Table A and Table X are unrelated
Table B and Table X are unrelated
Table A and Table X are unrelated | Table B and Table X are unrelated |
| |
Table A and Table S are related | Table B and Table S are related (through Table A) |
 |  |
| Not yet related | Ambiguously related | Relatedness resolved to a single tree | |
| Related through base Table A | Related through base Table X | ||
 |  |  |  |
Stitching | Resolving uncertainty |
 Unrelated FieldA and FieldX stitched by DimensionS | FieldS and FieldT evaluated through the tree defined by base Table A |
| Juxtaposes unrelated fields based on shared attributes | Narrows down which relationship path to use when there are multiple options (ambiguity or a shared measure), or establishes a relationship path when there wasn't one (not yet related). |
Uses multiple base table logic to calculate results | Uses single base table logic to calculate results |
| Analysis involves unrelated tables | Analysis involves shared tables |
Classes | Clubs | Students |
 |  |  |
Fields:
| Fields:
| Fields:
|
| Resolved Issue | Fixed as of |
Extracts Local data source (in a workbook): Attempting to extract a multi-fact relationship data source will give a "No such table" error. Published data source: Extracting a published multi-fact relationship data source appears to succeed, but field values can be swapped. |
If you still see these issues in Tableau Desktop or Tableau Server, upgrade to a version from 24th July 2024 or later. |
EXCLUDE Level of Detail expressions Only INCLUDE LODs should be validated in the presence of unrelated fields. However, EXCLUDE LODs may also be incorrectly marked as not valid in the same conditions. | |
Nested user calculations Nested user calculations are not available in published data sources with a multi-fact relationship data model. |
Double-click on an existing field to start editing. |  |
| You can also double-click on an empty shelf or on an empty part of a shelf to create a new calculation. |  |
| Type to update the expression, or drag new fields into the expression from the Data pane or elsewhere in the view. |  |
Press Enter, Tab, or click outside the expression to commit the expression, close the calculation, and update the view. Press Ctrl+Enter (or Command+Enter on a Mac) to commit the expression and update the view without closing the calculation. |  |
| Product Name | Product Image URL | Product Sales |
| Flats | https://img.example.com/flats.png | 12,118 |
| High Heels | https://img.example.com/highheels.png | 15,865 |
| Running Shoes | https://img.example.com/runningshoes.png | 14,200 |
| Wedges | https://img.example.com/wedges.png | 8,665 |
| Syntax | REGEXP_REPLACE(string, pattern, replacement) |
| Output | String |
| Definition | Returns a copy of the given string where the regular expression pattern is replaced by the replacement string. |
| Example | REGEXP_REPLACE('abc 123', '\s', '-') = 'abc-123' |
| Notes | 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. |
| Syntax | REGEXP_MATCH(string, pattern) |
| Output | Boolean |
| Definition | Returns true if a substring of the specified string matches the regular expression pattern. |
| Example | REGEXP_MATCH('-([1234].[The.Market])-','\[\s*(\w*\.)(\w*\s*\])')=true |
| Notes | 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. |
| Syntax | REGEXP_EXTRACT(string, pattern) |
| Output | String |
| Definition | Returns the portion of the string that matches the regular expression pattern. |
| Example | REGEXP_EXTRACT('abc 123', '[a-z]+\s+(\d+)') = '123' |
| Notes | 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. |
| Syntax | REGEXP_EXTRACT_NTH(string, pattern, index) |
| Output | String |
| Definition | 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. |
| Example | REGEXP_EXTRACT_NTH('abc 123', '([a-z]+)\s+(\d+)', 2) = '123' |
| Notes | 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. |
| Syntax | ATTR(expression) |
| Definition | Returns the value of the expression if it has a single value for all rows. Otherwise returns an asterisk. Null values are ignored. |
| Syntax | AVG(expression) |
| Definition | Returns the average of all the values in the expression. Null values are ignored. |
| Notes | AVG can only be used with numeric fields. |
| Syntax | COLLECT(spatial) |
| Definition | An aggregate calculation that combines the values in the argument field. Null values are ignored. |
| Notes | COLLECT can only be used with spatial fields. |
| Syntax | CORR(expression1, expression2) |
| Output | Number from -1 to 1 |
| Definition | Returns the Pearson correlation coefficient of two expressions. |
| Example | example |
| Notes | 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, 0 denotes no linear relationship between the variance and −1 is an exact negative relationship. The square of a CORR result is equivalent to the R-Squared value for a linear trend line model. See Trend Line Model Terms. Use with table-scoped LOD expressions: You can use CORR to visualise correlation in a disaggregated scatter using 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 |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | COUNT(expression) |
| Definition | Returns the number of items. Null values are not counted. |
| Syntax | COUNTD(expression) |
| Definition | Returns the number of distinct items in a group. Null values are not counted. |
