The Tableau functions in this reference are organised alphabetically. Click a letter to see functions that start with it. If no functions start with that letter, the functions that start with the next letter in the alphabet are shown. You can also press Ctrl+F (Command-F on a Mac) to open a search box that you can use to search the page for a specific function.

#### ABS(number)

Returns the absolute value of the given number.

##### Examples

`ABS(-7) = 7`

`ABS([Budget Variance])`

The second example returns the absolute value for all the numbers contained in the `Budget Variance` field.

#### ACOS(number)

Returns the arc cosine of the given number. The result is in radians.

##### Example

```ACOS(-1) = 3.14159265358979```

#### ASCII(string)

Returns the ASCII code for the first character of `string`.

##### Example

```ASCII('A') = 65```

#### ASIN(number)

Returns the arc sine of a given number. The result is in radians.

##### Example

`ASIN(1) = 1.5707963267949`

#### ATAN(number)

Returns the arc tangent of a given number. The result is in radians.

##### Example

```ATAN(180) = 1.5652408283942```

#### ATAN2(y number, x number)

Returns the arc tangent of two given numbers (x and y). The result is in radians.

##### Example

`ATAN2(2, 1) = 1.10714871779409`

#### ATTR(expression)

Returns the value of the expression if it has a single value for all rows. Otherwise returns an asterisk. Null values are ignored.

#### AVG(expression)

Returns the average of all the values in the expression. AVG can be used with numeric fields only. Null values are ignored.

#### CASE expression WHEN value1 THEN return1 WHEN value2 THEN return2...ELSE default return END

Use the CASE function to perform logical tests and return appropriate values. CASE is often easier to use than IIF or IF THEN ELSE. The CASE function evaluates `expression`, compares it to a sequence of values, `value1`, `value2`, etc., and returns a result. When a value that matches `expression` is encountered, CASE returns the corresponding return value. If no match is found, the default return expression is used. If there is no default return and no values match, then Null is returned.

Typically, you use an IF function to perform a sequence of arbitrary tests, any you use a CASE function to search for a match to an expression. But a CASE function can always be rewritten as an IF function, although the CASE function will generally be more concise.

Often, you can use a group to get the same results as a complicated case function.

##### Examples

```CASE [Region] WHEN 'West' THEN 1 WHEN 'East' THEN 2 ELSE 3 END```

```CASE LEFT(DATENAME('weekday',[Order Date]),3) WHEN 'Sun' THEN 0 WHEN 'Mon' THEN 1 WHEN 'Tue' THEN 2 WHEN 'Wed' THEN 3 WHEN 'Thu' THEN 4 WHEN 'Fri' THEN 5 WHEN 'Sat' THEN 6 END```

#### CEILING(number)

Rounds a number to the nearest integer of equal or greater value.

##### Example

`CEILING(3.1415) = 4`

Availability by data source
 Data Source Support Microsoft Access Not supported Microsoft Excel Supported Text File Supported Statistical File Supported Tableau Server Supported Actian Vectorwise Not supported Amazon Aurora Not supported Amazon EMR Hadoop Hive Supported Amazon Redshift Not supported Aster Database Not supported Cloudera Hadoop Supported DataStax Enterprise Supported EXASOL Not supported Firebird Not supported Google Analytics Supported Google BigQuery Supported Google Cloud SQL Not supported Hortonworks Hadoop Hive Supported IBM BigInsights Not supported IBM DB2 Not supported IBM PDA (Netezza) Not supported MapR Hadoop Hive Supported MarkLogic Not supported Microsoft Analysis Services Not supported Microsoft PowerPivot Not supported Microsoft SQL Server Not supported MySQL Not supported Oracle Not supported Oracle Essbase Not supported Actian Matrix (ParAccel) Not supported Pivotal Greenplum Not supported PostgreSQL Not supported Progress OpenEdge Not supported Salesforce Supported SAP HANA Not supported SAP Sybase ASE Not supported SAP Sybase IQ Not supported Spark SQL Supported Splunk Not supported Teradata Not supported Teradata OLAP Connector Not supported Vertica Not supported

#### CHAR(number)

Returns the character encoded by the ASCII code `number`.

##### Example

```CHAR(65) = 'A'```

#### COLLECT (spatial)

An aggregate calculation that combines the values in the argument field. Null values are ignored.

Note: The COLLECT function can only be used with spatial fields.

##### Example

`COLLECT ([Geometry])`

#### CONTAINS(string, substring)

Returns true if the given string contains the specified substring.

##### Example

```CONTAINS(“Calculation”, “alcu”) = true```

#### CORR(expression 1, expression2)

Returns the Pearson correlation coefficient of two expressions.

The Pearson correlation measures the linear relationship between two variables. Results range from -1 to +1 inclusive, where 1 denotes an exact positive linear relationship, as when a positive change in one variable implies a positive change of corresponding magnitude in the other, 0 denotes no linear relationship between the variance and −1 is an exact negative relationship.

CORR is available with the following data sources:

• Tableau data extracts (you can create an extract from any data source)
• Cloudera Hive
• EXASOL
• Firebird (version 3.0 and later)
• Oracle
• PostgreSQL
• Presto
• SybaseIQ
• Vertica

For other data sources, consider either extracting the data or using WINDOW_CORR. See Table Calculation Functions.

Note: The square of a CORR result is equivalent to the R-Squared value for a linear trend line model. See Trend Line Model Terms.

##### Example

You can use CORR to visualise correlation in a disaggregated scatter plot. The way to do this is to use a table-scoped level of detail expression. For example:

`{CORR(Sales, Profit)}`

With a level of detail expression, the correlation is run over all rows. If you used a formula like `CORR(Sales, Profit)` (without the surrounding brackets to make it a level of detail expression), the view would show the correlation of each individual point in the scatter plot with each other point, which is undefined.

See Table-Scoped

#### COS(number)

Returns the cosine of an angle. Specify the angle in radians.

##### Example

`COS(PI( ) /4) = 0.707106781186548`

#### COT(number)

Returns the cotangent of an angle. Specify the angle in radians.

##### Example

`COT(PI( ) /4) = 1`

#### COUNT(expression)

Returns the number of items in a group. Null values are not counted.

#### COUNTD(expression)

Returns the number of distinct items in a group. Null values are not counted. This function is not available in the following cases: workbooks created before Tableau Desktop 8.2 that use Microsoft Excel or text file data sources, workbooks that use the legacy connection and workbooks that use Microsoft Access data sources. Extract your data into an extract file to use this function. See Extract Your Data.

#### COVAR(expression 1, expression2)

Returns the sample covariance of two expressions.

Covariance quantifies how two variables change together. A positive covariance indicates that the variables tend to move in the same direction, as when larger values of one variable tend to correspond to larger values of the other variable, on average. Sample covariance uses the number of non-null data points n - 1 to normalise the covariance calculation, rather than n, which is used by the population covariance (available with the COVARP function). Sample covariance is the appropriate choice when the data is a random sample that is being used to estimate the covariance for a larger population.

COVAR is available with the following data sources:

• Tableau data extracts (you can create an extract from any data source)
• Cloudera Hive
• EXASOL
• Firebird (version 3.0 and later)
• IBM PDA (Netezza)
• Oracle
• PostgreSQL
• Presto
• SybaseIQ
• Vertica

For other data sources, consider either extracting the data or using WINDOW_COVAR. See Table Calculation Functions.

If expression1 and expression2 are the same – for example, COVAR([profit], [profit]) – COVAR returns a value that indicates how widely the values are distributed.

Note: The value of COVAR(X, X) is equivalent to the value of VAR(X) and also to the value of STDEV(X)^2.

##### Example

The following formula returns the sample covariance of Sales and Profit.

`COVAR([Sales], [Profit])`

#### COVARP(expression 1, expression2)

Returns the population covariance of two expressions.

Covariance quantifies how two variables change together. A positive covariance indicates that the variables tend to move in the same direction, as when larger values of one variable tend to correspond to larger values of the other variable, on average. Population covariance is sample covariance multiplied by (n-1)/n, where n is the total number of non-null data points. Population covariance is the appropriate choice when there is data available for all items of interest as opposed to when there is only a random subset of items, in which case sample covariance (with the COVAR function) is appropriate.

COVARP is available with the following data sources:

• Tableau data extracts (you can create an extract from any data source)
• Cloudera Hive
• EXASOL
• Firebird (version 3.0 and later)
• IBM PDA (Netezza)
• Oracle
• PostgreSQL
• Presto
• SybaseIQ
• Vertica

For other data sources, consider either extracting the data or using WINDOW_COVARP. See Table Calculation Functions.

If expression1 and expression2 are the same – for example, COVARP([profit], [profit]) – COVARP returns a value that indicates how widely values are distributed.

Note: The value of COVARP(X, X) is equivalent to the value of VARP(X) and also to the value of STDEVP(X)^2.

##### Example

The following formula returns the population covariance of Sales and Profit.

`COVARP([Sales], [Profit])`

#### DATE(expression)

Returns a date, given a number, string or date expression.

##### Examples

```DATE([Employee Start Date])```

```DATE("April 15, 2004") = #April 15, 2004#```

`DATE("4/15/2004")`

```DATE(#2006-06-15 14:52#) = #2006-06-15#```

Quotation marks are required in the second and third examples.

