Functions by category
In this section, you can find a list of the functions available in Amazon QuickSight, sorted by category.
Topics
Aggregate functions
The aggregate functions for calculated fields in Amazon QuickSight include the following. These are only available during analysis and visualization. Each of these functions returns values grouped by the chosen dimension or dimensions. For each aggregation, there is also a conditional aggregation. These perform the same type of aggregation, based on a condition.

avg averages the set of numbers in the specified measure, grouped by the chosen dimension or dimensions.

avgIf calculates the average based on a conditional statement.

count calculates the number of values in a dimension or measure, grouped by the chosen dimension or dimensions.

countIf calculates the count based on a conditional statement.

distinct_count calculates the number of distinct values in a dimension or measure, grouped by the chosen dimension or dimensions.

distinct_countIf calculates the distinct count based on a conditional statement.

max returns the maximum value of the specified measure, grouped by the chosen dimension or dimensions.

maxIf calculates the maximum based on a conditional statement.

median returns the median value of the specified measure, grouped by the chosen dimension or dimensions.

medianIf calculates the median based on a conditional statement.

min returns the minimum value of the specified measure, grouped by the chosen dimension or dimensions.

minIf calculates the minimum based on a conditional statement.

percentile (alias of
percentileDisc
) computes the nth percentile of the specified measure, grouped by the chosen dimension or dimensions. 
percentileCont calculates the nth percentile based on a continuous distribution of the numbers of the specified measure, grouped by the chosen dimension or dimensions.

percentileDisc (percentile) calculates the nth percentile based on the actual numbers of the specified measure, grouped by the chosen dimension or dimensions.

periodToDateAvg averages the set of numbers in the specified measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateCount calculates the number of values in a dimension or measure for a given time granularity (for instance, Quarter) up to a point in time including duplicates.

periodToDateMax returns the maximum value of the specified measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateMedian returns the median value of the specified measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateMin returns the minimum value of the specified measure or date for a given time granularity (for instance, a quarter) up to a point in time.

periodToDatePercentile calculates the percentile based on the actual numbers in measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDatePercentileCont calculates percentile based on a continuous distribution of the numbers in the measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateStDev calculates the standard deviation of the set of numbers in the specified measure for a given time granularity (for instance, a quarter) up to a point in time based on a sample.

periodToDateStDevP calculates the population standard deviation of the set of numbers in the specified measure for a given time granularity (for instance, a quarter) up to a point in time based on a sample.

periodToDateSum adds the set of numbers in the specified measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateVar calculates the sample variance of the set of numbers in the specified measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateVarP calculates the population variance of the set of numbers in the specified measure for a given time granularity (for instance, a quarter) up to a point in time.

stdev) calculates the standard deviation of the set of numbers in the specified measure, grouped by the chosen dimension or dimensions, based on a sample.

stdevIf calculates the sample standard deviation based on a conditional statement.

stdevp calculates the standard deviation of the set of numbers in the specified measure, grouped by the chosen dimension or dimensions, based on a biased population.

stdevpIf calculates the population deviation based on a conditional statement.

var) calculates the variance of the set of numbers in the specified measure, grouped by the chosen dimension or dimensions, based on a sample.

varIf calculates the sample variance based on a conditional statement.

varp) calculates the variance of the set of numbers in the specified measure, grouped by the chosen dimension or dimensions, based on a biased population.

varpIf calculates the population variance based on a conditional statement.

sum) adds the set of numbers in the specified measure, grouped by the chosen dimension or dimensions.

sumIf) calculates the sum based on a conditional statement.
Conditional functions
The conditional functions for calculated fields in Amazon QuickSight include the following:

Coalesce returns the value of the first argument that is not null.

Ifelse evaluates a set of if, then expression pairings, and returns the value of the then argument for the first if argument that evaluates to true.

in evaluates an expression to see if it is in a given list of values.

isNotNull evaluates an expression to see if it is not null.

isNull evaluates an expression to see if it is null. If the expression is null,
isNull
returns true, and otherwise it returns false. 
notIn evaluates an expression to see if it is not in a given list of values.

nullIf compares two expressions. If they are equal, the function returns null. If they are not equal, the function returns the first expression.

switch returns an expression that matches the first label equal to the condition expression.
Date functions
The date functions for calculated fields in Amazon QuickSight include the following:

addDateTime adds or subtracts a unit of time to the date or time provided.

addWorkDays adds or subtracts the given number of work days to the date or time provided.

dateDiff returns the difference in days between two date fields.

epochDate converts an epoch date into a standard date.

Extract returns a specified portion of a date value.

formatDate formats a date using a pattern you specify.

isWorkDay returns TRUE if a given datetime value is a work or business day.

netWorkDays returns the number of working days between the provided two date values.

Now returns the current date and time, using either settings for a database, or UTC for file and Salesforce.

truncDate returns a date value that represents a specified portion of a date.
Numeric functions
The numeric functions for calculated fields in Amazon QuickSight include the following:

Ceil rounds a decimal value to the next highest integer.

decimalToInt converts a decimal value to an integer.

Floor decrements a decimal value to the next lowest integer.

intToDecimal converts an integer value to a decimal.