| Syntax | COVAR(expression1, expression2) |
| Definition | Returns the sample covariance of two expressions. |
| Notes | 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 If The value of |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | COVARP(expression 1, expression2) |
| Definition | Returns the population covariance of two expressions. |
| Notes | 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 If |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MEDIAN(expression) |
| Definition | Returns the median of an expression across all records. Null values are ignored. |
| Notes | MEDIAN can only be used with numeric fields. |
| Database limitations |
For other data source types, you can extract your data into an extract file to use this function. See Extract Your Data. |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | PERCENTILE(expression, number) |
| Definition | Returns the percentile value from the given expression corresponding to the specified <number>. The <number> must be between 0 and 1 (inclusive) and must be a numeric constant. |
| Example | PERCENTILE([Score], 0.9) |
| Database limitations | 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, EXASolution 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. |
| Syntax | STDEV(expression) |
| Definition | Returns the statistical standard deviation of all values in the given expression based on a sample of the population. |
| Syntax | STDEVP(expression) |
| Definition | Returns the statistical standard deviation of all values in the given expression based on a biased population. |
| Syntax | SUM(expression) |
| Definition | Returns the sum of all values in the expression. Null values are ignored. |
| Notes | SUM can only be used with numeric fields. |
| Syntax | VAR(expression) |
| Definition | Returns the statistical variance of all values in the given expression based on a sample of the population. |
| Syntax | VARP(expression) |
| Definition | Returns the statistical variance of all values in the given expression on the entire population. |
| Syntax | ABS(number) |
| Output | Number (positive) |
| Definition | Returns the absolute value of the given <number>. |
| Example | ABS(-7) = 7 The second example returns the absolute value for all the numbers contained in the Budget Variance field. |
| Notes | See also SIGN. |
| Syntax | ACOS(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arccosine (angle) of the given <number>. |
| Example | ACOS(-1) = 3.14159265358979 |
| Notes | The inverse function, COS, takes the angle in radians as the argument and returns the cosine. |
| Syntax | <expr1> AND <expr2> |
| Definition | Performs a logical conjunction on two expressions. (If both sides are true, the logical test returns true.) |
| Output | Boolean |
| Example | IF [Season] = "Spring" AND "[Season] = "Fall" "If both (Season = Spring) and (Season = Fall) are true simultaneously, then return It's the apocalypse and footwear doesn't matter." |
| Notes | Often used with IF and IIF. See also NOT and OR. If both expressions are If you create a calculation in which the result of an Note: The |
| Syntax | AREA(Spatial Polygon, 'units') |
| Output | Number |
| Definition | Returns the total surface area of a <spatial polygon>. |
| Example | AREA([Geometry], 'feet') |
| Notes | Supported unit names (must be in quotation marks in the calculation, such as
|
| Syntax | ASCII(string) |
| Output | Number |
| Definition | Returns the ASCII code for the first character of a <string>. |
| Example | ASCII('A') = 65 |
| Notes | This is the inverse of the CHAR function. |
| Syntax | ASIN(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arcsine (angle) of a given <number>. |
| Example | ASIN(1) = 1.5707963267949 |
| Notes | The inverse function, SIN, takes the angle in radians as the argument and returns the sine. |
| Syntax | ATAN(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arctangent (angle) of a given <number>. |
| Example | ATAN(180) = 1.5652408283942 |
| Notes | The inverse function, |
| Syntax | ATAN2(y number, x number) |
| Output | Number (angle in radians) |
| Definition | Returns the arctangent (angle) between two numbers (<y number> and <x number>). The result is in radians. |
| Example | ATAN2(2, 1) = 1.10714871779409 |
| Notes | See also ATAN, TAN and COT. |
| Syntax | ATTR(expression) |
| Definition | Returns the value of the <expression> if it has a single value for all rows. Otherwise returns an asterisk. Null values are ignored. |
| Syntax | AVG(expression) |
| Definition | Returns the average of all the values in the <expression>. Null values are ignored. |
| Notes | AVG can only be used with numeric fields. |
| Syntax | BUFFER(Spatial Point, distance, 'units') |
| Output | Geometry |
| Definition | Returns a polygon shape centred over a <spatial point>, with a radius determined by the <distance> and <unit> values. |
| Example | BUFFER([Spatial Point Geometry], 25, 'mi') BUFFER(MAKEPOINT(47.59, -122.32), 3, 'km') |
| Notes | Supported unit names (must be in quotation marks in the calculation, such as
|
| Syntax | CASE <expression>
|
| Output | Depends on data type of the <then> values. |
| Definition | Evaluates the |
| Example | "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes | Used with WHEN, THEN, ELSE and END.