Returns the specified date with the specified number `interval` added to the specified `date_part` of that date.

##### Example

`DATEADD('month', 3, #2004-04-15#) = 2004-07-15 12:00:00 AM`

This expression adds three months to the date `#2004-04-15#`.

#### DATEDIFF(date_part, date1, date2, [start_of_week])

Returns the difference between `date1` and `date2` expressed in units of `date_part`.

The `start_of_week` parameter, which you can use to specify which day is to be considered the first day or the week, is optional. Possible values are 'monday', 'tuesday', etc. If it is omitted, the start of week is determined by the data source. See Date Properties for a Data Source.

##### Example

`DATEDIFF('week', #2013-09-22#, #2013-09-24#, 'monday')= 1`

`DATEDIFF('week', #2013-09-22#, #2013-09-24#, 'sunday')= 0`

The first expression returns 1 because when `start_of_week` is 'monday', then 22 September (a Sunday) and 24 September (a Tuesday) are in different weeks. The second expression returns 0 because when `start_of_week` is 'sunday' then 22 September (a Sunday) and 24 September (a Tuesday) are in the same week.

#### DATENAME(date_part, date, [start_of_week])

Returns `date_part` of `date` as a string. The `start_of_week` parameter, which you can use to specify which day is to be considered the first day or the week, is optional. Possible values are 'monday', 'tuesday', etc. If `start_of_week` is omitted, the start of week is determined by the data source. See Date Properties for a Data Source.

##### Examples

```DATENAME('year', #2004-04-15#) = "2004"```

`DATENAME('month', #2004-04-15#) = "April"`

#### DATEPARSE(format, string)

Converts a string to a datetime in the specified format. Support for some locale-specific formats is determined by the computer's system settings. Letters that appear in the data and do not need to be parsed should be surrounded by single quotes (' '). For formats that do not have delimiters between values (for example, MMddyy), verify that they are parsed as expected. The format must be a constant string, not a field value. This function returns `Null` if the data does not match the format.

This function is available for several connectors. For more information, see Convert a Field to a Date Field.

##### Examples

`DATEPARSE ("dd.MMMM.yyyy", "15.April.2004") = #April 15, 2004#`

`DATEPARSE ("h'h' m'm' s's'", "10h 5m 3s") = #10:05:03#`

#### DATEPART(date_part, date, [start_of_week])

Returns `date_part` of `date` as an integer.

The `start_of_week` parameter, which you can use to specify which day is to be considered the first day or the week, is optional. Possible values are 'monday', 'tuesday', etc. If `start_of_week` is omitted, the start of week is determined by the data source. See Date Properties for a Data Source.

Note: When the `date_part` is weekday, the `start_of_week` parameter is ignored. This is because Tableau relies on a fixed weekday ordering to apply offsets.

##### Examples

```DATEPART('year', #2004-04-15#) = 2004```

`DATEPART('month', #2004-04-15#) = 4`

#### DATETIME(expression)

Returns a datetime given a number, string or date expression.

##### Example

```DATETIME(“April 15, 2005 07:59:00”) = April 15, 2005 07:59:00```

#### DATETRUNC(date_part, date, [start_of_week])

Truncates the specified date to the accuracy specified by the date_part. This function returns a new date. For example, when you truncate a date that is in the middle of the month at the month level, this function returns the first day of the month. The `start_of_week` parameter, which you can use to specify which day is to be considered the first day or the week, is optional. Possible values are 'monday', 'tuesday', etc. If `start_of_week` is omitted, the start of week is determined by the data source. See Date Properties for a Data Source.

##### Examples

```DATETRUNC('quarter', #2004-08-15#) = 2004-07-01 12:00:00 AM```

```DATETRUNC('month', #2004-04-15#) = 2004-04-01 12:00:00 AM```

#### DAY(date)

Returns the day of the given date as an integer.

##### Example

`DAY(#2004-04-12#) = 12`

#### DEGREES(number)

Converts a given number in radians to degrees.

##### Example

`DEGREES(PI( )/4) = 45.0`

#### DISTANCE(Geometry1, Geometry2, "Units")

Returns distance measurement between two points in a specified unit. Supported unit names: metres ("meters", "metres", "m"), kilometres ("kilometres", "kilometres", "km"), miles ("miles" or "miles"), feet ("feet" or "ft").

This function can only be created with a live connection and will continue to work when a data source is converted to an extract.

##### Examples

`DISTANCE ({ EXCLUDE [Branch Name] : COLLECT([Selected Point]) }, [unselected point], 'km') `

`DISTANCE([Origin MakePoint],[Destination MakePoint], "miles")`

#### DIV(integer1, integer2)

Returns the integer part of a division operation, in which integer1 is divided by integer2.

##### Example

`DIV(11,2) = 5`

#### DOMAIN(string_url)

Note : Supported only when connected to Google BigQuery

Given a URL string, returns the domain as a string.

#### ENDSWITH(string, substring)

Returns true if the given string ends with the specified substring. Trailing white spaces are ignored.

##### Example

```ENDSWITH(“Tableau”, “leau”) = true```

#### EXP(number)

Returns e raised to the power of the given number.

##### Examples

`EXP(2) = 7.389`

```EXP(-[Growth Rate]*[Time])```

#### FIND(string, substring, [start])

Returns the index position of `substring` in `string`, or 0 if the `substring` isn't found. If the optional argument `start` is added, the function ignores any instances of `substring` that appear before the index position `start`. The first character in the string is position 1.

##### Examples

```FIND("Calculation", "alcu") = 2 ```

`FIND("Calculation", "Computer") = 0`

```FIND("Calculation", "a", 3) = 7```

`FIND("Calculation", "a", 2) = 2`

```FIND("Calculation", "a", 8) = 0```

#### FINDNTH(string, substring, occurrence)

Returns the position of the nth occurrence of substring within the specified string, where n is defined by the occurrence argument.

Note: FINDNTH is not available for all data sources.

##### Example

`FINDNTH("Calculation", "a", 2) = 7`

#### FIRST( )

Returns the number of rows from the current row to the first row in the partition. For example, the view below shows quarterly sales. When FIRST() is computed within the Date partition, the offset of the first row from the second row is -1.

##### Example

When the current row index is 3, ```FIRST() = -2```.

#### FLOAT(expression)

Casts its argument as a floating point number.

##### Examples

`FLOAT(3)` = `3.000`

`FLOAT([Age])` converts every value in the `Age` field to a floating point number.

#### FLOOR(number)

Rounds a number to the nearest integer of equal or lesser value.

##### Example

`FLOOR(3.1415) = 3`

Availability by data source
 Data Source Support Microsoft Access Not supported Microsoft Excel Supported Text File Supported Statistical File Supported Tableau Server Supported Actian Vector Not supported Amazon Aurora Not supported Amazon EMR Hadoop Hive Supported Amazon Redshift Not supported Aster Database Not supported Cloudera Hadoop Supported DataStax Enterprise Supported EXASOL Not supported Firebird Not supported Google Analytics Supported Google BigQuery Supported Google Cloud SQL Not supported Hortonworks Hadoop Hive Supported IBM BigInsights Not supported IBM DB2 Not supported IBM Netezza Not supported MapR Hadoop Hive Supported MarkLogic Not supported Microsoft Analysis Services Not supported Microsoft PowerPivot Not supported Microsoft SQL Server Not supported MySQL Not supported Oracle Not supported Oracle Essbase Not supported ParAccel Not supported Pivotal Greenplum Not supported PostgreSQL Not supported Progress OpenEdge Not supported Salesforce Supported SAP HANA Not supported SAP Sybase ASE Not supported SAP Sybase IQ Not supported Spark SQL Supported Splunk Not supported Teradata Not supported Teradata OLAP Connector Not supported Vertica Not supported

#### FULLNAME( )

Returns the full name for the current user. This is the Tableau Server or Tableau Online full name when the user is signed in; otherwise the local or network full name for the Tableau Desktop user.

