6. Data Exploration: Exploring Geographical Data

Overview

This chapter reviews the geographic capabilities available within Tableau. Tableau provides an extensive set of options for working with location-based source data, which can help you design solutions using either point or polygon location data. By the end of this chapter, you will be able to effectively use geographic data in Tableau to perform sophisticated location-based analyses. You will gain a greater understanding of how to import multiple data formats and use your data to create polished, interactive maps. These skills will be developed through a series of exercises followed by an activity wherein you will create your own geographic workbook from start to finish.

Introduction

In the last chapter, you explored distributions and relationships in a dataset and learned how to identify patterns within a given dataset. This chapter will focus on the geographic aspect of data and how location affects those distributions and relationships.

Understanding geographic patterns is critical for many datasets, whether they are revenue patterns around the world for a global corporation or local purchase patterns for a small business. This type of data is especially useful for explaining patterns to internal or external customers with maps, in which you can show patterns at the region or country level all the way down to postal code or even smaller geographic levels, depending on how the data is collected. This can be highly useful for visualizing purchase, voting, or demographic patterns, as just a few examples.

One of the most powerful aspects of using geographic data and maps lies in the intuitive understanding of location data many users are...

Importing Spatial Data

Before you can use the many capabilities Tableau provides for geographic datasets, it is important to understand the geographic data types that Tableau can utilize. Tableau can ingest geospatial data from many popular formats, including shapefile, GeoJSON, and MapInfo sources. The next section will cover some of the most common spatial formats and how to add them to your workbooks.

Spatial data is unique in how it defines geographic attributes. While typical spreadsheet or database data may contain geographic elements (city, state, country, postal code, and so on), it will not contain additional information about those entities. Most often, you will have a pair of geographic coordinates to work with: latitude and longitude. For common entities such as a country, state, or province, mapping software will recognize the codes and allow the use of choropleth (filled) maps.

Choropleth maps are shapefiles/GeoJSON data sources that not only contain simple latitude...

Importing Non-Spatial Geographic Data Sources

Many geographic data sources are not specifically spatial sources but are instead found in spreadsheet or database formats as part of a larger dataset. These datasets will typically contain non-geographic data, such as customer information, time-period details, and assorted metrics. Geographic features such as country, state, and city will often also be included, making it possible to create maps displaying many data attributes.

Tableau makes it easy to create maps from these sources, although you may need to assist in the process, as you'll see shortly. Since many Tableau data sources will not reside in spatial formats, it is essential to make sure you can use general data sources to display geographic information at the appropriate level of detail.

Importing these sources is no different than the process for any general type of Tableau data. The only difference here is that you require one or more geographic fields to...

Managing Location Data

The key to producing maps and other meaningful geographic analyses is to have the necessary location elements (country, state, city, and so on) and to make sure they are classified correctly in Tableau. In many instances, Tableau will correctly identify these roles, making your job simple. In other cases, you will need to tell Tableau the correct role. This is often the case when your source field names do not correspond to the standard naming conventions used by Tableau. There may also be cases where Tableau incorrectly assumes that a non-geographic field represents location data based on the field name of the dimension, or where a value cannot be automatically identified.

This section will explore the various ways in which geographic data can be created and maintained in Tableau using three primary approaches—assigning roles, editing locations, and building custom geographic levels.

Assigning Geographic Roles

Tableau is quite adept at interpreting...

Creating Maps in Tableau

Tableau provides two distinct map options in the Show Me menu—one for symbol maps and a second for choropleth maps. If your data has simple latitude/longitude values corresponding to a postal code centroid, such as a store location (or even a city), then your mapping will be focused on the symbol map option. If, however, your data has more detailed data based on a shapefile or GeoJSON data source, you can then use the choropleth option to create filled maps based on the polygons in the data source. In some cases, you will have access to both types of source data and will be able to create a dual-axis map, which will be explored later in this section. The following is a simple comparison of the two types, with choropleth (filled) on the left and symbol on the right:

Figure 6.32: A choropleth (filled) map and a symbol map

Geocoding

Geocoding is the process of assigning geographic attributes to a data field that may not be automatically...

Summary

This chapter introduced you to many of the geographic capabilities and methods designers and users can employ in Tableau. The ability to take geographic data and create powerful, attractive maps that integrate with other displays is a critical skill in building visual insights. You learned how Tableau maps can incorporate size, color, shapes, and filtering so users can explore and understand geographic information more thoroughly.

You also learned that while Tableau is not a dedicated mapping platform, it can be used to replicate much of the functionality of traditional mapping and GIS software. Being able to map geographic data is an essential skill in developing complete Tableau solutions for users and can be incorporated into any analysis where geospatial data is available and interacting with external map files can add an additional layer of detail to maps.

In the next chapter, you will be moving into the analysis section of the course with Chapter 7: Analysis : Creating...