|
| Syntax | CEILING(number) |
| Output | Integer |
| Definition | Rounds a <number> to the nearest integer of equal or greater value. |
| Example | CEILING(2.1) = 3 |
| Notes | See also FLOOR and ROUND. |
| Database limitations |
|
| Syntax | CHAR(number) |
| Output | String |
| Definition | Returns the character encoded by the ASCII code <number>. |
| Example | CHAR(65) = 'A' |
| Notes | This is the inverse of the ASCII function. |
| Syntax | COLLECT(spatial) |
| Definition | An aggregate calculation that combines the values in the argument field. Null values are ignored. |
| Notes | COLLECT can only be used with spatial fields. |
| Syntax | CONTAINS(string, substring) |
| Output | Boolean |
| Definition | Returns true if the given <string> contains the specified <substring>. |
| Example | CONTAINS("Calculation", "alcu") = true |
| Notes | See also the logical function IN as well as supported RegEx in the additional functions documentation. |
| Syntax | CORR(expression1, expression2) |
| Output | Number from -1 to 1 |
| Definition | Returns the Pearson correlation coefficient of two expressions. |
| Example | example |
| Notes | 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, 0 denotes no linear relationship between the variance and −1 is an exact negative relationship. The square of a CORR result is equivalent to the R-Squared value for a linear trend line model. See Trend Line Model Terms. Use with table-scoped LOD expressions: You can use CORR to visualise correlation in a disaggregated scatter using 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 |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | COS(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the cosine of an angle. |
| Example | COS(PI( ) /4) = 0.707106781186548 |
| Notes | The inverse function, See also |
| Syntax | COT(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the cotangent of an angle. |
| Example | COT(PI( ) /4) = 1 |
| Notes | See also ATAN, TAN and PI. |
| Syntax | COUNT(expression) |
| Definition | Returns the number of items. Null values are not counted. |
| Syntax | COUNTD(expression) |
| Definition | Returns the number of distinct items in a group. Null values are not counted. |
| Syntax | COVAR(expression1, expression2) |
| Definition | Returns the sample covariance of two expressions. |
| Notes | 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 If The value of |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | COVARP(expression 1, expression2) |
| Definition | Returns the population covariance of two expressions. |
| Notes | 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 If |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | DATE(expression) |
| Output | Date |
| Definition | Returns a date given a number, string or date <expression>. |
| Example | DATE([Employee Start Date]) DATE("September 22, 2018") DATE("9/22/2018")DATE(#2018-09-22 14:52#) |
| Notes | Unlike
|
| Syntax | DATEADD(date_part, interval, date) |
| Output | Date |
| Definition | Returns the specified date with the specified number <interval> added to the specified ><date_part of that date. For example, adding three months or 12 days to a starting date. |
| Example | Push out all due dates by one week DATEADD('week', 1, [due date])Add 280 days to the date February 20, 2021 DATEADD('day', 280, #2/20/21#) = #November 27, 2021# |
| Notes | Supports ISO 8601 dates. |
| Syntax | DATEDIFF(date_part, date1, date2, [start_of_week]) |
| Output | Integer |
| Definition | Returns the difference between date1 and date2 expressed in units of date_part. For example, subtracting the dates someone entered and left a band to see how long they were in the band. |
| Example | Number of days between 25th March 1986 and 20th February 2021 DATEDIFF('day', #3/25/1986#, #2/20/2021#) = 12,751How many months someone was in a band DATEDIFF('month', [date joined band], [date left band]) |
| Notes | Supports ISO 8601 dates. |
| Syntax | DATENAME(date_part, date, [start_of_week]) |
| Output | String |
| Definition | Returns <date_part> of date as a string. |
| Example | DATENAME('year', #3/25/1986#) = "1986"DATENAME('month', #1986-03-25#) = "March" |
| Notes | Supports ISO 8601 dates. A very similar calculation is DATEPART, which returns the value of the specified date part as a continuous integer. By changing the attributes of the calculation’s result (dimension or measure, continuous or discrete) and the date formatting, the results of An inverse function is |
