Size encoding in Tableau - Dashboard Guide

Dashboard Mode - Size encoding

Dashboard Goal

Understand how sales amount varies by product category and region using size encoding to show sales volume differences visually.

Sample Data

Region	Product Category	Sales Amount	Units Sold
East	Furniture	5000	50
East	Technology	12000	30
West	Furniture	7000	70
West	Office Supplies	3000	100
Central	Technology	9000	45
Central	Office Supplies	4000	80

Dashboard Components

• KPI Card: Total Sales calculated as SUM([Sales Amount]). Displays total sales of 40,000.
• Bubble Chart: Shows Product Category on X-axis and Region on Y-axis. Bubble size encodes SUM([Sales Amount]). Larger bubbles mean higher sales. Color differentiates product categories.
• Bar Chart: Displays Units Sold by Region. Uses SUM([Units Sold]) for bar height.

Dashboard Layout

+----------------------+----------------------+
|      KPI Card        |    Bubble Chart      |
|  (Total Sales)       |  (Size encodes sales)|
+----------------------+----------------------+
|                      Bar Chart (Units Sold)  |
|                      by Region               |
+---------------------------------------------+

Interactivity

A filter for Region allows users to select one or multiple regions. When applied, the KPI card updates total sales for selected regions, the bubble chart resizes bubbles accordingly, and the bar chart shows units sold only for those regions.

Self Check

If you add a filter to select only the East region, which components update and how?

• KPI Card: Updates to show total sales of 17,000 (5000 + 12000).
• Bubble Chart: Shows bubbles only for East region categories with sizes reflecting sales amounts (Furniture smaller than Technology).
• Bar Chart: Displays units sold only for East region (total 80).

Key Result

Dashboard showing sales volume differences by product category and region using size encoding in a bubble chart, with total sales KPI and units sold bar chart.

Practice

1. What is the main purpose of size encoding in Tableau visualizations?

easy

A. To sort data in ascending or descending order

B. To change the color of marks based on categories

C. To filter data points from the view

D. To change the size of marks based on data values

Solution

1. Step 1: Understand size encoding concept

   Size encoding adjusts the size of visual marks to represent numeric data values visually.

2. Step 2: Compare options with concept

   Only To change the size of marks based on data values describes changing mark size based on data values, which matches size encoding.

3. Final Answer:

   To change the size of marks based on data values -> Option D

4. Quick Check:

   Size encoding = mark size by data [OK]

Hint: Size encoding changes mark size to show data amounts [OK]

Common Mistakes:

• Confusing size encoding with color encoding
• Thinking size encoding filters data
• Assuming size encoding sorts data

2. Which of the following is the correct way to apply size encoding in Tableau?

easy

A. Drag a measure field to the Color shelf

B. Drag a dimension field to the Size shelf

C. Drag a measure field to the Size shelf

D. Drag a dimension field to the Filters shelf

Solution

1. Step 1: Identify what type of field size encoding uses

   Size encoding requires numeric data, so it uses measure fields.

2. Step 2: Match correct shelf for size encoding

   Size shelf controls mark size, so dragging a measure field there is correct.

3. Final Answer:

   Drag a measure field to the Size shelf -> Option C

4. Quick Check:

   Size shelf + measure field = correct size encoding [OK]

Hint: Size encoding needs numeric (measure) fields on Size shelf [OK]

Common Mistakes:

• Using dimension fields instead of measures
• Dragging fields to Color shelf instead of Size
• Confusing Filters shelf with Size shelf

3. Given a bar chart with sales amounts encoded by size, what happens if you increase the size range in Tableau's Size legend?

medium

A. Bars with higher sales become noticeably larger compared to smaller sales bars

B. All bars become uniformly larger regardless of sales

C. Bars change color instead of size

D. The chart filters out smaller sales bars

Solution

1. Step 1: Understand effect of increasing size range

   Increasing size range makes size differences more pronounced between small and large values.

2. Step 2: Analyze impact on bars

   Bars with higher sales grow larger relative to smaller sales bars, enhancing visual comparison.

3. Final Answer:

   Bars with higher sales become noticeably larger compared to smaller sales bars -> Option A

4. Quick Check:

   Increase size range = bigger size difference [OK]

Hint: Larger size range exaggerates size differences [OK]

Common Mistakes:

• Thinking all bars grow equally
• Confusing size changes with color changes
• Assuming filtering happens automatically

4. You applied size encoding to a measure but notice all marks are the same size. What is the most likely cause?

medium

A. The measure has the same value for all data points

B. You dragged a dimension field to the Size shelf

C. The color legend is overriding size encoding

D. The data source is disconnected

Solution

1. Step 1: Check measure values for size encoding

   If all measure values are identical, size encoding cannot differentiate mark sizes.

2. Step 2: Evaluate other options

   Dragging dimension to Size shelf would cause error, color legend does not override size, and disconnected data prevents any marks.

3. Final Answer:

   The measure has the same value for all data points -> Option A

4. Quick Check:

   Same measure values = same mark size [OK]

Hint: Check if measure values vary to see size differences [OK]

Common Mistakes:

• Assuming dimension fields work for size encoding
• Thinking color affects size encoding directly
• Ignoring data connection status

5. You want to create a scatter plot where the size of each point shows the total sales per region, but some points appear too small to see. What is the best way to improve size encoding clarity?

hard

A. Remove size encoding and use color encoding instead

B. Increase the maximum size in the Size legend and use a logarithmic scale for sales

C. Filter out regions with small sales values

D. Use a dimension field on the Size shelf instead of sales

Solution

1. Step 1: Address small point visibility

   Increasing maximum size makes larger points bigger and more visible.

2. Step 2: Use logarithmic scale for better size distribution

   Log scale reduces skew from very large sales, improving size differences for smaller points.

3. Final Answer:

   Increase the maximum size in the Size legend and use a logarithmic scale for sales -> Option B

4. Quick Check:

   Max size + log scale = clearer size differences [OK]

Hint: Use max size and log scale to fix tiny marks [OK]

Common Mistakes:

• Removing size encoding loses visual comparison
• Filtering data hides information unnecessarily
• Using dimension fields for size causes errors