Tag Archives: mapping

Maps in Tableau

Making Maps with Tableau

Tableau LogoOne of the attractive features of Tableau for visualization is that it can produce maps in addition to standard charts and graphs. While Tableau is far from being a full-fledged GIS application, it continues to expand its mapping capabilities, making it a useful option to show where something is located or to show how indicators are spatially distributed.

Here, we’re going to go over a few of the Tableau’s mapping capabilities. We’ve recorded a workshop with examples relating to this blog post’s discussion:

For a more general introduction to Tableau (including some mapping examples), you should check out one of these other past CDVS workshops:

Concepts to Keep in Mind

Tableau is a visualization tool: Tableau can quickly and effectively visualize your data, but it will not do specialized statistical or spatial analysis.

Tableau makes it easy to import data:  A big advantage of Tableau is the simplicity of tasks such as changing variable definitions between numeric, string, and date, or filtering out unneeded columns. You can easily do this at the time you connect to the data (“connect” is Tableau’s term for importing data into the program).

Tableau is quite limited for displaying multiple data layers: Tableau wants to display one layer, so you need to use join techniques to connect multiple tables or layers together. You can join data tables based on common attribute values, but to overlay two geographic layers (stack them), you must spatially join one layer to one other layer based on their common location.

Tableau uses a concept that it calls a “dual-axis” map to allow two indicators to display on the same map or to overlay two spatial layers. If, however, you do need to overlay a lot of data on the same map, consider using proper GIS software.

Dual-Axis map
Overlay spatial files using dual-axis maps

Displaying paths on a map requires a special data structure:  In order for tabular data with coordinate values (latitude/longitude) to display as lines on a map, you need to include a field that indicates drawing order. Tableau constructs the lines like connect-the-dots, each row of data being a dot, and the drawing order indicating how the dots are connected.

Using drawing order to create lines from points

You might use this, for instance, with hurricane tracking data, each row representing measurements and location collected sequentially at different times. The illustration above shows Paris metro lines with the station symbol diameter indicating passenger volume. See how to do this in Tableau’s tutorial.

You can take advantage of Tableau’s built-in geographies: Tableau has many built-in geographies (e.g., counties, states, countries), making it easy to plot tabular data that has an attribute with values for these geographic locations, even if you don’t have latitude/longitude coordinates or geographic files — Tableau will look up the places for you!  (It won’t, however, look up addresses.)

Tableau also has several built-in base maps available for your background.

Tableau uses the “Web Mercator” projection: This is the same as Google Earth/Maps. Small-scale maps (i.e., large area of coverage) may look stretched out in an unattractive way since it greatly exaggerates the size of areas near the poles.

Useful Mapping Capabilities

Plot points: Tableau works really well for plotting coordinate data (Longitude (X) and Latitude (Y) values) as points.  The coordinates must have values in decimal degrees with negative longitudes being east of Greenwich and negative latitudes being south of the equator.

Points with time slider
Point data with time slider

Time slider: If you move a categorical “Dimension” variable onto Tableau’s Pages Card, you can get a value-based slider to filter your data by that variable’s values (date, for instance, as in Google Earth). This is shown in the image above.

Heatmap of point distribution: You can choose Tableau’s “Density” option on its Marks card to create a heatmap, which may display the concentration of your data locations in a smoother manner.

Filter a map’s features: Tableau’s Filter card is akin to ArcGIS’s Definition Query, to allow you to look at just a subset of the features in a data table.

Shade polygons to reflect attribute values: Choropleth maps (polygons shaded to represent values of a variable) are easy to make in Tableau. Generally, you’ll have a field with values that match a built-in geography, like countries of the world or US counties.  But you can also connect to spatial files (e.g., Esri shapefiles or GeoJSON files), which is especially helpful if the geography isn’t built into Tableau (US Census Tracts are an example).

Choropleth Map
Filled map using color to indicate values

Display multiple indicators: Visualizing two variables on the same map is always problematic because the data patterns often get hidden in the confusion, but it is possible in Tableau.  Use the “dual-axis” map concept mentioned above.  An example might be pies for one categorical variable (with slices representing the categories) on top of choropleth polygons that visualize a continuous numeric variable.

Multiple variables
Two variables using filled polygons and pies

Draw lines from tabular data: Tableau can display lines if your data is structured right, as discussed and illustrated previously, with a field for drawing order. You could also connect to a spatial line file, such as a shapefile or a GeoJSON file.