| Syntax | DATEPARSE(date_format, date_string) |
| Output | Date |
| Definition | The <date_format> argument describes how the <date_string> field is arranged. Because of the variety of ways the string field can be ordered, the <date_format> must match exactly. For a full explanation, see Convert a Field to a Date Field. |
| Example | DATEPARSE('yyyy-MM-dd', "1986-03-25") = #March 25, 1986# |
| Notes |
Inverse functions, which take dates apart and return the value of their parts, are |
| Database limitations |
|
| Syntax | DATEPART(date_part, date, [start_of_week]) |
| Output | Integer |
| Definition | Returns <date_part> of date as an integer. |
| Example | DATEPART('year', #1986-03-25#) = 1986DATEPART('month', #1986-03-25#) = 3 |
| Notes | Supports ISO 8601 dates. A very similar calculation is An inverse function is |
| Syntax | DATETIME(expression) |
| Output | Datetime |
| Definition | Returns a datetime given a number, string or date expression. |
| Example | DATETIME("April 15, 2005 07:59:00") = April 15, 2005 07:59:00 |
| Syntax | DATETRUNC(date_part, date, [start_of_week]) |
| Output | Date |
| Definition | Truncates the <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. |
| Example | DATETRUNC('day', #9/22/2018#) = #9/22/2018#DATETRUNC('iso-week', #9/22/2018#) = #9/17/2018#(the Monday of the week containing 22/09/2018) DATETRUNC(quarter, #9/22/2018#) = #7/1/2018# (the first day of the quarter containing 22/09/2018) Note: For week and iso-week, the |
| Notes | Supports ISO 8601 dates. You shouldn't use For example, |
| Syntax | DAY(date) |
| Output | Integer |
| Definition | Returns the day of the given <date> as an integer. |
| Example | Day(#September 22, 2018#) = 22 |
| Notes | See also WEEK, MONTH, Quarter, YEAR and the ISO equivalents |
| Syntax | DEGREES(number)The number argument is the angle in radians. |
| Output | Number (degrees) |
| Definition | Converts an angle in radians to degrees. |
| Example | DEGREES(PI( )/4) = 45.0 |
| Notes | The inverse function, See also |
| Syntax | DISTANCE(<SpatialPoint1>, <SpatialPoint2>, 'units') |
| Output | Number |
| Definition | Returns the distance measurement between two points in the specified units. |
| Example | DISTANCE([Origin Point],[Destination Point], 'km') |
| Notes | Supported unit names (must be in quotation marks in the calculation):
|
| Database limitations | This function can only be created with a live connection but will continue to work if the data source is converted to an extract. |
| Syntax | DIV(integer1, integer2) |
| Output | Integer |
| Definition | Returns the integer part of a division operation, in which <integer1> is divided by <integer2>. |
| Example | DIV(11,2) = 5 |
| Syntax | CASE <expression>
|
| Definition | An optional piece of an IF or CASE expression used to specify a default value to return if none of the tested expressions are true. |
| Example | IF [Season] = "Summer" THEN 'Sandals' CASE [Season] |
| Notes | Used with CASE, WHEN, IF, ELSEIF, THEN and END
|
| Syntax | [ELSEIF <test2> THEN <then2>] |
| Definition | An optional piece of an IF expression used to specify additional conditions beyond the initial IF. |
| Example | IF [Season] = "Summer" THEN 'Sandals' |
| Notes | Used with IF, THEN, ELSE and END
Unlike |
| Definition | Used to close an IF or CASE expression. |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes |
| Syntax | ENDSWITH(string, substring) |
| Output | Boolean |
| Definition | Returns true if the given <string> ends with the specified <substring>. Trailing white spaces are ignored. |
| Example | ENDSWITH("Tableau", "leau") = true |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | EXP(number) |
| Output | Number |
| Definition | Returns e raised to the power of the given <number>. |
| Example | EXP(2) = 7.389 |
| Notes | See also LN. |
| Syntax | FIND(string, substring, [start]) |
| Output | Number |
| Definition | Returns the index position of If the optional numeric argument |
| Example | FIND("Calculation", "alcu") = 2FIND("Calculation", "Computer") = 0FIND("Calculation", "a", 3) = 7FIND("Calculation", "a", 2) = 2FIND("Calculation", "a", 8) = 0 |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | FINDNTH(string, substring, occurrence) |
