Visualizing data on geographical maps
1. Visualizing data on geographical maps
Hi there! We're about halfway through this course, and I'm glad you're still with us! In this chapter, we will learn how to work with maps in Tableau, covering both classic geographical maps and custom mapping on any other background.2. The digital cartography
Welcome to the world of digital cartography, the digital art of map-making. With tools such as Tableau, you can taste the feeling of being a modern cartographer. Before we start, let's appreciate this field's evolution, from paper maps to digitalized ones, bringing us far beyond static 2D pictures. With Google Maps, we can watch the world in 3D, and thanks to GPS navigation systems, we no longer struggle to find directions. GIS, the geographic information system, plays an important role in structuring and systematizing this field, becoming a fully-fledged subdiscipline of geography. With intense digitalization, new professions emerged, such as GIS tools and application developers or location intelligence experts.3. Basic (digital) geometries
Before we dig deeper, let's bring all to a common understanding of basic geometries. Points, so indicators of the exact location, require X and Y coordinates, and in 3D maps may additionally contain a Z value, informing us about the point's height. Lines link points and create a chain, also known as polygonal chains. Polygons, in other words, planes, are figures described by a finite, closed sequence of lines with a clear starting and closing point.4. Various (geographical) spatial data types
When working with geographical data in Tableau, we can upload plain text or spreadsheet data files containing geographical information. These could be, for example, latitude and longitude coordinates, but also fields containing internationally recognized codes. These include country or city codes and names, airport codes or even more specific statistical geographical units, such as the European NUTS¹ codes. This type of data will allow us to draw point maps. Another option is working with spatial files, such as Shapefile or GeoJSON. Such files store information on coordinates needed to plot a point, a line, or a polygon (in other words - a shape) and often contain metadata on these places. This type of data can easily facilitate maps consisting of various geometries.5. Recognizing the fields as geographical data
When we upload the data to Tableau, in many cases, the code or coordinate fields will be auto-recognized as geographical data and marked with a small globe icon. When this happens, the Tableau map server automatically creates latitude and longitude measures, containing precise information on the place. However, in other cases, we will need to give Tableau a hand, manually assigning the geographic role and specifying its type. It may be as trivial as converting latitude and longitude fields to numeric decimals and correcting the typos or alternative spellings. Still, in some cases, we will need to upload a custom geocoding file. Think, for example, about plotting all high schools and universities on the map: doing that will require supplying a data file with their coordinates.6. Working with GeoJSONs
GeoJSON data can easily store any kind of geometry. In this example, we see a GeoJSON-based map of Amsterdam's neighborhoods. The pink-colored district of Osdorp is recognized in Tableau as a multipolygon (a polygon containing other polygons). When we look under the hood, it's a GeoJSON geometry described by 252 multipolygon coordinates. Fun tip! You can easily edit and adapt GeoJSON files. Interested? Head over to the below link.7. Airbnb dataset
Let's wrap this video up with the intro to our new dataset! We will explore Airbnb data, discover Barcelona as a popular touristic destination, and plot many insights onto interactive maps.8. Let's practice!
Before we do so, let's check what you still remember from this video.Create Your Free Account
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