##### Example

`[Manager]=FULLNAME( )`

If manager Dave Hallsten is signed in, this example returns True only if the Manager field in the view contained Dave Hallsten. When used as a filter, this calculated field can be used to create a user filter that only shows data that is relevant to the person signed in to the server.

#### GET_JSON_OBJECT(JSON string, JSON path)

Note: Supported only when connected to Hadoop Hive.

Returns the JSON object within the JSON string based on the JSON path.

#### GROUP_CONCAT(expression)

Note : Supported only when connected to Google BigQuery

Concatenates values from each record into a single comma-delimited string. This function acts like a SUM() for strings.

##### Example

GROUP_CONCAT(Region) = "Central,East,West"

#### HEXBINX(number, number)

Maps an x, y coordinate to the x-coordinate of the nearest hexagonal bin. The bins have side length 1, so the inputs may need to be scaled appropriately.

HEXBINX and HEXBINY are binning and plotting functions for hexagonal bins. Hexagonal bins are an efficient and elegant option for visualising data in an x/y plane such as a map. Because the bins are hexagonal, each bin closely approximates a circle and minimises variation in the distance from the data point to the centre of the bin. This makes the clustering both more accurate and informative.

##### Example

`HEXBINX([Longitude], [Latitude])`

#### HEXBINY(number, number)

Maps an x, y coordinate to the y-coordinate of the nearest hexagonal bin. The bins have side length 1, so the inputs may need to be scaled appropriately.

##### Example

`HEXBINY([Longitude], [Latitude])`

#### HOST(string_url)

Note : Supported only when connected to Google BigQuery

Given a URL string, returns the host name as a string.

#### IF test THEN value END / IF test THEN value ELSE else END

Use the IF THEN ELSE function to perform logical tests and return appropriate values. The IF THEN ELSE function evaluates a sequence of test conditions and returns the value for the first condition that is true. If no condition is true, the ELSE value is returned. Each test must be a boolean: either a boolean field in the data source or the result of a logical expression. The final ELSE is optional, but if it is not provided and there is no true test expression, then the function returns Null. All the value expressions must be of the same type.

##### Examples

```IF [Cost]>[Budget Cost] THEN 'Over Budget' ELSE 'Under Budget' END```

```IF [Budget Sales]!=0 THEN [Sales]/[Budget Sales] END```

#### IF test1 THEN value1 ELSEIF test2 THEN value2 ELSE else END

Use this version of the IF function to perform logical tests recursively. There is no built-in limit to the number of ELSEIFvalues you can use with an IF function, though individual databases may impose a limit on IF function complexity. While an IF function can be rewritten as a series of nested IIF statements, there are differences in how the expressions will be evaluated. In particular, an IIF statement distinguishes TRUE, FALSE and UNKNOWN, whereas an IF statement only worries about TRUE and not true (which includes both FALSE and UNKNOWN).

##### Example

When you create bins from a measure, Tableau creates bins of equal size by default. For example, let’s say you have a measure that represents age. When you create bins from that measure, Tableau makes all the bins of equal size. You can specify how big you want the bins to be, but you cannot specify a separate range of values for each bin. A way around this constraint is to create a calculated field to define bins. Then you can create one bin for ages 0 - 20, another for ages 21 - 32, and so on. The following procedure shows how you could do that.

1. Create a new calculated field by choosing Analysis > Create Calculated Field.

2. Name the field Age Groups and type the following in the definition area

```IF
[Age] < 21 THEN 'Under 21'
ELSEIF
[Age] <= 32 THEN '21-32'
ELSEIF
[Age] <= 42 THEN '33-42'
ELSEIF
[Age] <= 52 THEN '43-52'
ELSEIF
[Age] <= 64 THEN '53-64'
ELSE '65+'
END```

Confirm that the status message indicates that the formula is valid, and then click OK.

3. From the Measures area of the Data pane, drag Number of Records to Rows.

4. From the Dimensions area of the Data pane, drag Age Groups to Columns.

The records are now divided among the six bins that you defined:

Unfortunately, the Under 21 bin is at the far right, when you would expect it to be at the far left. Tableau is smart enough to put the bins with entirely numerical names in the right order, but it can't guess that the bin name beginning with 'Under' belongs at the left. Fix the problem with a manual sort.

5. Click the down arrow at the right side of the Age Groups field on Columns and then click Sort. Choose Manual and then move the Under 21 bin up to the top of the list:

#### IIF(test, then, else, [unknown])

Use the IIF function to perform logical tests and return appropriate values. The first argument, `test`, must be a boolean: either a boolean field in the data source, or the result of a logical expression using operators (or a logical comparison of AND, OR, or NOT). If `test` evaluates to TRUE, then IIF returns the `then `value. If `test` evaluates to FALSE, then IIF returns the `else` value.

A boolean comparison may also yield the value UNKNOWN (neither TRUE nor FALSE), usually due to the presence of Null values in test. The final argument to IIF is returned in the event of an UNKNOWN result for the comparison. If this argument is left out, Null is returned.

##### Examples

```IIF(7>5, 'Seven is greater than five', 'Seven is less than five')```

```IIF([Cost]>[Budget Cost], 'Over Budget', 'Under Budget')```

`IIF([Budget Sales]!=0,[Sales]/[Budget Sales],0)`

```IIF(Sales>=[Budget Sales], 'Over Cost Budget and Over Sales Budget', 'Over Cost Budget and Under Sales Budget','Under Cost Budget')```

#### IFNULL(expression1, expression2)

The IFNULL function returns the first expression if the result is not null, and returns the second expression if it is null.

##### Example

`IFNULL([Profit], 0) = [Profit]`

#### INDEX( )

Returns the index of the current row in the partition, without any sorting with regard to value. The first row index starts at 1. For example, the table below shows quarterly sales. When INDEX() is computed within the Date partition, the index of each row is 1, 2, 3, 4..., etc.

##### Example

For the third row in the partition, `INDEX() = 3`.

#### INT(expression)

Casts its argument as an integer. For expressions, this function truncates results to the closest integer toward zero.

##### Examples

`INT(8.0/3.0)` = `2`

`INT(4.0/1.5)` = `2`

`INT(0.50/1.0)` = `0`

`INT(-9.7)` = `-9`

When a string is converted to an integer it is first converted to a float and then rounded.

#### ISDATE(string)

The ISDATE function returns `TRUE` if the string argument can be converted to a date and `FALSE` if it cannot.

##### Examples

`ISDATE('January 1, 2003') = TRUE`

```ISDATE('Jan 1 2003') = TRUE```

`ISDATE('1/1/03') = TRUE`

```ISDATE('Janxx 1 2003') = FALSE```

#### ISFULLNAME(string)

Returns true if the current user's full name matches the specified full name, or false if it does not match. This function uses the Tableau Server or Online full name when the user is signed in; otherwise it uses the local or network full name for the Tableau Desktop user.

##### Example

`ISFULLNAME(“Dave Hallsten”)`

This example returns true if Dave Hallsten is the current user, otherwise it returns false.

#### ISNULL(expression)

The ISNULL function returns `TRUE` if the expression is `Null` and `FALSE` if it is not.

##### Example

The following example uses ISNULL in combination with IIF to replace null values with 0's.

`IIF(ISNULL([Sales]), 0,[Sales] )`

#### ISMEMBEROF(string)

Returns true if the person currently using Tableau is a member of a group that matches the given string. If the person currently using Tableau is signed in, the group membership is determined by groups on Tableau Server or Tableau Online. If the person is not signed in, this function returns false.