| Output | Number |
| Definition | Returns the position of the nth occurrence of <substring> within the specified <string>, where n is defined by the <occurence> argument. |
| Example | FINDNTH("Calculation", "a", 2) = 7 |
| Notes |
See also the supported RegEx in the additional functions documentation. |
| Syntax | FLOAT(expression) |
| Output | Floating point number (decimal) |
| Definition | Casts its argument as a floating point number. |
| Example | FLOAT(3) = 3.000 |
| Notes | See also INT, which returns an integer. |
| Syntax | FLOOR(number) |
| Output | Integer |
| Definition | Rounds a <number> to the nearest integer of equal or lesser value. |
| Example | FLOOR(7.9) = 7 |
| Notes | See also CEILING and ROUND. |
| Database limitations |
|
| Syntax | FULLNAME( ) |
| Output | String |
| Definition | Returns the full name for the current user. |
| Example | FULLNAME( ) This returns the full name of the signed-in user, such as "Hamlin Myrer". [Manager] = FULLNAME( ) If manager "Hamlin Myrer" is signed in, this example returns TRUE only if the Manager field in the view contains "Hamlin Myrer". |
| Notes | This function checks:
User filters When used as a filter, a calculated field such as |
| Syntax | HEXBINX(number, number) |
| Output | Number |
| Definition | 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. |
| Example | HEXBINX([Longitude]*2.5, [Latitude]*2.5) |
| Notes | 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. |
| Syntax | HEXBINY(number, number) |
| Output | Number |
| Definition | 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]*2.5, [Latitude]*2.5) |
| Notes | See also HEXBINX. |
| Syntax | IF <test1> THEN <then1> |
| Output | Depends on data type of the <then> values. |
| Definition | Tests a series of expressions and returns the |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." |
| Notes |
| Syntax | IFNULL(expr1, expr2) |
| Output | Depends on the data type of the <expr> values. |
| Definition | Returns |
| Example | IFNULL([Assigned Room], "TBD") "If the Assigned Room field isn't null, return its value. If the Assigned room field is null, return TBD instead." |
| Notes | Compare with ISNULL. See also ZN. |
| Syntax | IIF(<test>, <then>, <else>, [<unknown>]) |
| Output | Depends on the data type of the values in the expression. |
| Definition | Checks whether a condition is met (<test>) and returns <then> if the test is true, <else> if the test is false and an optional value for <unknown> if the test is null. If the optional unknown isn't specified, IIF returns null. |
| Example | IIF([Season] = 'Summer', 'Sandals', 'Other footwear') "If Season = Summer, then return Sandals. If not, return Other footwear" IIF([Season] = 'Summer', 'Sandals', "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither are true, return Sneakers." IIF('Season' = 'Summer', 'Sandals', "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If none of the expressions are true, return Sneakers." |
| Notes |
That is to say, in the calculation below, the result will be Red, not Orange, because the expression stops being evaluated as soon as A=A is evaluated as true:
|
| Syntax | <expr1> IN <expr2> |
| Output | Boolean (true or false) |
| Definition | Returns TRUE if any value in <expr1> matches any value in <expr2>. |
| Example | SUM([Cost]) IN (1000, 15, 200) "Is the value of the Cost field 1000, 15 or 200?" [Field] IN [Set] "Is the value of the field present in the set?" |
| Notes | The values in See also WHEN. |
| Syntax | INT(expression) |
| Output | Integer |
| Definition | Casts its argument as an integer. For expressions, this function truncates results to the closest integer toward zero. |
| Example | INT(8/3) = 2 INT(-9.7) = -9 |
| Notes | When a string is converted to an integer it is first converted to a float and then rounded. See also |
| Syntax | INTERSECTS (<geometry1>, <geometry2>) |
| Output | Boolean |
| Definition | Returns true or false indicating whether two geometries overlap in space. |
| Notes | Supported combinations: point/polygon, line/polygon and polygon/polygon. |
| Syntax | ISDATE(string) |
| Output | Boolean |
| Definition | Returns true if a given <string> is a valid date. |
| Example | ISDATE(09/22/2018) = true ISDATE(22SEP18) = false |
