Basic Mapping in Tableau

Maps are a good way to visualize location-based data. Tableau recognizes geographical fields such as country, city, and automatically generates the latitude and longitude. This prevents users from manually looking up coordinates.

There are four different types of mapping:

1. Symbol Map

2. Filled Map

3. Dual-Axis Map

4. Mapping Non-geographical Fields

Symbol Map

Symbol map allows you to show multiple measures on a single map. For example, you can use color and size for two separate measures.

Let's see how to show every city by profit and sales.

1. Double-click City from the Orders table. This will generate a map.

2. Drag Sales to Size and Profit to Color.

3. Increase the size of the points by using the Size on the Marks card. The final map would look like this:

Symbol maps are good for showing exact locations. You should also choose the right measure to use on the Size property. If the measure contains negative numbers, then do not use it on Size as it would not be accurately displayed. The best option for measures that contain negative numbers is to use on Colors.

Filled Map

A filled map can have a bigger impact when compared to a Symbol map.

Let's visualize the profit per state using a Filled map.

1. Double-click the State field under the Orders table.

2. Drag Profit to Color on the Marks card.

The final map would look like this:

This filled map shows the lowest and highest profit per state.

You can choose from several styles of maps and edit the maps to suit your needs. The options to edit maps can be found under the Map option.

You can change the type of map, the level of detail on the map, etc.

Tableau can use the Map mark type only when you have country, state, region, or country geographical fields. You cannot create a filled map at the city or postal code level. To do so, you would need to use custom geocoding or spatial files.

A filled map should be used for geographical fields of only state or higher. To show cities, you need a point map.

Note: Use filled map with caution. Especially when you have smaller countries or states that have higher value. Their smaller size means you might not instantly see that. This is where symbol map is better at visualizing the smaller areas.

Dual-Axis Map

Maps in Tableau use latitude and longitude, either generated by Tableau or present in the data set. Both these fields would be continuous, measures, or dimensions. This means they create an Axis that can be used to create a dual-axis chart, which means having two separate Marks shelves.

Let's see how to show Sales by state, with city by sales and profit layered on top.

1. Create a filled state map by Sales and change the color scale to gray.

2. In the Rows shelf, duplicate "Latitude (generated)", by pressing Ctrl (Command on Mac) and dragging it next to itself. You can also duplicate the "Longitude" field in the Columns shelf.

3. On the third Marks shelf on the left, "Latitude (generated) (2)", drag City to Detail, Sales to Size, and Profit to Color on the Marks card.

4. The final step is to create the dual-axis. Right-click the second latitude field int he Rows and select "Dual- Axis". Your final map would look like this:

Mapping Nongeographical Fields

Tableau recognizes various levels of geographical fields. But region is not one of them. As long as you have other geographical fields, like state, or city in your data set, you can convert a nongeographical field into a geographical one. This means, you will be able to plot it on a map.

Let's see how to visualize regions on a map.

1. Right-click the Region field and select Geographic Role -- > Create from -- > State. This changes the Region field to be geographic.

2. Now, you have your region as a geographic field. Double-click Region, change the default mark type to Map, and add Region to Color. The resulting map would look like this:

Using other geographical locations, like state or country, to enable creation of a new geographic field is a powerful way to be able to visualize nongeographic fields like regions.

Map visualization is very useful to research and display the geographically related data and present it within maps. This kind of data expression is clearer and more intuitive. You can visually see the distribution or proportion of knowledge in each region. It is convenient for everybody to mine deeper information and make better decisions.