If you are new to Tableau and confused with the left side of your Tableau canvas, which is divided into two sections, dimensions and measures, this blog will help you understand those concepts.

Understanding blue/green, dimension/measure, discrete/continuous will make you proficient in Tableau. It will boost your confidence and save your time.

Dimensions and Measures

You can see such things on the left side of the canvas. Anything above the line are dimensions (shown with blue icons). Anything below the line are measures which are numeric.

* Dimensions contain qualitative values (names, dates, or geographical data). You can use dimensions to categorize, segment, and reveal the details in your data. In a nutshell, dimensions are the fields from your dataset which gives you descriptive data. For example, “Region” gives you the four regions. South, East, West, and North. Those are descriptive, categorical, and qualitative. Although it’s not descriptive every time, some times it could be numeric as well. Like “Customer ID”, “Year”, and “Row ID”. Keep in mind that we don't want to perform aggregate functions on these numerical fields like count, sum, and min because it doesn't make sense.

* Measures contain numeric, quantitative values that you can measure. They can be aggregated. When you drag a measure into view, Tableau applies an aggregation to that measure.They are followed by a green hashtag. These are green pills.

These are the fields (columns) from your dataset which are numeric and can be aggregated as per the requirement. Like sum, count, distinct count, min, max etc.

## Dimensions and Measures in Canvas

If you drag something from “Dimensions” to “Rows” or “Columns” it will be a blue pill. Similarly, if you drag something from “Measures” to “Rows” or “Columns” it will be an aggregated green pill.

Discrete and Continuous

Discrete data is a numerical type of data that includes whole, concrete numbers with specific and fixed data values determined by counting.

Some discrete data examples are:

The number of customers who bought different items

The number of computers in each department

The number of items you buy at the grocery store each week

Continuous data includes complex numbers and varying data values measured over a particular time interval.

Some continuous data examples include:

The weight of newborn babies

The daily wind speed

The temperature of a freezer

Go to the Measures section, then choose any field. Let’s choose “Sales”. If you right click, there are two options “ convert to dimensions” and “convert to discrete”.

If you choose the option “convert to dimension”, it will go to the dimension section above the line and it will act like a dimension. Which in “Sales” case, makes no sense.

Converting Measures to Discrete

Example: Sales column (field) from Sample superstore dataset

First, you make a copy of “Sales” by right clicking and clicking “duplicate”. Now you can see the sales field followed by a blue hashtag.

I renamed that “Sales(copy)Discrete”. It has the additional “=” sign because it is explicitly created and it was not in the original dataset that is called “Calculated Field”.

Let’s see what will happen when we drag “Sales” to “Rows”. As expected, it displays an axis with the sum of “Sales” as a continuous number which varies from 0 to 2,29,201.

Now let’s drag “Sales(copy)Discrete” to “Rows” and see what happen. It becomes a blue pill and acts as a label or header. It didn't produce an axis.

By converting sales into Discrete, it doesn't change its quantitative property. Just the way it is displayed in canvas.

Now putting all together:

measure→ sales→ aggregated value→ green pill→ continuous→ axis

measure→ sales→ aggregated value→ blue pill→ discrete→ header/label

Convert Dimension to Continuous (Row ID)

If you right click on Row ID, we will see two options, “Convert to Measure” and “Convert to Continuous”. Keep in mind, if the dimension is numeric, then only will you see the option “Convert to Measure”. Now let’s get back to converting “Row ID” to “Continuous”. It’s the same way. Right click, duplicate, convert to continuous. After converting, it’s the same measure. Just the way we want to represent it on the canvas, changes.

Drag and drop “Row ID” to “Rows”.

Let’s see Row ID as dimension, which is a blue pill, produce a header.

Drag and drop Row ID (copy) to row.

Now let’s see Row ID (copy) as dimension which is a green pill.

A green pill will produce an axis and a blue pill will produce a header or label.

Discrete (measure or dimensions) will produce column /header/label.

Continuous (measure or dimensions) will produce an axis.

Let’s see one example of both in one visualization.

For Order Date from dimensions

To understand these concepts, you have to experiment with the fields. Try different combinations. For the summary, I created this diagram.