| Notes | The required argument must be a string. ISDATE cannot be used for a field with a date data type – the calculation will return an error. |
| Syntax | ISFULLNAME("User Full Name") |
| Output | Boolean |
| Definition | Returns |
| Example | ISFULLNAME("Hamlin Myrer") |
| Notes | The This function checks:
|
| Syntax | ISMEMBEROF("Group Name") |
| Output | Boolean or null |
| Definition | Returns |
| Example | ISMEMBEROF('Superstars')ISMEMBEROF('domain.lan\Sales') |
| Notes | The If the user is signed in to Tableau Cloud or Tableau Server, group membership is determined by Tableau groups. The function will return TRUE if the given string is "All Users" The |
| Syntax | ISNULL(expression) |
| Output | Boolean (true or false) |
| Definition | Returns true if the |
| Example | ISNULL([Assigned Room]) "Is the Assigned Room field null?" |
| Notes | Compare with IFNULL. See also ZN. |
| Syntax | ISOQUARTER(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based quarter of a given <date> as an integer. |
| Example | ISOQUARTER(#1986-03-25#) = 1 |
| Notes | See also ISOWEEK, ISOWEEKDAY, ISOYEAR and the non-ISO equivalents. |
| Syntax | ISOWEEK(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based week of a given <date> as an integer. |
| Example | ISOWEEK(#1986-03-25#) = 13 |
| Notes | See also ISOWEEKDAY, ISOQUARTER, ISOYEAR and the non-ISO equivalents. |
| Syntax | ISOWEEKDAY(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based weekday of a given <date> as an integer. |
| Example | ISOWEEKDAY(#1986-03-25#) = 2 |
| Notes | See also ISOWEEK, ISOQUARTER, ISOYEAR and the non-ISO equivalents |
| Syntax | ISOYEAR(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based year of a given date as an integer. |
| Example | ISOYEAR(#1986-03-25#) = 1,986 |
| Notes | See also ISOWEEK, ISOWEEKDAY, ISOQUARTER and the non-ISO equivalents. |
| Syntax | ISUSERNAME("username") |
| Output | Boolean |
| Definition | Returns TRUE if the current user's username matches the specified <username> or FALSE if it does not match. |
| Example | ISUSERNAME("hmyrer") |
| Notes | The This function checks:
|
| Syntax | LEFT(string, number) |
| Output | String |
| Definition | Returns the left-most <number> of characters in the string. |
| Example | LEFT("Matador", 4) = "Mata" |
| Notes | See also MID and RIGHT. |
| Syntax | LEN(string) |
| Output | Number |
| Definition | Returns the length of the <string>. |
| Example | LEN("Matador") = 7 |
| Notes | Not to be confused with the spatial function LENGTH. |
| Syntax | LENGTH(geometry, 'units') |
| Output | Number |
| Definition | Returns the geodetic path length of the line string or strings in the <geometry> using the given <units>. |
| Example | LENGTH([Spatial], 'metres') |
| Notes | The result is Not to be confused with the string function |
| Syntax | LN(number) |
| Output | Number The output is |
| Definition | Returns the natural logarithm of a <number>. |
| Example | LN(50) = 3.912023005 |
| Notes | See also EXP and LOG. |
| Syntax | LOG(number, [base])If the optional base argument isn't present, base 10 is used. |
| Output | Number |
| Definition | Returns the logarithm of a <number> for the given <base>. |
| Example | LOG(16,4) = 2 |
| Notes | See also POWER LN. |
| Syntax | LOWER(string) |
| Output | String |
| Definition | Returns the provided <string> in all lowercase characters. |
| Example | LOWER("ProductVersion") = "productversion" |
| Notes | See also UPPER and PROPER. |
| Syntax | LTRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with any leading spaces removed. |
| Example | LTRIM(" Matador ") = "Matador " |
| Notes | See also RTRIM. |
| Syntax | MAKEDATE(year, month, day) |
| Output | Date |
| Definition | Returns a date value constructed from the specified <year>, <month> and <day>. |
| Example | MAKEDATE(1986,3,25) = #1986-03-25# |
| Notes | Note: Incorrectly entered values will be adjusted into a date, such as Available for Tableau Data Extracts. Check for availability in other data sources.
|
| Syntax | MAKEDATETIME(date, time) |
| Output | Datetime |
| Definition | 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. |
| Example | MAKEDATETIME("1899-12-30", #07:59:00#) = #12/30/1899 7:59:00 AM#MAKEDATETIME([Date], [Time]) = #1/1/2001 6:00:00 AM# |
| Notes | This function is available only for MySQL-compatible connections (which for Tableau are MySQL and Amazon Aurora).
