Why Scatter plots in Tableau? - Purpose & Use Cases

The Big Idea

What if you could see hidden connections in your data at a glance?

The Scenario

Imagine you have a big list of sales data with numbers for revenue and customer visits. You try to find if more visits mean more sales by writing down numbers on paper or in a simple table.

The Problem

Manually comparing numbers one by one is slow and confusing. You might miss patterns or make mistakes. It's hard to see how two things relate just by looking at rows of numbers.

The Solution

Scatter plots show each data point as a dot on a graph, making it easy to see if two things move together. You can spot trends, clusters, or outliers quickly without guessing.

Before vs After

✗ Before

Revenue | Visits
1000    | 50
1500    | 70
1200    | 55

✓ After

Scatter plot with Visits on X-axis and Revenue on Y-axis showing dots for each record

What It Enables

Scatter plots let you instantly understand relationships between two variables and make smarter decisions based on clear visual patterns.

Real Life Example

A store manager uses a scatter plot to see if more customer visits lead to higher sales, helping decide where to focus marketing efforts.

Key Takeaways

Manual number comparison is slow and error-prone.

Scatter plots visualize relationships clearly and quickly.

They help spot trends and outliers to guide better decisions.

Practice

1. What is the main purpose of a scatter plot in Tableau?

easy

A. To show the relationship between two numeric variables

B. To display the total sales over time

C. To list all categories in a table format

D. To create a pie chart of proportions

Solution

1. Step 1: Understand scatter plot basics and compare options

   A scatter plot displays points representing two numeric values on X and Y axes. Only 'To show the relationship between two numeric variables' describes this core purpose.

2. Final Answer:

   To show the relationship between two numeric variables -> Option A

3. Quick Check:

   Scatter plot = relationship between two numbers [OK]

Hint: Scatter plots always compare two numeric values [OK]

Common Mistakes:

• Confusing scatter plots with line charts
• Thinking scatter plots show totals or categories only
• Assuming scatter plots are for single variable data

2. Which of the following is the correct way to create a scatter plot in Tableau?

easy

A. Drag two dimensions to the Color shelf

B. Drag a dimension to Columns and a measure to Rows

C. Drag one numeric field to Columns and another numeric field to Rows

D. Drag a measure to Filters and a dimension to Tooltip

Solution

1. Step 1: Recall scatter plot setup and evaluate options

   Scatter plots require two numeric fields, one on Columns and one on Rows. Only 'Drag one numeric field to Columns and another numeric field to Rows' creates a scatter plot.

2. Final Answer:

   Drag one numeric field to Columns and another numeric field to Rows -> Option C

3. Quick Check:

   Scatter plot = numeric on Columns and Rows [OK]

Hint: Scatter plots need two numeric fields on axes [OK]

Common Mistakes:

• Using dimensions instead of numeric fields on axes
• Placing fields only on Color or Tooltip shelves
• Trying to create scatter plots with filters only

3. Given a scatter plot with Sales on Columns and Profit on Rows, what does a point far to the right but low on the Y-axis represent?

medium

A. Low sales but high profit

B. Low sales and low profit

C. High profit and high sales

D. High sales but low profit

Solution

1. Step 1: Understand axes and interpret point position

   Columns (X) = Sales (far right = high); Rows (Y) = Profit (low = low). Thus, high sales but low profit.

2. Final Answer:

   High sales but low profit -> Option D

3. Quick Check:

   X=Sales high, Y=Profit low = High sales, low profit [OK]

Hint: Right = high X value, low Y = low Y value [OK]

Common Mistakes:

• Mixing up X and Y axis meanings
• Assuming high sales always means high profit
• Ignoring axis labels when interpreting points

4. You created a scatter plot but all points appear stacked in one corner. What is the most likely cause?

medium

A. One or both fields are dimensions instead of measures

B. Both axes use the same numeric field

C. Color shelf is empty

D. Filters are applied incorrectly

Solution

1. Step 1: Identify requirements and analyze stacking cause

   Scatter plots need numeric measures on axes. Dimensions cause points to stack at same coordinates.

2. Final Answer:

   One or both fields are dimensions instead of measures -> Option A

3. Quick Check:

   Dimensions on axes cause stacked points [OK]

Hint: Axes must have numeric measures, not dimensions [OK]

Common Mistakes:

• Assuming color shelf affects point spread
• Not checking field data types on axes
• Blaming filters without verifying axes

5. You want to analyze customer segments by plotting Annual Income vs Spending Score and color points by Customer Age Group. How should you set up your scatter plot in Tableau?

hard

A. Place Customer Age Group on Filters, Annual Income on Tooltip, Spending Score on Rows

B. Place Annual Income on Columns, Spending Score on Rows, and Customer Age Group on Color

C. Place Spending Score on Columns, Customer Age Group on Rows, and Annual Income on Detail

D. Place Customer Age Group on Columns, Annual Income on Rows, and Spending Score on Color

Solution

1. Step 1: Assign fields correctly for scatter plot with coloring

   Numerics Annual Income (Columns) and Spending Score (Rows) for axes; categorical Customer Age Group on Color for segments.

2. Final Answer:

   Place Annual Income on Columns, Spending Score on Rows, and Customer Age Group on Color -> Option B

3. Quick Check:

   Numeric on axes + category on Color [OK]

Hint: Numeric fields on axes, categories on Color for groups [OK]

Common Mistakes:

• Putting categorical fields on axes instead of Color
• Using Filters instead of Color for grouping
• Mixing up which numeric fields go on Columns or Rows