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  • Book Overview & Buying Visual Analytics with Tableau
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Visual Analytics with Tableau

Visual Analytics with Tableau

By : Alexander Loth
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Visual Analytics with Tableau

Visual Analytics with Tableau

By: Alexander Loth

Overview of this book

Tableau is a popular data visualization tool that’s easy for individual desktop use as well as enterprise. Used by financial analysts, marketers, statisticians, business and sales leadership, and many other job roles to present data visually for easy understanding, it’s no surprise that Tableau is an essential tool in our data-driven economy. Visual Analytics with Tableau is a complete journey in Tableau visualization for a non-technical business user. You can start from zero, connect your first data, and get right into creating and publishing awesome visualizations and insightful dashboards. The book starts with an overview of Tableau, enabling you to grasp the tool’s capabilities and functions. Next, you’ll build assorted types of data visualizations in Tableau, and learn how to perform table calculations in detail. Moving ahead, you’ll work with maps, forecasts, clusters, trend lines, and learn to integrate R, Python, and MATLAB for more advanced statistical modeling. Towards the end, you’ll create interactive dashboards and share your work with others on Tableau Server, Tableau Online, and Tableau Public.
Table of Contents (16 chapters)
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1
Cover
2
Foreword by Nate Vogel
3
Foreword by Sophie Sparkes
15
Index
16
End User License Agreement

Chapter 6
Maps

From subway networks to weather forecasts to tourist guides, we are used to seeing maps conveying geographic information. When you want to display geographic data, you can utilize this familiarity to draw the end user into your data visualization. Furthermore, maps also help you see regional patterns that might be difficult to spot in a table.

Three basic map types in Tableau can be used to display geographic data in map form: symbol maps, filled maps, and density maps. With symbol maps, specific geographic locations are marked with circles, squares, or custom shapes. The form, size, or color of these marks can vary according to a measure or dimension.

With filled maps, also called choropleth maps, geographic areas are shaded according to a measure or dimension.

With density maps, also called heatmaps, areas of relative concentration are colored intensely, while those with sparse occurrences of the dimension in question are colored lightly. They are a good alternative to...

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Visual Analytics with Tableau
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