|
| Syntax | MAKELINE(SpatialPoint1, SpatialPoint2) |
| Output | Geometry (line) |
| Definition | Generates a line mark between two points |
| Example | MAKELINE(MAKEPOINT(47.59, -122.32), MAKEPOINT(48.5, -123.1)) |
| Notes | Useful for building origin-destination maps. |
| Syntax | MAKEPOINT(latitude, longitude, [SRID]) |
| Output | Geometry (point) |
| Definition | Converts data from If the optional |
| Example | MAKEPOINT(48.5, -123.1) MAKEPOINT([AirportLatitude], [AirportLongitude]) MAKEPOINT([Xcoord],[Ycoord], 3493) |
| Notes |
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. You can use |
| Syntax | MAKETIME(hour, minute, second) |
| Output | Datetime |
| Definition | Returns a date value constructed from the specified <hour>, <minute> and <second>. |
| Example | MAKETIME(14, 52, 40) = #1/1/1899 14:52:40# |
| Notes | Because Tableau does not support a time data type, only datetime, the output is a datetime. The date portion of the field will be 1/1/1899. Similar function to |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MEDIAN(expression) |
| Definition | Returns the median of an expression across all records. Null values are ignored. |
| Notes | MEDIAN can only be used with numeric fields. |
| Database limitations |
For other data source types, you can extract your data into an extract file to use this function. See Extract Your Data. |
| Syntax | (MID(string, start, [length]) |
| Output | String |
| Definition | Returns a string starting at the specified If the optional numeric argument |
| Example | MID("Calculation", 2) = "alculation"MID("Calculation", 2, 5) ="alcul" |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MODEL_PERCENTILE(
|
| Definition | 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])) |
| Syntax | MODEL_QUANTILE(
|
| Definition | 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])) |
| Syntax | MONTH(date) |
| Output | Integer |
| Definition | Returns the month of the given <date> as an integer. |
| Example | MONTH(#1986-03-25#) = 3 |
| Notes | See also DAY, WEEK, Quarter, YEAR and the ISO equivalents |
| Syntax | NOT <expression> |
| Output | Boolean (true or false) |
| Definition | Performs logical negation on an expression. |
| Example | IF NOT [Season] = "Summer" "If Season doesn't equal Summer, then return Don't wear sandals. If not, return Wear sandals." |
| Notes | Often used with IF and IIF. See also The Tableau functions in this reference are organised alphabetically. Click a letter to jump to that location in the list. You can also use Ctrl+F (Command-F on a Mac) to open a search box to look for a specific function. and OR. |
| Syntax | NOW() |
| Output | Datetime |
| Definition | Returns the current local system date and time. |
| Example | NOW() = 1986-03-25 1:08:21 PM |
| Notes |
See also If the data source is a live connection, the system date and time could be in another time zone. For more information on how to address this, see the Knowledge Base. |
| Syntax | <expr1> OR <expr2> |
| Output | Boolean (true or false) |
| Definition | Performs a logical disjunction on two expressions. |
| Example | IF [Season] = "Spring" OR [Season] = "Fall" "If either (Season = Spring) or (Season = Fall) is true, then return Sneakers." |
| Notes | Often used with IF and IIF. See also The Tableau functions in this reference are organised alphabetically. Click a letter to jump to that location in the list. You can also use Ctrl+F (Command-F on a Mac) to open a search box to look for a specific function. and NOT. If either expression is If you create a calculation which displays the result of an Note: The |
| Syntax | OUTLINE(<spatial polygon>) |
| Output | Geometry |
| Definition | Converts a polygon geometry into linestrings. |
| Notes | Useful for creating a separate layer for an outline that can be styled differently than the fill. Supports polygons within multipolygons. |
| Syntax | PERCENTILE(expression, number) |
| Definition | Returns the percentile value from the given <expression> corresponding to the specified <number>. The <number> must be between 0 and 1 (inclusive) and must be a numeric constant. |
| Example | PERCENTILE([Score], 0.9) |
| Database limitations | 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, EXASolution 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. |
| Syntax | PI() |
| Output | Number |
| Definition | Returns the numeric constant pi: 3.14159... |
| Example | PI() = 3.14159 |
| Notes | Useful for trig functions that take their input in radians. |
| Syntax | POWER(number, power) |
| Output | Number |
| Definition | Raises the <number> to the specified <power>. |
| Example | POWER(5,3) = 125 |