Help Resources

We’ve just given an overview of some of Tableau’s capabilities regarding spatial data. The developers are adding features in this area all the time, so stay tuned!

Telling Stories with Maps: Esri Story Maps at Duke

Developing interactive maps that incorporate text, images, video, and audio can be time-consuming and require specialized technical skills. Fortunately, at Duke we have access to Esri Story Maps, a web-based tool that helps you quickly design engaging narratives around your maps, no coding required.

We have seen a variety of creative uses of Story Maps at Duke, including:

  • Presentations to communicate research
  • Student assignments, as an alternative to a midterm or paper
  • Tours and guides of campus
  • Tutorials to explain a topic with a spatial component
  • Portfolios to showcase projects that include maps

Krakow Story MapChristine Liu, a graduate student in the Department of Art, Art History & Visual Studies, created this Story Map to illustrate a journey through Kraków under Nazi occupation.

If you are interested in building a Story Map, we recommend first spending some time exploring Esri’s curated gallery of stories to find inspiration and understand the platform’s capabilities. You can also review their collection of resources, which includes training videos, FAQs, and useful advice.

When you are ready to get started,  you can contact one of our GIS specialists (by emailing askdata@duke.edu) to schedule an appointment. We are always happy to answer questions and provide recommendations specific to your project. We also offer workshops to guide you through the process of building a basic online map, making it visually effective, and combining it with other materials to publish a Story Map.

If you already have a Story Map you want to show off, please share it with us! We are assembling a gallery of stories made at Duke and would love to feature your project.

DVS Fall Workshops

GenericWorkshops-01Data and Visualization Services is happy to announce its Fall 2015 Workshop Series.  With a range of workshops covering basic data skills to data visualization, we have a wide range of courses for different interests and skill levels..  New (and redesigned) workshops include:

  • OpenRefine: Data Mining and Transformations, Text Normalization
  • Historical GIS
  • Advanced Excel for Data Projects
  • Analysis with R
  • Webscraping and Gathering Data from Websites

Workshop descriptions and registration information are available at:





OpenRefine: Data Mining and Transformations, Text Normalization
Sep 9
Basic Data Cleaning and Analysis for Data Tables
Sep 15
Introduction to ArcGIS
Sep 16
Easy Interactive Charts and Maps with Tableau
Sep 18
Introduction to Stata
Sep 22
Historical GIS
Sep 23
Advanced Excel for Data Projects
Sep 28
Easy Interactive Charts and Maps with Tableau
Sep 29
Analysis with R
Sep 30
ArcGIS Online
Oct 1
Web Scraping and Gathering Data from Websites
Oct 2
Advanced Excel for Data Projects
Oct 6
Basic Data Cleaning and Analysis for Data Tables
Oct 7
Introduction to Stata
Oct 14
Introduction to ArcGIS
Oct 15
OpenRefine: Data Mining and Transformations, Text Normalization
Oct 20
Analysis with R
Oct 20


New Year- New Data and Visualization Lab!

Data and Visualization Services is happy to announce our new Data and Visualization Lab in Duke Libraries new Edge research space.  Located on the first floor of the Bostock Library, the Brandaleone Family Lab for Data and Visualization Services offers a dedicated space for researchers working on data driven projects.

The lab features three distinct areas for supporting data driven research.

Data and Visualization Lab Space

Data and Visualization Lab Computing Zone

Our lab space features twelve high end workstations with dual monitors with the latest software for data visualization, digital mapping, statistics, and qualitative research.  All of the machines have two dedicated displays to encourage collaborative work and data consultations.  Additionally, all twelve machines have a dedicated power port located conveniently under the edge of the table for powering a laptop or usb powered device.

Bloomberg Professional “Bar”


Since the launch of our Bloomberg terminals, we have seen a steady increase in both individual and team based usage of Bloomberg financial data.  Our three Bloomberg Professional workstations are now located on a dedicated “bar” across from our lab machines.  The  new Bloomberg zone will facilitate collaborate work and provide a base for groups such as the Duke University Investment Club and Duke Financial Economics Center.

Consult and Collaborative SpaceCollaboration Zone

Our third lab space provides a set of four rolling tables for small groups to collaborate or for projects that don’t require a fixed computing space.   An 85″ flat panel display near this zone features data visualizations and other data driven research projects at Duke.

Come See Us!

With ample natural light,  almost 24/7 availability, and a welcoming staff eager to work with you on your next data driven project.  We look forward to working with you in the upcoming year!