##### Example

`IF ISMEMBEROF(“Sales”) THEN “Sales” ELSE “Other” END`

Returns true if the current user's username matches the specified username, or false if it does not. This function uses the Tableau Server or Online username when the user is signed in; otherwise it uses the local or network username for the Tableau Desktop user.

##### Example

`ISUSERNAME(“dhallsten”)`

This example returns true if dhallsten is the current user; otherwise it returns false.

#### LAST( )

Returns the number of rows from the current row to the last row in the partition. For example, the table below shows quarterly sales. When LAST() is computed within the Date partition, the offset of the last row from the second row is 5.

##### Example

When the current row index is 3 of 7, `LAST() = 4`.

#### LEFT(string, number)

Returns the left-most number of characters in the string.

##### Example

```LEFT("Matador", 4) = "Mata"```

#### LEN(string)

Returns the length of the string.

##### Example

`LEN("Matador") = 7`

#### LN(number)

Returns the natural logarithm of a number. Returns `Null` if number is less than or equal to 0.

#### LOG(number [, base])

Returns the logarithm of a number for the given base. If the base value is omitted, base 10 is used.

#### LOG2(number)

Note : Supported only when connected to Google BigQuery

Returns the logarithm base 2 of a number.

##### Example

LOG2(16) = '4.00'

#### LOOKUP(expression, [offset])

Returns the value of the expression in a target row, specified as a relative offset from the current row. Use FIRST() + n and LAST() - n as part of your offset definition for a target relative to the first/last rows in the partition. If `offset` is omitted, the row to compare to can be set on the field menu. This function returns NULL if the target row cannot be determined.

The view below shows quarterly sales. When `LOOKUP (SUM(Sales), 2)` is computed within the Date partition, each row shows the sales value from 2 quarters into the future.

##### Example

```LOOKUP(SUM([Profit]), FIRST()+2)``` computes the SUM(Profit) in the third row of the partition.

#### LOWER(string)

Returns `string`, with all characters lowercase.

##### Example

`LOWER("ProductVersion") = "productversion"`

#### LTRIM(string)

Returns the string with any leading spaces removed.

##### Example

```LTRIM(" Matador ") = "Matador "```

#### LTRIM_THIS(string, string)

Note : Supported only when connected to Google BigQuery

Returns the first string with any leading occurrence of the second string removed.

##### Example

LTRIM_THIS('[-Sales-]','[-') = 'Sales-]'

#### MAKEDATE(year, month, day)

Returns a date value constructed from the specified year, month and date.

Available for Tableau Data Extracts. Check for availability in other data sources.

##### Example

`MAKEDATE(2004, 4, 15) = #April 15, 2004#`

#### MAKEDATETIME(date, time)

Returns a datetime that combines a date and a time. The date can be a date, datetime or a string type. The time must be a datetime. This function is available only for MySQL-compatible connections (which for Tableau are, in addition to MySQL, Amazon Aurora and Amazon Aurora).

##### Examples

`MAKEDATETIME("1899-12-30", #07:59:00#) = #12/30/1899 7:59:00 AM#`

`MAKEDATETIME([Date], [Time]) = #1/1/2001 6:00:00 AM#`

MAKELINE(geometry1,geometry2)

#### MAKELINE(Geometry1,Geometry2)

Generates a line mark between two spatial points; useful for building origin-destination maps.

##### Example

`MAKELINE(MAKEPOINT(OriginLat],[OriginLong) ),MAKEPOINT([DestinationLat],[DestinationLong] ) )`

`MAKELINE(Geometry1, Geometry2 )`

#### MAKEPOINT(Latitude,Longitude)

Converts data from latitude and longitude columns into spatial objects. You can use MAKEPOINT to spatially-enable a data source so that it can be joined with a spatial file using a spatial join. To use MAKEPOINT, your data must contain latitude and longitude coordinates.

##### Example

`MAKEPOINT([AirportLatitude],[AirportLongitude])`

#### MAKEPOINT(Xcoordinate,Ycoordinate,SRID)

Converts data from projected geographic coordinates into spatial objects. SRID is a spatial reference identifier that uses ESPG reference system codes to specify coordinate systems. If SRID is not specified, WGS84 is assumed and parameters are treated as latitude/longitude in degrees.

This function can only be created with a live connection and will continue to work when a data source is converted to an extract.

##### Example

`MAKEPOINT([Xcoord],[Ycoord],3493)`

#### MAKETIME(hour, minute, second)

Returns a date value constructed from the specified hour, minute and second.

Available for Tableau Data Extracts. Check for availability in other data sources.

##### Example

`MAKETIME(14, 52, 40) = #14:52:40#`

#### MAX(a, b)

Returns the maximum of `a` and `b` (which must be of the same type). This function is usually used to compare numbers, but also works on strings. With strings, `MAX` finds the value that is highest in the sort sequence defined by the database for that column. It returns `Null` if either argument is `Null`.

##### Example

`MAX ("Apple","Banana") = "Banana"`

#### MAX(expression) or MAX(expr1, expr2)

Usually applied to numbers but also works on dates. Returns the maximum of `a` and `b` (`a` and `b` must be of the same type). Returns `Null` if either argument is `Null`.

##### Examples

`MAX(#2004-01-01# ,#2004-03-01#) = 2004-03-01 12:00:00 AM`

```MAX([ShipDate1], [ShipDate2])```

#### MAX(number, number)

Returns the maximum of the two arguments, which must be of the same type. Returns `Null` if either argument is `Null`. `MAX` can also be applied to a single field in an aggregate calculation.

##### Examples

`MAX(4,7)`

`MAX(Sales,Profit)`

```MAX([First Name],[Last Name])```

#### MEDIAN(expression)

Returns the median of an expression across all records. Median can only be used with numeric fields. Null values are ignored. This function is not available for workbooks created before Tableau Desktop 8.2 or that use legacy connections. It is also not available for connections using any of the following data sources:

• Access
• Amazon Redshift
• IBM DB2
• IBM PDA (Netezza)
• Microsoft SQL Server
• MySQL
• SAP HANA
• Vertica

For other data source types, you can extract your data into an extract file to use this function. See Extract Your Data.

#### MID(string, start, [length])

Returns the string starting at index position `start`. The first character in the string is position 1. If the optional argument `length` is added, the returned string includes only that number of characters.

##### Examples

`MID("Calculation", 2) = "alculation"`

```MID("Calculation", 2, 5) ="alcul"```

#### MIN(a, b)

Returns the minimum of `a` and `b` (which must be of the same type). This function is usually used to compare numbers, but also works on strings. With strings, `MIN` finds the value that is lowest in the sort sequence. It returns `Null` if either argument is `Null`.

##### Example

```MIN ("Apple","Banana") = "Apple"```

#### MIN(expression) or MIN(expr1, expr2)

Usually applied to numbers but also works on dates. Returns the minimum of `a` and `b` (`a` and `b` must be of the same type). Returns `Null` if either argument is `Null`.

##### Examples

`MIN(#2004-01-01# ,#2004-03-01#) = 2004-01-01 12:00:00 AM`

```MIN([ShipDate1], [ShipDate2])```

#### MIN(number, number)

Returns the minimum of the two arguments, which must be of the same type. Returns `Null` if either argument is `Null`. `MIN` can also be applied to a single field in an aggregate calculation.

