A filled map uses shading or tinting or patterns to display how a value differs in proportion across a geography or region. Quickly display these relative differences with shading that ranges from light (less-frequent/lower) to dark (more-frequent/more).
Power BI integrates with Bing to provide default map coordinates (a process called geo-coding). When you create a map visualization in Power BI service or Power BI Desktop, the data in the Location, Latitude, and Longitude buckets (that is being used to create that visualization) is sent to Bing.
For more information about the data being sent to Bing, and for tips to increase your geo-coding success, see Tips and tricks for map visualizations.
Filled maps are a great choice:
to display quantitative information on a map.
to show spatial patterns and relationships.
when your data is standardized.
when working with socioeconomic data.
when defined regions are important.
to get an overview of the distribution across the geographic locations.
In this video, Kim creates a basic map and converts it to a filled map.
To create your own filled map, download the Sales and Marketing sample by signing in to Power BI and selecting Get Data > Samples > Sales and Marketing > Connect.
When the success message appears, select View dataset.
Power BI opens a blank report canvas in Editing View.
From the Fields pane, select the Geo > State field.
Convert the chart to a filled map. Notice that State is now in the Location well. Bing Maps uses the field in the Location well to create the map. The location can be a variety of valid locations: countries, states, counties, cities, zip codes or other postal codes etc. Bing Maps provides filled map shapes for locations around the world. Without a valid entry in the Location well, Power BI cannot create the filled map.
Filter the map to display only the continental United States.
a. At the bottom of the Visualizations pane, look for the Filters area.
b. Hover over State and click the expand chevron
c. Place a checkmark next to All and remove the checkmark next to AK.
Select SalesFact > Sentiment to add it to the Color saturation well. The field in the Color saturation well controls the map shading.
The filled map is shaded in green, with light green representing the lower sentiment numbers and dark green representing the higher, more-positive sentiment. Here I've highlighted the state of Wyoming (WY) and see that Sentiment is very good, 74.
For information about using the Filters pane, see Add a filter to a report.
Highlighting a Location in a Filled Map cross-filters the other visualizations on the report page... and vice versa.
On the filled map, select a state. This highlights the other visualizations on the page. Selecting Texas, for example, shows me that Sentiment is 74, Texas is in the Central District #23, and that most of the sales volume comes from the Moderation and Convenience segments.
On the line chart, toggle between No and Yes. This filters the Filled Map to show Sentiment for VanArsdel and for VanArsdel's competition.
Map data can be ambiguous. For example, there's a Paris, France, but there's also a Paris, Texas. Your geographic data is probably stored in separate columns – a column for city names, a column for state or province names, etc. – so Bing may not be able to tell which Paris is which. If your dataset already contains latitude and longitude data, Power BI has special fields to help make the map data unambiguous. Just drag the field that contains your latitude data into the Visualizations > Latitude area. And do the same for your longitude data.
If you have permissions to edit the dataset in Power BI Desktop, watch this video for help addressing map ambiguity.
If you do not have access to latitude and longitude data, follow these instructions to update your dataset.
For more help with Map visualizations, see Tips and tricks for map visualizations.
Add the filled map as a dashboard tile (pin the visual)
Add a visualization to a report
Visualization types in Power BI
Change the type of visualization being used
More questions? Try the Power BI Community