Tableau Calculations¶

Tableau offers multiple calculation types that operate at different levels of granularity. Understanding when to use each type is essential for building accurate and performant dashboards.

Key Facts¶

Six calculation types: row-level, aggregated, quick table calculations, table calculations, window calculations, LOD
Row-level calculations run per row; aggregated require aggregation functions
Table calculations compute over values visible in the current view
Window calculations are a sub-type of table calculations that operate over a window of visible values
Quick table calculations are wrappers around window functions applied in 2 clicks
Parameters are user-controlled variables that modify dashboard behavior

Patterns¶

Calculation Types Overview¶

Type	Description	Example
Row-level	Per row (observation)	`[Price] * [Quantity]`
Aggregated	Uses aggregation function	`SUM([Sales]) / COUNT([Orders])`
Quick Table Calc	Built-in table calcs (2 clicks)	Running Total, Percent of Total
Table Calculation	Custom formula over visible values	`INDEX()`, `RANK()`, `LOOKUP()`
Window Calculation	Over window of visible values	`WINDOW_AVG(SUM([Sales]), -2, 0)`
LOD	At specified granularity	`{FIXED [Customer] : SUM([Sales])}`

Date Functions¶

DATEPART('month', [Order Date])    -- extracts integer (3 for March)
DATETRUNC('month', [Order Date])   -- returns first date of period (2023-03-01)
DATEDIFF('day', [Order Date], TODAY())  -- difference between dates
DATENAME('weekday', [Order Date])  -- returns string ("Monday")

Note: Tableau wraps DATETRUNC in DATEBAR by default. Choose "exact date" from field dropdown to see actual date.

String Functions¶

SPLIT([Product Name], '-', 1)      -- split by delimiter, first part
FIND([String], 'word')             -- position of substring
REPLACE([String], 'old', 'new')    -- replace substring
CONTAINS([String], 'word')         -- true/false
STARTSWITH([Category], 'word')     -- true/false (faster than CONTAINS)
REGEXP_MATCH / REGEXP_EXTRACT / REGEXP_REPLACE  -- regex

Performance tip: STARTSWITH is faster than CONTAINS when possible.

Aggregated Calculations¶

SUM([Sales])
AVG([Profit])
MEDIAN([Revenue])
COUNTD([User ID])               -- count distinct
ATTR([Region])                  -- checks if unique; marks * if multiple values
SUM([Revenue] - [Cost]) / SUM([Revenue])  -- margin calculation

Table Calculations¶

Indexing and ranking:

INDEX()                -- row number within partition (1, 2, 3...)
FIRST()                -- offset from first row (0 for first)
LAST()                 -- offset from last row (0 for last)
RANK(expression)       -- rank by value
RANK_UNIQUE(), RANK_DENSE(), RANK_PERCENTILE()

Running totals:

RUNNING_SUM(SUM([Sales]))
RUNNING_AVG(SUM([Profit]))
RUNNING_MAX(SUM([Revenue]))

Lookup and reference:

LOOKUP(SUM([Sales]), -1)       -- value from 1 row earlier
LOOKUP(SUM([Sales]), FIRST())  -- value from first row in partition
PREVIOUS_VALUE(0)              -- previous value or 0 if none

Partition and Address: "Compute Using" settings define which dimension to address (calculate along) and which to partition (reset the calculation).

Window Calculations¶

WINDOW_SUM(SUM([Sales]), -2, 0)    -- rolling 3-period sum
WINDOW_AVG(SUM([Sales]), -2, 0)    -- rolling 3-period average
WINDOW_MAX(SUM([Profit]))           -- max in entire window
WINDOW_MIN(SUM([Profit]))           -- min in entire window
WINDOW_STDEV(SUM([Sales]))         -- std deviation

Offsets: FIRST() = beginning, LAST() = end, 0 = current row. Second and third params are relative start and end.

Quick Table Calculations¶

Applied via right-click measure on shelf -> Quick Table Calculation:

Function	Description
Running Total	Cumulative sum
Difference	Difference from previous period
Percent Difference	`(current - previous) / previous * 100%`
Percent of Total	Share in overall total
Moving Average	Rolling average over N periods
YTD Total	Year-to-date running total
Compound Growth Rate	CAGR
Rank	Ranking within partition

Show last month filter: LAST() = 0 as table calculation filter.

Parameters¶

Create: right-click data panel -> Create Parameter. Types: String, Integer, Float, Boolean, Date.

IF [Sales] > [Parameter: Sales Threshold] THEN 'Above' ELSE 'Below' END

Metric switcher pattern: Parameter + IF/CASE to show different metrics based on dropdown selection.

Logical Functions¶

// IF
IF [Profit] > 0 THEN 'Profitable'
ELSEIF [Profit] = 0 THEN 'Break Even'
ELSE 'Loss'
END

// CASE (cleaner for multiple fixed values)
CASE [Region]
  WHEN 'North' THEN 'Northern Division'
  WHEN 'South' THEN 'Southern Division'
  ELSE 'Other'
END

Gotchas¶

Aggregation direction matters: configure whether calculation runs across columns or down rows from the "Compute Using" menu
Quick table calculations are actually window functions - they wrap formulas so you don't write them manually
Mixing aggregated and non-aggregated fields in a calculation causes errors - all must be at the same level
String type operations are the slowest; prefer type hierarchy: String > Date > Numeric > Boolean
DUPLICATE_AS_CROSSTAB reveals the underlying data table beneath a visualization - useful for debugging