##### Examples

`MIN(4,7)`

`MIN(Sales,Profit)`

```MIN([First Name],[Last Name])```

#### MODEL_PERCENTILE(target_expression, predictor_expression(s))

Returns the probability (between 0 and 1) of the expected value being less than or equal to the observed mark, defined by the target expression and other predictors. This is the Posterior Predictive Distribution Function, also known as the Cumulative Distribution Function (CDF).

##### Example

`MODEL_PERCENTILE( SUM([Sales]),COUNT([Orders]))`

#### MODEL_QUANTILE(quantile, target_expression, predictor_expression(s))

Returns a target numeric value within the probable range defined by the target expression and other predictors, at a specified quantile. This is the Posterior Predictive Quantile.

##### Example

`MODEL_QUANTILE(0.5, SUM([Sales]),COUNT([Orders]))`

#### MONTH(date)

Returns the month of the given date as an integer.

##### Example

`MONTH(#2004-04-15#) = 4`

#### NOW( )

Returns the current date and time.

The return varies depending on the nature of the connection:

• For a live, unpublished connection, NOW returns the data source server time.

• For a live, published connection, NOW returns the data source server time.

• For an unpublished extract, NOW returns the local system time.

• For a published extract, NOW returns the local time of the Tableau Server Data Engine. When there are multiple worker machines indifferent time zones, this can produce inconsistent results.

##### Example

`NOW( ) = 2004-04-15 1:08:21 PM`

#### PARSE_URL(string, url_part)

Note: Supported only when connected to Hadoop Hive and Cloudera Impala.

Returns a component of the given URL string where the component is defined by url_part. Valid url_part values include: 'HOST', 'PATH', 'QUERY', 'REF', 'PROTOCOL', 'AUTHORITY', 'FILE' and 'USERINFO'.

##### Example

PARSE_URL('http://www.tableau.com', 'HOST') = 'www.tableau.com'

#### PARSE_URL_QUERY(string, key)

Note: Supported only when connected to Hadoop Hive and Cloudera Impala.

Returns the value of the specified query parameter in the given URL string. The query parameter is defined by the key.

##### Example

PARSE_URL_QUERY('http://www.tableau.com?page=1&cat=4', 'page') = '1'

#### PERCENTILE(expression, number)

Returns the percentile value from the given expression corresponding to the specified number. The number must be between 0 and 1 (inclusive) – for example, 0.66, and must be a numeric constant.

This function is available for the following data sources.

• Non-legacy Microsoft Excel and Text File connections.

• Extracts and extract-only data source types (for example, Google Analytics, OData or Salesforce).

• Sybase IQ 15.1 and later data sources.

• Oracle 10 and later data sources.

• Cloudera Hive and Hortonworks Hadoop Hive data sources.

• EXASOL 4.2 and later data sources.

For other data source types, you can extract your data into an extract file to use this function. See Extract Your Data.

#### PI( )

Returns the numeric constant pi: 3.14159.

#### POWER(number, power)

Raises the number to the specified power.

##### Examples

```POWER(5,2) = 52 = 25```

`POWER(Temperature, 2)`

You can also use the ^ symbol:

```5^2 = POWER(5,2) = 25```

#### PREVIOUS_VALUE(expression)

Returns the value of this calculation in the previous row. Returns the given expression if the current row is the first row of the partition.

##### Example

`SUM([Profit]) * PREVIOUS_VALUE(1)` computes the running product of SUM(Profit).

Converts the given number from degrees to radians.

##### Example

`RADIANS(180) = 3.14159`

#### RANK(expression, ['asc' | 'desc'])

Returns the standard competition rank for the current row in the partition. Identical values are assigned an identical rank. Use the optional `'asc' | 'desc'` argument to specify ascending or descending order. The default is descending.

With this function, the set of values (6, 9, 9, 14) would be ranked (4, 2, 2, 1).

Nulls are ignored in ranking functions. They are not numbered and they do not count against the total number of records in percentile rank calculations.

For information on different ranking options, see Rank calculation.

##### Example

The following image shows the effect of the various ranking functions (RANK, RANK_DENSE, RANK_MODIFIED, RANK_PERCENTILE and RANK_UNIQUE) on a set of values. The data set contains information on 14 students (StudentA through StudentN); the Age column shows the current age of each student (all students are between 17 and 20 years of age). The remaining columns show the effect of each rank function on the set of age values, always assuming the default order (ascending or descending) for the function.

#### RANK_DENSE(expression, ['asc' | 'desc'])

Returns the dense rank for the current row in the partition. Identical values are assigned an identical rank, but no gaps are inserted into the number sequence. Use the optional `'asc' | 'desc'` argument to specify ascending or descending order. The default is descending.

With this function, the set of values (6, 9, 9, 14) would be ranked (3, 2, 2, 1).

Nulls are ignored in ranking functions. They are not numbered and they do not count against the total number of records in percentile rank calculations.

For information on different ranking options, see Rank calculation.

#### RANK_MODIFIED(expression, ['asc' | 'desc'])

Returns the modified competition rank for the current row in the partition. Identical values are assigned an identical rank. Use the optional `'asc' | 'desc'` argument to specify ascending or descending order. The default is descending.

With this function, the set of values (6, 9, 9, 14) would be ranked (4, 3, 3, 1).

Nulls are ignored in ranking functions. They are not numbered and they do not count against the total number of records in percentile rank calculations.

For information on different ranking options, see Rank calculation.

#### RANK_PERCENTILE(expression, ['asc' | 'desc'])

Returns the percentile rank for the current row in the partition. Use the optional `'asc' | 'desc'` argument to specify ascending or descending order. The default is ascending.

With this function, the set of values (6, 9, 9, 14) would be ranked (0.25, 0.75, 0.75, 1.00).

Nulls are ignored in ranking functions. They are not numbered and they do not count against the total number of records in percentile rank calculations.

For information on different ranking options, see Rank calculation.

#### RANK_UNIQUE(expression, ['asc' | 'desc'])

Returns the unique rank for the current row in the partition. Identical values are assigned different ranks. Use the optional `'asc' | 'desc'` argument to specify ascending or descending order. The default is descending.

With this function, the set of values (6, 9, 9, 14) would be ranked (4, 2, 3, 1).

Nulls are ignored in ranking functions. They are not numbered and they do not count against the total number of records in percentile rank calculations.

For information on different ranking options, see Rank calculation.

#### RAWSQL_BOOL(“sql_expr”, [arg1], …[argN])

Returns a Boolean result from a given SQL expression. The SQL expression is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values.

#### Example

In the example, %1 is equal to [Sales] and %2 is equal to [Profit].

RAWSQL_BOOL(“IIF( %1 > %2, True, False)”, [Sales], [Profit])

#### RAWSQL_DATE(“sql_expr”, [arg1], …[argN])

Returns a Date result from a given SQL expression. The SQL expression is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values.

#### Example

In this example, %1 is equal to [Order Date].

```RAWSQL_DATE(“%1”, [Order Date])```

#### RAWSQL_DATETIME(“sql_expr”, [arg1], …[argN])

Returns a Date and Time result from a given SQL expression. The SQL expression is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Delivery Date].

#### Example

RAWSQL_DATETIME(“MIN(%1)”, [Delivery Date])

#### RAWSQL_INT(“sql_expr”, [arg1], …[argN])

Returns an integer result from a given SQL expression. The SQL expression is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Sales].

#### Example

```RAWSQL_INT(“500 + %1”, [Sales])```

#### RAWSQL_REAL(“sql_expr”, [arg1], …[argN])

Returns a numeric result from a given SQL expression that is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Sales]

#### Example

`RAWSQL_REAL(“-123.98 * %1”, [Sales])`

#### RAWSQL_SPATIAL

Returns a Spatial from a given SQL expression that is passed directly to the underlying data source. Use %n in the SQL expression as a substitution syntax for database values.

#### Example

In this example, %1 is equal to [Geometry].

`RAWSQL_SPATIAL("%1", [Geometry])`

#### RAWSQL_STR(“sql_expr”, [arg1], …[argN])

Returns a string from a given SQL expression that is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Customer Name].

#### Example

`RAWSQL_STR(“%1”, [Customer Name])`

#### RAWSQLAGG_BOOL(“sql_expr”, [arg1], …[argN])

Returns a Boolean result from a given aggregate SQL expression. The SQL expression is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values.

#### Example

In the example, %1 is equal to [Sales] and %2 is equal to [Profit].

RAWSQLAGG_BOOL(“SUM( %1) >SUM( %2)”, [Sales], [Profit])

#### RAWSQLAGG_DATE(“sql_expr”, [arg1], …[argN])

Returns a Date result from a given aggregate SQL expression. The SQL expression is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Order Date].

#### Example

```RAWSQLAGG_DATE(“MAX(%1)”, [Order Date])```

#### RAWSQLAGG_DATETIME(“sql_expr”, [arg1], …[argN])

Returns a Date and Time result from a given aggregate SQL expression. The SQL expression is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Delivery Date].

#### Example

`RAWSQLAGG_DATETIME(“MIN(%1)”, [Delivery Date])`

#### RAWSQLAGG_INT(“sql_expr”, [arg1,] …[argN])

Returns an integer result from a given aggregate SQL expression. The SQL expression is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Sales].

