Maps are a versatile tool in any analyst’s toolkit. Visualizing data on a map can often highlight spatial relationships in a way that no other chart can. The context provided by seeing geographic regions, landmarks, and other features can be vital to understanding patterns in your data.
Google Data Studio allows you to overlay your data directly onto Google Maps to add detailed geographic context to your reports and dashboards. In this post, we’ll look at examples of how Google Maps can be used in Data Studio with different datasets.
There are two types of Google Maps charts available in Data Studio: Filled Map and Bubble Map. The Filled Map allows you to plot your data over geographic areas, such as country, state, and ZIP code, appearing as shaded regions on the map. The Bubble Map lets you plot data points at specific map coordinates, including latitude/longitude and address.
Both types of charts provide familiar Google Maps functionality, including pan-and-zoom, satellite view, and even Street View, all without leaving your Data Studio report.
Here are some examples that demonstrate using Google Maps in Data Studio:
Maple Trees in Downtown Vancouver (Bubble Map)
In this report, we look at the location of maple trees in Downtown Vancouver using data from the Vancouver Open Data Portal. The bubbles are plotted using the latitude and longitude of each tree. The size of the bubbles corresponds to the recorded diameter of the tree and the colour denotes the species. You can use the chart on the right to filter for a particular type of tree. Be sure to also try out satellite view and street view on the map to see the trees for yourself!
Average Flight Prices by U.S. Airport (Bubble Map)
This report shows the average flight fare for each airport in the United States. The bubbles are plotted using the latitude and longitude of each airport and are sized by the average fare. Try using pan and zoom along with satellite view to find your favourite (or least favourite) airport!
Median Income by ZIP Code in New York City (Filled Map)
In this report, we have plotted the median income of each ZIP code in New York City using a filled map. The colour of each shaded region is determined by the Median Income metric and indicated by the gradient above the map. Try clicking on a specific ZIP code in the table to filter and zoom in on the map.
We hope these examples give you some ideas for how you can use Google Maps to visualize your own data in Data Studio. Let us know what you create!
Complete list of posts in our 2020 Data Studio series:
1. Visualizing the COVID-19 Pandemic in Google Data Studio
2. Creating a Google Analytics Dashboard in One Click
3. Using Google Maps in Data Studio (this post)
4. Visualizing BigQuery Public Datasets in Data Studio
5. Measuring Web Vitals – Part 2: Monitoring in Data Studio
6. Using Parameters in Data Studio
7. How to Style Links in Data Studio
8. Using Filter Controls in Data Studio
9. Extracting a Theme from an Image in Data Studio
10. Building a Google Analytics 4 Dashboard in Data Studio
11. How to Convert Text to Dates in Google Data Studio
12. 12 Tips for Enhancing Your Tables in Data Studio