Logical Functions in Tableau: IF and CASE statements

“If you apply yourself, you can do anything.” “If the number is equal to 8, I win the game!” Conditional statements are part of everyday life. We use them on a regular basis to determine a course of action based on a logical evaluation:

• Do I apply myself (TRUE/FALSE)? In that case, I can do anything.
• Is the number = 8? If so, I win the game.

In Tableau, you can apply conditional logic to emulate the same logic you use on a daily basis. Tableau provides a series of logical functions that make it easy to conditionally transform the data based on a logical evaluation, either a boolean expression (TRUE/FALSE) or an exact value match. In this article, we'll explore some of the most common conditional statements in Tableau and show how you can use them to analyze and visualize data.

Tableau IF Statements

The IF statement is a basic conditional statement in Tableau allowing users to evaluate a boolean expression and return a value if the condition is true, and another if it's false. The basic syntax of the IF statement is:

IF [condition] THEN [value1] ELSE [value2] END

If the final result depends on the evaluation of an alternate boolean expression, you can plug an ELSEIF clause into the statement like this:

IF [condition1] THEN [value1]

  ELSEIF [condition2] THEN [value2]

  ELSE [value3]

END

For instance, to identify pop v. non-pop music genres based on whether ‘pop’ is contained in the name, we can use the following IF statement:

IF CONTAINS([Top Genre], 'pop') THEN 'pop'

  ELSE 'other genre'

END

Nested IF statements

IF statements can also be nested to create more complex conditions and evaluate multiple conditions for subgroups of your data. To build nested IF statements, use the following syntax:

IF [condition1] THEN 

    IF [condition2] THEN [value1] 

      ELSE [value2] 

    END

  ELSE [value3] 

END

Let’s say that we’re interested in figuring out what proportion of pop songs are danceable (per the danceability measure defined in the Spotify Music Dataset). We can use the following nested IF statement to figure it out:

IF CONTAINS([Top Genre], 'pop') THEN

      IF [Dnce] > 66 THEN 'danceable pop' // 66 is the median

      ELSE 'less danceable pop'

    END

  ELSE 'not pop'

END

Nested IF statements are powerful functions, especially when multiple conditions need to be met for different subgroups of the data.

IIF Statements

The IIF function is another conditional statement in Tableau that allows users to test a condition and return one of two values. The syntax of the IIF function is:

IIF([condition], [value if true], [value if false])

For example, to create a calculated field that identifies songwriters who produced a song that was a top hit between 2017 and 2019, we can use the following IIF function:

IIF([Year] >= 2017 AND [Year] <= 2019, '2017-2019 Top Song', 'Not Top Song in 2017-2019')

This will return “2017-2019 Top Song” if the song was a top hit between 2017 and 2019 (as measured by Billboard) and “Not Top Song in 2017-2019” otherwise.

Using Tableau Aggregation Functions with IF

Tableau offers a wide range of built-in functions that can be used in conjunction with conditional statements to perform more advanced calculations. Some of the most commonly used aggregation functions include COUNTD, SUM, AVG, MIN, and MAX. With aggregate functions, you can summarize insights in an effective way by building new metrics in Tableau. You’ll need to use the following syntax:

<Aggregation>(IF [Condition] THEN [value] END)

For example, let's count the number of unique artists with a top hit between 2017 and 2019 with the COUNTD function:

COUNTD(IF [Year] >= 2017 and [Year] <= 2019 THEN [Artist] END)

The statement above will return the distinct number of artists who had a hit between 2017 and 2019. If an artist had multiple hits in those years, the artist's name will only be counted once.

Similarly, we can use the SUM and AVG functions in combination with a conditional statement to perform calculations on specific subsets of data.

A word of advice: be sure to wrap the condition inside of the aggregation. If you don’t, you’ll get the infamous “Cannot mix aggregate and non aggregate comparisons or results in 'IF' expressions.” For instance, the statement below gives an error because we are trying to perform an aggregation on a single datapoint, which itself is not aggregated.

Tableau CASE Statements

Introduction

The CASE statement is another conditional statement in Tableau that allows users to perform multiple tests on a single field and return different values based on the results. Unlike IF statements, which rely on the evaluation of a boolean expression, CASE statements rely on exact value matches. If the WHEN clause uses boolean logic, you'll get the following error in Tableau:

The syntax of the CASE statement is:

CASE [expression]

     WHEN [value1] THEN [result1]

     WHEN [value2] THEN [result2]

     ELSE [default result]

END

For example, let's rewrite the logic to identify songwriters who produced a song that was a top hit between 2017 and 2019:

CASE [Year]

  WHEN IN (2017, 2018, 2019) THEN '2017-2019 Top Songs'

  ELSE 'Not Top Song in 2017-2019'

END

In the case above, we use the WHEN IN construction to list out the years of interest (2017, 2018, and 2019). Tableau then uses the set to find an exact match in the data. If no matching data is found, and no default value is specified, a null value is returned. 

Nested CASE Statements

Similar to nested IF statements, you can use nested CASE statements in Tableau to surface complex logic using a calculated field. You can use the syntax below to return nested logic with CASE statements:

CASE [expression1]

  WHEN [value1] THEN

    (CASE [expression2]

       WHEN [value2] THEN [result1]

       WHEN [value3] THEN [result2]

…

       ELSE [default result]

     END)

  WHEN [value4] THEN

    (CASE [expression2]

       WHEN [value5] THEN [result3]

       WHEN [value6] THEN [result4]

…

       ELSE [default result]

     END)

  ELSE [default result]

END

While CASE statements cannot evaluate boolean expressions and don't work to identify complex patterns in the data, they are easier to read and perform better than IF statements. If the data is simple enough to transform and does not need complex TRUE/FALSE evaluations, you're better off using a CASE statement. In some cases, you can use IF and CASE statements together for even more powerful analyses.

Conclusion

Conditional statements, like IF and CASE statements, are effective instruments to level up your Tableau skills as a data practitioner. To go from "zero-to-hero" with Tableau, be sure to check out our resources, like the Data Analyst in Tableau career track or the Analyzing Data in Tableau course.

Once you have a good foundation, practice visualization in Tableau using the datasets available on DataLab.  IF, IIF, and CASE WHEN statements will be second nature to you. Good luck!