#### Example

```RAWSQLAGG_INT(“500 + SUM(%1)”, [Sales])```

#### RAWSQLAGG_REAL(“sql_expr”, [arg1,] …[argN])

Returns a numeric result from a given aggregate SQL expression that is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Sales]

#### Example

`RAWSQLAGG_REAL(“SUM( %1)”, [Sales])`

#### RAWSQLAGG_STR(“sql_expr”, [arg1,] …[argN])

Returns a string from a given aggregate SQL expression that is passed directly to the underlying database. Use %n in the SQL expression as a substitution syntax for database values. In this example, %1 is equal to [Discount].

#### Example

```RAWSQLAGG_STR(“AVG(%1)”, [Discount])```

#### REGEXP_REPLACE(string, pattern, replacement)

Returns a copy of the given string where the regular expression pattern is replaced by the replacement string. This function is available for Text File, Hadoop Hive, Google BigQuery, PostgreSQL, Tableau Data Extract, Microsoft Excel, Salesforce, Vertica, Pivotal Greenplum, Teradata (version 14.1 and above), Snowflake and Oracle data sources.

For Tableau data extracts, the pattern and the replacement must be constants.

For information on regular expression syntax, see your data source's documentation. For Tableau extracts, regular expression syntax conforms to the standards of the ICU (International Components for Unicode), an open source project of mature C/C++ and Java libraries for Unicode support, software internationalisation and software globalisation. See the Regular Expressions(Link opens in a new window) page in the online ICU User Guide.

##### Example

REGEXP_REPLACE('abc 123', '\s', '-') = 'abc-123'

#### REGEXP_MATCH(string, pattern)

Returns true if a substring of the specified string matches the regular expression pattern. This function is available for Text File, Google BigQuery, PostgreSQL, Tableau Data Extract, Microsoft Excel, Salesforce, Vertica, Pivotal Greenplum, Teradata (version 14.1 and above), Impala 2.3.0 (through Cloudera Hadoop data sources), Snowflake and Oracle data sources.

For Tableau data extracts, the pattern must be a constant.

For information on regular expression syntax, see your data source's documentation. For Tableau extracts, regular expression syntax conforms to the standards of the ICU (International Components for Unicode), an open source project of mature C/C++ and Java libraries for Unicode support, software internationalisation and software globalisation. See the Regular Expressions(Link opens in a new window) page in the online ICU User Guide.

##### Example

REGEXP_MATCH('-([1234].[The.Market])-','\[\s*(\w*\.)(\w*\s*\])')=true

#### REGEXP_EXTRACT(string, pattern)

Returns the portion of the string that matches the regular expression pattern. This function is available for Text File, Hadoop Hive, Google BigQuery, PostgreSQL, Tableau Data Extract, Microsoft Excel, Salesforce, Vertica, Pivotal Greenplum, Teradata (version 14.1 and above), Snowflake and Oracle data sources.

For Tableau data extracts, the pattern must be a constant.

For information on regular expression syntax, see your data source's documentation. For Tableau extracts, regular expression syntax conforms to the standards of the ICU (International Components for Unicode), an open source project of mature C/C++ and Java libraries for Unicode support, software internationalisation and software globalisation. See the Regular Expressions(Link opens in a new window) page in the online ICU User Guide.

##### Example

REGEXP_EXTRACT('abc 123', '[a-z]+\s+(\d+)') = '123'

#### REGEXP_EXTRACT_NTH(string, pattern, index)

Returns the portion of the string that matches the regular expression pattern. The substring is matched to the nth capturing group, where n is the given index. If index is 0, the entire string is returned. This function is available for Text File, PostgreSQL, Tableau Data Extract, Microsoft Excel, Salesforce, Vertica, Pivotal Greenplum, Teradata (version 14.1 and above) and Oracle data sources.

For Tableau data extracts, the pattern must be a constant.

For information on regular expression syntax, see your data source's documentation. For Tableau extracts, regular expression syntax conforms to the standards of the ICU (International Components for Unicode), an open source project of mature C/C++ and Java libraries for Unicode support, software internationalisation and software globalisation. See the Regular Expressions(Link opens in a new window) page in the online ICU User Guide.

##### Example

REGEXP_EXTRACT_NTH('abc 123', '([a-z]+)\s+(\d+)', 2) = '123'

#### REPLACE(string, substring, replacement)

Searches `string` for `substring` and replaces it with `replacement`. If `substring` is not found, the string is not changed.

##### Example

`REPLACE("Version8.5", "8.5", "9.0") = "Version9.0"`

#### RIGHT(string, number)

Returns the right-most number of characters in `string`.

##### Example

```RIGHT("Calculation", 4) = "tion"```

#### ROUND(number, [decimals])

Rounds numbers to a specified number of digits. The `decimals` argument specifies how many decimal points of precision to include in the final result. If `decimals` is omitted, `number` is rounded to the nearest integer.

##### Example

This example rounds every `Sales` value to an integer:

`ROUND(Sales)`

Some databases, such as SQL Server, allow specification of a negative `length`, where -1 rounds `number` to 10's, -2 rounds to 100's and so on. This is not true of all databases. For example, it is not true of Excel or Access.

#### RTRIM(string)

Returns `string` with any trailing spaces removed.

##### Example

```RTRIM(" Calculation ") = " Calculation"```

#### RTRIM_THIS(string, string)

Note : Supported only when connected to Google BigQuery

Returns the first string with any trailing occurrence of the second string removed.

##### Example

RTRIM_THIS('[-Market-]','-]') = '[-Market'

#### RUNNING_AVG(expression)

Returns the running average of the given expression, from the first row in the partition to the current row.

The view below shows quarterly sales. When `RUNNING_AVG(SUM([Sales])` is computed within the Date partition, the result is a running average of the sales values for each quarter.

##### Example

`RUNNING_AVG(SUM([Profit]))` computes the running average of SUM(Profit).

#### RUNNING_COUNT(expression)

Returns the running count of the given expression, from the first row in the partition to the current row.

##### Example

`RUNNING_COUNT(SUM([Profit]))` computes the running count of SUM(Profit).

#### RUNNING_MAX(expression)

Returns the running maximum of the given expression, from the first row in the partition to the current row.

##### Example

`RUNNING_MAX(SUM([Profit]))` computes the running maximum of SUM(Profit).

#### RUNNING_MIN(expression)

Returns the running minimum of the given expression, from the first row in the partition to the current row.

##### Example

`RUNNING_MIN(SUM([Profit]))` computes the running minimum of SUM(Profit).

#### RUNNING_SUM(expression)

Returns the running sum of the given expression, from the first row in the partition to the current row.

##### Example

`RUNNING_SUM(SUM([Profit]))` computes the running sum of SUM(Profit)

#### SCRIPT_BOOL

Returns a Boolean result from the specified expression. The expression is passed directly to a running external service instance.

In R expressions, use .argn (with a leading dot) to reference parameters (.arg1, .arg2, etc.).

In Python expressions, use _argn (with a leading underscore).

##### Examples

In this R example, .arg1 is equal to SUM([Profit]):

`SCRIPT_BOOL("is.finite(.arg1)", SUM([Profit]))`

The next example returns True for store IDs in Washington state, and False otherwise. This example could be the definition for a calculated field titled IsStoreInWA.

`SCRIPT_BOOL('grepl(".*_WA", .arg1, perl=TRUE)',ATTR([Store ID]))`

A command for Python would take this form:

`SCRIPT_BOOL("return map(lambda x : x > 0, _arg1)", SUM([Profit]))`

#### SCRIPT_INT

Returns an integer result from the specified expression. The expression is passed directly to a running external service instance.

In R expressions, use .argn (with a leading dot) to reference parameters (.arg1, .arg2, etc.)

In Python expressions, use _argn (with a leading underscore).

##### Examples

In this R example, .arg1 is equal to SUM([Profit]):

`SCRIPT_INT("is.finite(.arg1)", SUM([Profit]))`

In the next example, k-means clustering is used to create three clusters:

`SCRIPT_INT('result <- kmeans(data.frame(.arg1,.arg2,.arg3,.arg4), 3);result\$cluster;', SUM([Petal length]), SUM([Petal width]),SUM([Sepal length]),SUM([Sepal width]))`

A command for Python would take this form:

`SCRIPT_INT("return map(lambda x : int(x * 5), _arg1)", SUM([Profit]))`

#### SCRIPT_REAL

Returns a real result from the specified expression. The expression is passed directly to a running external service instance. In

R expressions, use .argn (with a leading dot) to reference parameters (.arg1, .arg2, etc.)

