In our previous article, we dug into the concepts of measures and dimensions in Tableau, shedding light on their key roles in data analysis and visualization. The distinction between discrete and continuous data representation is another key concept in Tableau that needs to be explored. Using blue and green fields, often referred to as “pills” in Tableau, effectively is crucial to maximizing the power of data visualization. We will explore discrete and continuous data representation in this article, as well as how they affect Tableau visualizations.

What are Blue and Green pills?

Depending on whether a field is discrete (blue) or continuous (green), Tableau depicts the data differently in the view.

Blue Pills: Discrete Data

Discrete data only accepts specific values. This type of data, which can be counted and has a finite number of values, is frequently expressed as whole numbers or integers. These values must be able to fit into specific categories and cannot be divided into smaller components.

  • Categorical Data: Values that can be sorted into groups or categories
  • Nominal Data: Values in the form of just labels. Nominal data cannot be ordered or measured, only counted.

E.g. Gender

  • Ordinal Data: Values or observations may be ranked (placed in a certain order) or assigned a rating. Ordinal data can be ordered and counted but not measured.

E.g. Rating scale

Blue Measures and Dimensions

• Are discrete
• Are treated as finite values
• Add headers to the view

Green Pills: Continuous Data

The data can be measured continuously. Any value may be assigned to values or observations over a finite or indefinite interval. These values can have a range of decimal places, allowing for precise measurements and calculations.

E.g.: Height, Weight

Green Measures and Dimensions

  • Are continuous
  • Treated as an infinite range
  • Add axes to the view

Example 1: Let’s create a view to display the crash count by year.

Step 1: First, let’s drag the ‘Crash_Data’ to ‘Rows’. Since it’s a green measure, it will create a green pill (Continuous) and we could see that its aggregated by COUNT (CNT).

Step 2: Then, will add another green dimension (Continuous) ‘Year’ to the ‘Columns’.

A view like below will be displayed and you could see that those measures have added axes to the view.

Example 2: Let’s create a view to display the crash count by Day Week.

Step 1: Let’s drag the ‘Crash_Data’ (Green Pill- Continuous) field to the Rows.

Step 2: Next, we can drag the ‘Day Week’ (Blue Pill-Discrete) field to Columns.

A view like below will be displayed and you could see that Green Pill (CNT Crash_data) has added axis and Blue Pill has added a header to the view.

I hope this blog article help you in understanding the behaviour and nature of Green and Blue pills. Download a sample dataset and play around to see how they behave. It will help you in creating insightful dashboards.

The Data School
Author: The Data School