Symbol maps in Tableau - Deep Dive

Overview - Symbol maps

What is it?

Symbol maps are a type of map visualization in Tableau that use symbols like circles or shapes to represent data points on a geographic map. Each symbol's size, color, or shape can show different data values, helping you see patterns across locations. They make it easy to compare data across places like cities, states, or countries visually. Symbol maps are great for showing where things happen and how much or how often.

Why it matters

Without symbol maps, it would be hard to quickly understand how data changes across different locations. They solve the problem of making complex geographic data easy to see and compare at a glance. This helps businesses make better decisions, like where to open a new store or how sales vary by region. Without symbol maps, you might miss important location-based trends that affect your results.

Where it fits

Before learning symbol maps, you should understand basic Tableau concepts like connecting data, creating simple charts, and using geographic fields. After mastering symbol maps, you can explore more advanced map types like filled maps, density maps, and custom geocoding. Symbol maps fit into the broader journey of visualizing data geographically and telling stories with location data.

Mental Model

Core Idea

Symbol maps place data points on a map using symbols whose size or color shows the data’s value at each location.

Think of it like...

It’s like putting pins on a world map where each pin’s size or color tells you how important or big something is at that spot, like marking your friends’ houses with different-sized stickers based on how often you visit.

┌───────────────┐
│   Map Base    │
│  (Geography)  │
│               │
│  ●   ●   ●    │  ← Symbols sized or colored by data
│   ●      ●    │
│      ●        │
└───────────────┘

Build-Up - 7 Steps

1

Foundation

Understanding Geographic Data Basics

Concept: Learn what geographic data is and how Tableau recognizes locations.

Geographic data includes things like countries, states, cities, or coordinates (latitude and longitude). Tableau automatically detects geographic fields if your data has these names or coordinates. This lets Tableau place data points on a map without extra setup.

Result

You can identify geographic fields in your data and know Tableau will use them to create maps.

Knowing how Tableau recognizes geographic data is key to building any map visualization, including symbol maps.

2

Foundation

Creating Your First Symbol Map

Concept: Build a simple symbol map by placing geographic fields and adding data to size or color.

Drag a geographic field like 'City' or 'State' to the Rows or Columns shelf or directly to the canvas. Tableau will create a map with points for each location. Then drag a measure like 'Sales' to Size or Color on the Marks card to show data differences with symbol size or color.

Result

A map appears with symbols representing each location, sized or colored by the data measure.

Seeing data on a map with symbols helps you quickly spot where values are high or low geographically.

3

Intermediate

Using Multiple Data Attributes on Symbols

🤔Before reading on: Do you think you can show two different data values on the same symbol map, like size and color? Commit to your answer.

Concept: Learn to use both size and color on symbols to represent two data measures simultaneously.

On the Marks card, drag one measure to Size to control the symbol size, and drag another measure to Color to control the symbol color. For example, size could show sales volume, and color could show profit margin. This dual encoding gives richer insights.

Result

Symbols vary in size and color, showing two data dimensions on the same map.

Using size and color together lets you compare two data points per location, making the map more informative.

4

Intermediate

Customizing Symbol Appearance

🤔Before reading on: Do you think changing symbol shapes or colors can affect how easy the map is to understand? Commit to your answer.

Concept: Explore changing symbol shapes, colors, and transparency to improve map clarity and storytelling.

In the Marks card, you can change the symbol shape from circles to squares or custom shapes. Adjust colors to use meaningful palettes (like red for low, green for high). You can also set transparency to avoid clutter when symbols overlap. These tweaks help make the map clearer and more attractive.

Result

A visually clearer symbol map that communicates data better.

Customizing symbols improves how viewers interpret the map and prevents confusion from overlapping or unclear symbols.

5

Intermediate

Handling Overlapping Symbols and Clutter

Concept: Learn techniques to reduce symbol overlap and make crowded maps readable.

When many data points are close, symbols can overlap and hide information. You can reduce symbol size, add transparency, or use filters to show fewer points. Another option is to use clustering or zoom controls to focus on areas of interest.

Result

A less cluttered map where symbols remain distinct and data is easier to read.

Managing symbol overlap is crucial for accurate interpretation and avoids misleading viewers.

6

Advanced

Using Latitude and Longitude for Precise Placement

🤔Before reading on: Can you place symbols exactly where you want on a map using coordinates instead of names? Commit to your answer.

Concept: Use latitude and longitude fields to place symbols precisely on the map, beyond named locations.

If your data has latitude and longitude columns, drag them to Rows and Columns shelves respectively. Tableau plots symbols exactly at those coordinates. This is useful for custom locations like store addresses or event spots not recognized by name.

Result

Symbols appear exactly where coordinates specify, allowing detailed geographic analysis.

Using coordinates gives you full control over symbol placement, essential for detailed or custom maps.

7

Expert

Optimizing Symbol Maps for Performance and Usability

🤔Before reading on: Do you think large datasets with many symbols can slow down Tableau or confuse users? Commit to your answer.

Concept: Learn best practices to keep symbol maps fast and user-friendly with large or complex data.

Large datasets with thousands of symbols can slow rendering and overwhelm users. Use data aggregation, filters, or sampling to reduce points. Also, use tooltips and interactivity like zoom or highlight actions to help users explore data without clutter. Optimize color palettes for colorblind accessibility.