In Python expressions, use _argn (with a leading underscore).

##### Examples

In this R example, .arg1 is equal to SUM([Profit]):

`SCRIPT_REAL("is.finite(.arg1)", SUM([Profit]))`

The next example converts temperature values from Celsius to Fahrenheit.

`SCRIPT_REAL('library(udunits2);ud.convert(.arg1, "celsius", "degree_fahrenheit")',AVG([Temperature]))`

A command for Python would take this form:

`SCRIPT_REAL("return map(lambda x : x * 0.5, _arg1)", SUM([Profit]))`

#### SCRIPT_STR

Returns a string result from the specified expression. The expression is passed directly to a running external service instance.

In R expressions, use .argn (with a leading dot) to reference parameters (.arg1, .arg2, etc.)

In Python expressions, use _argn (with a leading underscore).

##### Examples

In this R example, .arg1 is equal to SUM([Profit]):

`SCRIPT_STR("is.finite(.arg1)", SUM([Profit]))`

The next example extracts a state abbreviation from a more complicated string (in the original form 13XSL_CA, A13_WA):

`SCRIPT_STR('gsub(".*_", "", .arg1)',ATTR([Store ID]))`

A command for Python would take this form:

`SCRIPT_STR("return map(lambda x : x[:2], _arg1)", ATTR([Region]))`

#### SIGN(number)

Returns the sign of a number: The possible return values are -1 if the number is negative, 0 if the number is zero or 1 if the number is positive.

##### Example

If the average of the profit field is negative, then

```SIGN(AVG(Profit)) = -1```

#### SIN(number)

Returns the sine of an angle. Specify the angle in radians.

##### Example

```SIN(0) = 1.0```

`SIN(PI( )/4) = 0.707106781186548`

#### SIZE()

Returns the number of rows in the partition. For example, the view below shows quarterly sales. Within the Date partition, there are seven rows, so the Size() of the Date partition is 7.

##### Example

`SIZE() = 5` when the current partition contains five rows.

#### SPACE(number)

Returns a string that is composed of the specified `number` of repeated spaces.

##### Example

`SPACE(1) = " "`

#### SPLIT(string, delimiter, token number)

Returns a substring from a string, using a delimiter character to divide the string into a sequence of tokens.

The string is interpreted as an alternating sequence of delimiters and tokens. So for the string `abc-defgh-i-jkl`, where the delimiter character is ‘-‘, the tokens are abc, defgh, i and jlk. Think of these as tokens 1 to 4. SPLIT returns the token corresponding to the token number. When the token number is positive, tokens are counted starting from the left end of the string; when the token number is negative, tokens are counted starting from the right.

##### Examples

`SPLIT (‘a-b-c-d’, ‘-‘, 2) = ‘b’`

`SPLIT (‘a|b|c|d’, ‘|‘, -2) = ‘c’`

Note: The split and custom split commands are available for the following data sources types: Tableau data extracts, Microsoft Excel, Text File, PDF File, Salesforce, OData, Microsoft Azure Market Place, Google Analytics, Vertica, Oracle, MySQL, PostgreSQL, Teradata, Amazon Redshift, Aster Data, Google Big Query, Cloudera Hadoop Hive, Hortonworks Hive and Microsoft SQL Server.

Some data sources impose limits on splitting string. The following table shows which data sources support negative token numbers (splitting from the right) and whether there is a limit on the number of splits allow per data source. A SPLIT function that specifies a negative token number and would be legal with other data sources will return this error with these data sources: “Splitting from right is not support by the data source.”

 Data Source Left/Right Constraints Maximum Number of Splits Version Limitations Tableau Data Extract Both Infinite Microsoft Excel Both Infinite Text file Both Infinite Salesforce Both Infinite OData Both Infinite Google Analytics Both Infinite Tableau Data Server Both Infinite Supported in version 9.0. Vertica Left only 10 Oracle Left only 10 MySQL Both 10 PostgreSQL Left only prior to version 9.0; both for version 9.0 and above 10 Teradata Left only 10 Version 14 and later Amazon Redshift Left only 10 Aster Database Left only 10 Google BigQuery Left only 10 Hortonworks Hadoop Hive Left only 10 Cloudera Hadoop Left only 10 Impala supported starting in version 2.3.0. Microsoft SQL Server Both 10 2008 and later

#### SQRT(number)

Returns the square root of a number.

##### Example

`SQRT(25) = 5`

#### SQUARE(number)

Returns the square of a number.

Example

`SQUARE(5) = 25`

#### STARTSWITH(string, substring)

Returns true if `string` starts with `substring`. Leading white spaces are ignored.

##### Example

```STARTSWITH(“Joker”, “Jo”) = true```

#### STDEV(expression)

Returns the statistical standard deviation of all values in the given expression based on a sample of the population.

#### STDEVP(expression)

Returns the statistical standard deviation of all values in the given expression based on a biased population.

#### STR(expression)

Casts its argument as a string.

##### Example

`STR([Age])` takes all of the values in the measure called `Age` and converts them to strings.

#### SUM(expression)

Returns the sum of all values in the expression. SUM can be used with numeric fields only. Null values are ignored.

#### TAN(number)

Returns the tangent of an angle. Specify the angle in radians.

##### Example

```TAN(PI ( )/4) = 1.0```

#### TIMESTAMP_TO_USEC(expression)

Note : Supported only when connected to Google BigQuery

Converts a TIMESTAMP data type to a UNIX timestamp in microseconds.

##### Example

TIMESTAMP_TO_USEC(#2012-10-01 01:02:03#)=1349053323000000

#### TLD(string_url)

Note : Supported only when connected to Google BigQuery

Given a URL string, returns the top level domain plus any country domain in the URL.

#### TODAY( )

Returns the current date.

##### Example

`TODAY( ) = 2004-04-15`

#### TOTAL(expression)

Returns the total for the given expression in a table calculation partition.

##### Example

Assume you are starting with this view:

You open the calculation editor and create a new field which you name Totality:

You then drop Totality on Text, to replace SUM(Sales). Your view changes such that it sums values based on the default Compute Using value:

This raises the question, What is the default Compute Using value? If you right-click (Control-click on a Mac) Totality in the Data pane and choose Edit, there is now an additional bit of information available:

The default Compute Using value is Table (Across). The result is that Totality is summing the values across each row of your table. Thus, the value that you see across each row is the sum of the values from the original version of the table.

The values in the 2011/Q1 row in the original table were \$8601, \$6579, \$44262 and \$15006. The values in the table after Totality replaces SUM(Sales) are all \$74,448, which is the sum of the four original values.

Notice the triangle next to Totality after you drop it on Text:

This indicates that this field is using a table calculation. You can right-click the field and choose Edit Table Calculation to redirect your function to a different Compute Using value. For example, you could set it to Table (Down). In that case, your table would look like this:

#### TRIM(string)

Returns the string with leading and trailing spaces removed. For example, ```TRIM(" Calculation ") = "Calculation"```

#### UPPER(string)

Returns string, with all characters uppercase.

##### Example

`UPPER("Calculation") = "CALCULATION"`

#### USEC_TO_TIMESTAMP(expression)

Note : Supported only when connected to Google BigQuery

Converts a UNIX timestamp in microsseconds to a TIMESTAMP data type.

##### Example

USEC_TO_TIMESTAMP(1349053323000000) = #2012-10-01 01:02:03#

#### USERDOMAIN()

Returns the domain for the current user when the user is signed on to Tableau Server. Returns the Windows domain if the Tableau Desktop user is on a domain. Otherwise this function returns a null string.

##### Example

`[Manager]=USERNAME() AND [Domain]=USERDOMAIN()`

Returns the username for the current user. This is the Tableau Server or Tableau Online username when the user is signed in; otherwise it is the local or network username for the Tableau Desktop user.

##### Example

`[Manager]=USERNAME( )`

If the manager dhallsten was signed in, this function would only return True when the Manager field in the view is dhallsten. When used as a filter this calculated field can be used to create a user filter that only shows data that is relevant to the person signed in to the server.

