- Always experiment with mapping layers when using symbol maps
- To practice geocoding addresses, a number of online tools are available
- http://www.gpsvisualizer.com/geocode is one of these tools, relying on the Google Maps API
As we saw in the previous lesson filled maps are pretty easy to create in Tableau because Tableau can easily identify the columns such as state, province or county to dynamically create these maps for you without worrying too much about geo-location.
However, sometimes you'll want more granularity than just comparing large geographic regions and for this type of visualization you'll need to use symbol maps.
In this particular case, I want to view the customer base in the context of the tristate area.
So instead of using state as my level of detail I am going to use postcode When I do this, Tableau immediately realizes that a filled map is not possible.
And instead automatically switches to a symbol map However, the shape is still a filled map.
Let's switch this to a circle.
And now we have all of our customers on a map that we can examine in more granular detail I am going to color code each customer by sales person And I am going to size each dot by annual revenue And with these changes in place let's now zoom in on the tristate area and see if we can do some analysis.
So, I'll simply zoom into this area.
And let's zoom in a little further.
With our map now created, we can actually compare the performance of sales people within this particular region.
So, let's select Palacios who tends to be a high performer and compare him against say Gilman And so, you can see how much more customers Palacios has than Gilman in this area.
Sometimes, if you want to go even more granular you may want to include some additional map layers to make the map a little easier to read.
To do this, let's go up to the map dropdown and go to map layers And while a couple of these are selected automatically I am going to select streets and highways and I am also going to select place names and again, this gives my map a lot more context So again, if I am very focused on the New York area I can select my zoom function, zoom in on this area And as you can see, my place names include Brooklyn, Manhattan, Yonkers and White Plains.
As we did with the XY Scatter plot it's nice to list either selected customers or sales people on the right-hand side that can interact with our visualization.
Off camera, I have created a new dashboard which includes our map of the tristate area, and the revenue by each sales person.
If I want to compare performance by sales person on the right-hand side of this map, I simply select all of these individual customers.
And in a very nice interactive feature, my chart updates on the right-hand side.
And as you can see, Palacios has more than double the revenue of the newer sales person in this part of my map.
Now it's all very well and good having the postcode for every single customer in the US.
And enabling Tableau to do all the heavy lifting around geo-coding.
But what happens if you don't have post codes? For example, in a country like Ireland.
Well in this scenario, Tableau won't be able to generate the geo-coordinates automatically for you.
And you will need to use some geo-coding software such as google maps and these software programs simply convert and address into a value for latitude and longitude.
Latitude and longitude can then be uploaded into Tableau which can then generate the map for you.
If I go back to my sheet, you'll see that Tableau actually auto-generates latitude and longitude from postcode.
And when you have these columns in your data set they'll simply appear down here as a measure.
There are many other options you can explore with maps including connecting different points on a map to create routes, layering custom background images behind maps, and even generating your own custom boundary areas, with shape files.
All of these advance mapping options will be covered in a later course, on advanced visualizations.
For now, if you can recreate the filled maps and symbol maps that I have shown you in these last two lessons you should be able to really impress your manager and your clients with these excellent visualizations.