Result

A responsive, clear symbol map that works well even with big data.

Balancing detail and performance ensures symbol maps remain practical and insightful in real-world use.

Under the Hood

Tableau uses geographic fields or coordinates to plot points on a map projection. Each data point becomes a symbol whose size, color, or shape is controlled by data measures. Tableau renders these symbols as vector graphics layered on map tiles or backgrounds. The map projection translates geographic coordinates into screen positions. Symbol attributes are dynamically calculated based on data and user settings.

Why designed this way?

Symbol maps were designed to combine geographic context with quantitative data visually. Using symbols allows flexible encoding of multiple data dimensions (size, color, shape) on a single map. This approach balances clarity and detail, letting users spot patterns without overwhelming them. Alternatives like filled maps show areas but lose point-level detail, so symbol maps fill that gap.

┌───────────────┐
│ Geographic    │
│ Data Input    │
└──────┬────────┘
       │
┌──────▼────────┐
│ Map Projection│
│ (Coordinates) │
└──────┬────────┘
       │
┌──────▼────────┐
│ Symbol Layer  │
│ (Size, Color) │
└──────┬────────┘
       │
┌──────▼────────┐
│ Rendered Map  │
│ Visualization │
└───────────────┘

Myth Busters - 4 Common Misconceptions

Quick: Do you think symbol size always represents the exact data value proportionally? Commit to yes or no.

Common Belief: Symbol size on maps always shows data values exactly proportional to their size.

Reality: Tableau scales symbol sizes for visibility and may not keep exact proportionality to data values, especially with very large or small numbers.

Why it matters: Assuming exact proportionality can lead to misinterpretation of data differences, causing wrong conclusions about magnitude.

Quick: Do you think symbol maps can show data for locations Tableau does not recognize? Commit to yes or no.

Common Belief: Symbol maps can automatically plot any location name without extra setup.

Reality: Tableau only recognizes standard geographic names or coordinates; unknown or misspelled locations won’t plot unless fixed or custom geocoding is used.

Why it matters: Missing or incorrect locations cause incomplete maps and misleading analysis if not addressed.

Quick: Do you think adding too many symbols on a map always improves insight? Commit to yes or no.

Common Belief: More symbols on a map always mean better and more detailed insights.

Reality: Too many symbols cause clutter and overlap, making the map confusing and hiding important patterns.

Why it matters: Ignoring clutter leads to poor user experience and misinterpretation of data.

Quick: Do you think symbol maps are always the best choice for geographic data visualization? Commit to yes or no.

Common Belief: Symbol maps are the best way to show all geographic data types.

Reality: Symbol maps are best for point data; for area-based data, filled maps or heat maps may be better choices.

Why it matters: Choosing the wrong map type can hide key insights or misrepresent data.

Expert Zone

1

Symbol size scaling in Tableau uses a nonlinear approach to keep symbols visible but can distort perceived differences; experts adjust size ranges carefully.

2

Custom shapes can be imported to represent categories, but they must be designed with consistent sizing and clarity to avoid confusion.

3

Using dual-axis maps to overlay symbol maps with other map types (like filled maps) allows richer storytelling but requires careful synchronization of axes.

When NOT to use

Avoid symbol maps when your data represents areas or regions better shown with filled maps or when data density causes excessive overlap; use filled maps, heat maps, or density maps instead.

Production Patterns

Professionals use symbol maps for sales territories, store locations, or event tracking, often combining them with filters and dashboard actions for interactive exploration. They optimize symbol size and color for accessibility and performance, and sometimes layer symbol maps over custom map backgrounds for branding.

Connections

Heat maps

Alternative geographic visualization

Understanding symbol maps helps grasp heat maps, which show data density with color gradients instead of discrete symbols.

Data storytelling

Builds-on

Symbol maps are powerful tools in data storytelling, helping narrate location-based insights visually and engagingly.

Cartography

Shares principles

Symbol maps apply cartographic principles like symbol scaling and map projections, linking BI visualization to traditional map-making science.

Common Pitfalls

#1 Using default symbol sizes without adjustment causes some symbols to be too big or too small, hiding data differences.

Wrong approach:

Drag measure to Size and accept default size range without changes.

Correct approach:

Adjust size slider on Marks card to balance symbol visibility and proportionality.

Root cause:

Assuming Tableau’s default size settings fit all data scales leads to poor symbol representation.

#2 Plotting location names with typos or non-standard names results in missing symbols on the map.

Wrong approach:

Use raw location names from data without cleaning or verifying.

Correct approach:

Clean data or use custom geocoding to fix or add missing locations.

Root cause:

Not validating geographic data causes Tableau to fail recognizing locations.

#3 Adding too many symbols without filtering or clustering creates clutter and unreadable maps.

Wrong approach:

Plot all data points regardless of density or map scale.

Correct approach:

Use filters, aggregation, or zoom to reduce symbol count and improve clarity.

Root cause:

Ignoring map readability and user experience when handling large datasets.

Key Takeaways

Symbol maps use symbols placed on geographic locations to visually represent data values through size, color, or shape.

They help reveal spatial patterns and differences that are hard to see in tables or simple charts.

Proper data preparation and symbol customization are essential to create clear, accurate, and insightful symbol maps.

Managing symbol overlap and performance is critical when working with large or dense geographic datasets.

Choosing the right map type depends on your data and the story you want to tell; symbol maps excel with point data.