Round rounds a decimal value to the closest integer or, if scale is specified, to the closest decimal place.
Mathematical functions
The mathematical functions for calculated fields in Amazon QuickSight include the following:

Mod(
– Finds the remainder after dividing a number by a divisor.number
,divisor
) 
Log(
– Returns the base 10 logarithm of a given expression.expression
) 
Ln(
– Returns the natural logarithm of a given expression.expression
) 
Abs(
– Returns the absolute value of a given expression.expression
) 
Sqrt(
– Returns the square root of a given expression.expression
) 
Exp(
– Returns the base of natural log e raised to the power of a given expression.expression
)
String functions
The string (text) functions for calculated fields in Amazon QuickSight include the following:

Concat concatenates two or more strings.

contains checks if an expression contains a substring.

endsWith checks if the expression ends with the substring specified.

Left returns the specified number of leftmost characters from a string.

Locate locates a substring within another string, and returns the number of characters before the substring.

Ltrim removes preceding blank space from a string.

parseDate parses a string to determine if it contains a date value, and returns the date if found.

parseDecimal parses a string to determine if it contains a decimal value.

parseInt parses a string to determine if it contains an integer value.

parseJson parses values from a native JSON or from a JSON object in a text field.

Replace replaces part of a string with a new string.

Right returns the specified number of rightmost characters from a string.

Rtrim removes following blank space from a string.

Split splits a string into an array of substrings, based on a delimiter that you choose, and returns the item specified by the position.

startsWith checks if the expression starts with the substring specified.

Strlen returns the number of characters in a string.

Substring returns the specified number of characters in a string, starting at the specified location.

toLower formats a string in all lowercase.

toString formats the input expression as a string.

toUpper formats a string in all uppercase.

trim removes both preceding and following blank space from a string.
Table calculations
Table calculations form a group of functions that provide context in an analysis. They provide support for enriched aggregated analysis. By using these calculations, you can address common business scenarios such as calculating percentage of total, running sum, difference, common baseline, and rank.
When you are analyzing data in a specific visual, you can apply table calculations to the current set of data to discover how dimensions influence measures or each other. Visualized data is your result set based on your current dataset, with all the filters, field selections, and customizations applied. To see exactly what this result set is, you can export your visual to a file. A table calculation function performs operations on the data to reveal relationships between fields.
Lookupbased functions
Difference calculates the difference between a measure based on one set of partitions and sorts, and a measure based on another.

Lag calculates the lag (previous) value for a measure.

Lead calculates the lead (following) value for a measure.
percentDifference calculates the percentage difference between the current value and a comparison value.
Over functions
avgOver calculates the average of a measure over one or more dimensions.
countOver calculates the count of a field over one or more dimensions.
distinctCountOver calculates the distinct count of the operand partitioned by the specified attributes at a specified level.
maxOver calculates the maximum of a measure over one or more dimensions.
minOver the minimum of a measure over one or more dimensions.
percentileOver (alias of
percentileDiscOver
) calculates the nth percentile of a measure partitioned by a list of dimensions.
percentileContOver calculates the nth percentile based on a continuous distribution of the numbers of a measure partitioned by a list of dimensions.

percentileDiscOver calculates the nth percentile based on the actual numbers of a measure partitioned by a list of dimensions.

percentOfTotal calculates the percentage that a measure contributes to the total.

periodOverPeriodDifference calculates the difference of a measure over two different time periods as specified by period granularity and offset.

periodOverPeriodLastValue calculates the last (previous) value of a measure from a previous time period as specified by period granularity and offset.

periodOverPeriodPercentDifference calculates the percent difference of a measure over two different time periods as specified by period granularity and offset.

periodToDateAvgOverTime calculates the average of a measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateCountOverTime calculates the count of a dimension or measure for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateMaxOverTime calculates the maximum of a measure or date for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateMinOverTime calculates the minimum of a measure or date for a given time granularity (for instance, a quarter) up to a point in time.

periodToDateSumOverTime calculates the sum of a measure for a given time granularity (for instance, a quarter) up to a point in time.

sumOver calculates the sum of a measure over one or more dimensions.

stdevOver calculates the standard deviation of the specified measure, partitioned by the chosen attribute or attributes, based on a sample.

stdevpOver calculates the standard deviation of the specified measure, partitioned by the chosen attribute or attributes, based on a biased population.

varOver calculates the variance of the specified measure, partitioned by the chosen attribute or attributes, based on a sample.

varpOver calculates the variance of the specified measure, partitioned by the chosen attribute or attributes, based on a biased population.
Ranking functions
Rank calculates the rank of a measure or a dimension.
denseRank calculates the rank of a measure or a dimension, ignoring duplicates.
percentileRank calculates the rank of a measure or a dimension, based on percentile.
Running functions
runningAvg calculates a running average for a measure.
runningCount calculates a running count for a measure.
runningMax calculates a running maximum for a measure.
runningMin calculates a running minimum for a measure.
runningSum calculates a running sum for a measure.
Window functions

firstValue calculates the first value of the aggregated measure or dimension partitioned and sorted by specified attributes.

lastValue calculates the last value of the aggregated measure or dimension partitioned and sorted by specified attributes.

windowAvg calculates the average of the aggregated measure in a custom window that is partitioned and sorted by specified attributes.

windowCount calculates the count of the aggregated measure in a custom window that is partitioned and sorted by specified attributes.

windowMax calculates the maximum of the aggregated measure in a custom window that is partitioned and sorted by specified attributes.

windowMin calculates the minimum of the aggregated measure in a custom window that is partitioned and sorted by specified attributes.

windowSum calculates the sum of the aggregated measure in a custom window that is partitioned and sorted by specified attributes.