#### VAR(expression)

Returns the statistical variance of all values in the given expression based on a sample of the population.

#### VARP(expression)

Returns the statistical variance of all values in the given expression on the entire population.

#### WINDOW_AVG(expression, [start, end])

Returns the average of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

For example, the view below shows quarterly sales. A window average within the Date partition returns the average sales across all dates.

##### Example

`WINDOW_AVG(SUM([Profit]), FIRST()+1, 0)` computes the average of SUM(Profit) from the second row to the current row.

#### WINDOW_CORR(expression1, expression2, [start, end])

Returns the Pearson correlation coefficient of two expressions within the window. The window is defined as offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If start and end are omitted, the entire partition is used.

The Pearson correlation measures the linear relationship between two variables. Results range from -1 to +1 inclusive, where 1 denotes an exact positive linear relationship, as when a positive change in one variable implies a positive change of corresponding magnitude in the other, 0 denotes no linear relationship between the variance and −1 is an exact negative relationship.

There is an equivalent aggregation fuction: CORR.

##### Example

The following formula returns the Pearson correlation of SUM(Profit) and SUM(Sales) from the five previous rows to the current row.

`WINDOW_CORR(SUM[Profit]), SUM([Sales]), -5, 0)`

#### WINDOW_COUNT(expression, [start, end])

Returns the count of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

##### Example

`WINDOW_COUNT(SUM([Profit]), FIRST()+1, 0)` computes the count of SUM(Profit) from the second row to the current row

#### WINDOW_COVAR(expression1, expression2, [start, end])

Returns the sample covariance of two expressions within the window. The window is defined as offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end arguments are omitted, the window is the entire partition.

Sample covariance uses the number of non-null data points n - 1 to normalise the covariance calculation, rather than n, which is used by the population covariance (with the WINDOW_COVARP function). Sample covariance is the appropriate choice when the data is a random sample that is being used to estimate the covariance for a larger population.

There is an equivalent aggregation fuction: COVAR.

##### Example

The following formula returns the sample covariance of SUM(Profit) and SUM(Sales) from the two previous rows to the current row.

`WINDOW_COVAR(SUM([Profit]), SUM([Sales]), -2, 0)`

#### WINDOW_COVARP(expression1, expression2, [start, end])

Returns the population covariance of two expressions within the window. The window is defined as offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If start and end are omitted, the entire partition is used.

Population covariance is sample covariance multiplied by (n-1)/n, where n is the total number of non-null data points. Population covariance is the appropriate choice when there is data available for all items of interest as opposed to when there is only a random subset of items, in which case sample covariance (with the WINDOW_COVAR function) is appropriate.

There is an equivalent aggregation fuction: COVARP. See Tableau Functions (Alphabetical)(Link opens in a new window).

##### Example

The following formula returns the population covariance of SUM(Profit) and SUM(Sales) from the two previous rows to the current row.

`WINDOW_COVARP(SUM([Profit]), SUM([Sales]), -2, 0)`

#### WINDOW_MEDIAN(expression, [start, end])

Returns the median of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

For example, the view below shows quarterly profit. A window median within the Date partition returns the median profit across all dates.

##### Example

`WINDOW_MEDIAN(SUM([Profit]), FIRST()+1, 0)` computes the median of SUM(Profit) from the second row to the current row.

#### WINDOW_MAX(expression, [start, end])

Returns the maximum of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

For example, the view below shows quarterly sales. A window maximum within the Date partition returns the maximum sales across all dates.

##### Example

`WINDOW_MAX(SUM([Profit]), FIRST()+1, 0)` computes the maximum of SUM(Profit) from the second row to the current row.

#### WINDOW_MIN(expression, [start, end])

Returns the minimum of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

For example, the view below shows quarterly sales. A window minimum within the Date partition returns the minimum sales across all dates.

##### Example

`WINDOW_MIN(SUM([Profit]), FIRST()+1, 0)` computes the minimum of SUM(Profit) from the second row to the current row.

#### WINDOW_PERCENTILE(expression, number, [start, end])

Returns the value corresponding to the specified percentile within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

##### Example

`WINDOW_PERCENTILE(SUM([Profit]), 0.75, -2, 0)` returns the 75th percentile for SUM(Profit) from the two previous rows to the current row.

#### WINDOW_STDEV(expression, [start, end])

Returns the sample standard deviation of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

##### Example

`WINDOW_STDEV(SUM([Profit]), FIRST()+1, 0)` computes the standard deviation of SUM(Profit) from the second row to the current row.

#### WINDOW_STDEVP(expression, [start, end])

Returns the biased standard deviation of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

##### Example

`WINDOW_STDEVP(SUM([Profit]), FIRST()+1, 0)` computes the standard deviation of SUM(Profit) from the second row to the current row.

#### WINDOW_SUM(expression, [start, end])

Returns the sum of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

For example, the view below shows quarterly sales. A window sum computed within the Date partition returns the summation of sales across all quarters.

##### Example

`WINDOW_SUM(SUM([Profit]), FIRST()+1, 0)` computes the sum of SUM(Profit) from the second row to the current row.

#### WINDOW_VAR(expression, [start, end])

Returns the sample variance of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

##### Example

`WINDOW_VAR((SUM([Profit])), FIRST()+1, 0)` computes the variance of SUM(Profit) from the second row to the current row.

#### WINDOW_VARP(expression, [start, end])

Returns the biased variance of the expression within the window. The window is defined by means of offsets from the current row. Use FIRST()+n and LAST()-n for offsets from the first or last row in the partition. If the start and end are omitted, the entire partition is used.

##### Example

`WINDOW_VARP(SUM([Profit]), FIRST()+1, 0)` computes the variance of SUM(Profit) from the second row to the current row.

#### XPATH_BOOLEAN(XML string, XPath expression string)

Note: Supported only when connected to Hadoop Hive

Returns true if the XPath expression matches a node or evaluates to true.

##### Example

XPATH_BOOLEAN('<values> <value id="0">1</value><value id="1">5</value>', 'values/value[@id="1"] = 5') = true

#### XPATH_DOUBLE(XML string, XPath expression string)

Note: Supported only when connected to Hadoop Hive

Returns the floating-point value of the XPath expression.

##### Example

XPATH_DOUBLE('<values><value>1.0</value><value>5.5</value> </values>', 'sum(value/*)') = 6.5

#### XPATH_FLOAT(XML string, XPath expression string)

Note: Supported only when connected to Hadoop Hive

Returns the floating-point value of the XPath expression.

##### Example

XPATH_FLOAT('<values><value>1.0</value><value>5.5</value> </values>','sum(value/*)') = 6.5

#### XPATH_INT(XML string, XPath expression string)

Note: Supported only when connected to Hadoop Hive

Returns the numerical value of the XPath expression, or zero if the XPath expression cannot evaluate to a number.

##### Example

XPATH_INT('<values><value>1</value><value>5</value> </values>','sum(value/*)') = 6

#### XPATH_LONG(XML string, XPath expression string)

Note: Supported only when connected to Hadoop Hive

Returns the numerical value of the XPath expression, or zero if the XPath expression cannot evaluate to a number.

##### Example

XPATH_LONG('<values><value>1</value><value>5</value> </values>','sum(value/*)') = 6

#### XPATH_SHORT(XML string, XPath expression string)

Note: Supported only when connected to Hadoop Hive

Returns the numerical value of the XPath expression, or zero if the XPath expression cannot evaluate to a number.

##### Example

XPATH_SHORT('<values><value>1</value><value>5</value> </values>','sum(value/*)') = 6

#### XPATH_STRING(XML string, XPath expression string)

Note: Supported only when connected to Hadoop Hive

Returns the text of the first matching node.

##### Example

XPATH_STRING('<sites ><url domain="org">http://www.w3.org</url> <url domain="com">http://www.tableau.com</url></sites>', 'sites/url[@domain="com"]') = 'http://www.tableau.com'

#### YEAR (date)

Returns the year of the given date as an integer.

##### Example

`YEAR(#2004-04-15#) = 2004`

#### ZN(expression)

Returns the expression if it is not null, otherwise returns zero. Use this function to use zero values instead of null values.

##### Example

`ZN([Profit]) = [Profit]`