This article is about building maps in Tableau, maps are very powerful in displaying metrics across geographical coverage, hence enabling users to spot variations between different regions. We'll use data on Main type of roofing in Kenya to show how different roofing materials vary across different County's.
But first, connect above data set to Tableau, and follow the guideline below.
Step 1: Assigning geographical role.
Looking at the data set below, you'll notice that the field 'County' is a string field instead of a geographical field.
We can assign a geographical role on the 'County' field by the following procedure.
Note, once we've executed the above, the string icon is automatically replaced with a geographical icon implying the field contains geographical data.
Step 2: Build our map.
Open a new sheet; drag the dimension field 'County' to the detail tab under the marks card. Note, am getting a blank page with 47 unknown values.
To rectify this, we'll edit location to match that of our data by selecting on the text '47 unknown' and following the guide below.
Executing above leaves us with data points which can be filled by selecting Map under marks card.
Now, we can visualize how different roofing materials vary in different County's by dragging the particular field to color. Let's say am interested to understand where majority of households are roofing with grass. Dragging the measure field 'Grass' to the color shelf under marks card and aggregating the field by 'Average' since the lowest level detail is 'District' we've.
Let's do some color editing by selecting 'Edit Colors....' under the color legend above.
Executing above enables users to spot on the go where most households use grass as a roofing material.
From this display, there are more households in the North-eastern region who use grass as a roofing material as compared to the Central and Coastal region. Note; Other categories could also be analyzed by dragging them to the color shelf.
Dragging each category to the color shelf is time consuming and doesn't empower users when consuming insights with the flexibility to chose what to view. Therefore, in one of the upcoming article we'll discuss about using Parameters and Filters to improve user-dashboard interaction.
Stay tuned to learn more.