| Notes | You can also use the ^ symbol, such as 5^3 = POWER(5,3) = 125 |
| Syntax | PROPER(string) |
| Output | String |
| Definition | Returns the provided |
| Example | PROPER("PRODUCT name") = "Product Name"PROPER("darcy-mae") = "Darcy-Mae" |
| Notes | Spaces and non-alphanumeric characters such as punctuation are treated as separators. |
| Syntax | QUARTER(date) |
| Output | Integer |
| Definition | Returns the quarter of the given <date> as an integer. |
| Example | QUARTER(#1986-03-25#) = 1 |
| Notes | See also DAY, WEEK, MONTH, YEAR and the ISO equivalents |
| Syntax | RADIANS(number) |
| Output | Number (angle in radians) |
| Definition | Converts the given <number> from degrees to radians. |
| Example | RADIANS(180) = 3.14159 |
| Notes | The inverse function, DEGREES, takes an angle in radians and returns the angle in degrees. |
| Syntax | REPLACE(string, substring, replacement |
| Output | String |
| Definition | Searches <string> for <substring> and replaces it with <replacement>. If <substring> is not found, the string is not changed. |
| Example | REPLACE("Version 3.8", "3.8", "4x") = "Version 4x" |
| Notes | See also REGEXP_REPLACE in the additional functions documentation. |
| Syntax | RIGHT(string, number) |
| Output | String |
| Definition | Returns the right-most <number> of characters in the string. |
| Example | RIGHT("Calculation", 4) = "tion" |
| Notes | See also LEFT and MID. |
| Syntax | ROUND(number, [decimals]) |
| Output | Number |
| Definition | Rounds the The optional |
| Example | ROUND(1/3, 2) = 0.33 |
| Notes | Some databases, such as SQL Server, allow specification of a negative length, where -1 rounds number to the tens place, -2 rounds to the hundreds place and so on. This is not true of all databases. For example, it is not true of Excel or Access.
|
| Syntax | RTRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with any trailing spaces removed. |
| Example | RTRIM(" Calculation ") = " Calculation" |
| Notes | See also LTRIM and TRIM. |
| Syntax | SHAPETYPE(<geometry>) |
| Output | String |
| Definition | Returns a string describing the structure of the spatial geometry, such as Empty, Point, MultiPoint, LineString, MultiLinestring, Polygon, MultiPolygon, Mixed and unsupported |
| Example | SHAPETYPE(MAKEPOINT(48.5, -123.1)) = "Point" |
| Syntax | SIGN(number) |
| Output | -1, 0 or 1 |
| Definition | 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 | SIGN(AVG(Profit)) = -1 |
| Notes | See also ABS. |
| Syntax | SIN(number) |
| Output | Number |
| Definition | Returns the sine of an angle in radians. |
| Example | SIN(0) = 1.0 |
| Notes | The inverse function, See also |
| Syntax | SPACE(number) |
| Output | String (specifically, just spaces) |
| Definition | Returns a string that is composed of the specified number of repeated spaces. |
| Example | SPACE(2) = " " |
| Syntax | SPLIT(string, delimiter, token number) |
| Output | String |
| Definition | Returns a substring from a <string>, using a <delimiter> character to divide the string into a sequence of <tokens>. |
| Example | SPLIT ("a-b-c-d", "-", 2) = "b"SPLIT ("a|b|c|d", "|", -2) = "c" |
| Notes | The string is interpreted as an alternating sequence of delimiters and tokens. So for the string
See also supported RegEX in the additional functions documentation. |
| Database limitations | 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 strings. See SPLIT function limitations later in this topic. |
| Syntax | SQRT(number) |
| Output | Number |
| Definition | Returns the square root of a <number>. |
| Example | SQRT(25) = 5 |
| Notes | See also SQUARE. |
| Syntax | SQUARE(number) |
| Output | Number |
| Definition | Returns the square of a <number>. |
| Example | SQUARE(5) = 25 |
| Notes | See also SQRT and POWER. |
| Syntax | STARTSWITH(string, substring) |
| Output | Boolean |
| Definition | Returns true if string starts with substring. Leading white spaces are ignored. |
| Example | STARTSWITH("Matador, "Ma") = TRUE |
| Notes | See also CONTAINS, as well as supported RegEX in the additional functions documentation. |
| Syntax | STDEV(expression) |
| Definition | Returns the statistical standard deviation of all values in the given <expression> based on a sample of the population. |
| Syntax | STDEVP(expression) |
| Definition | Returns the statistical standard deviation of all values in the given <expression> based on a biased population. |
| Syntax | STR(expression) |
| Output | String |
| Definition | Casts its argument as a string. |
| Example | STR([ID]) |
| Syntax | SUM(expression) |
| Definition | Returns the sum of all values in the <expression>. Null values are ignored. |
| Notes | SUM can only be used with numeric fields. |
| Syntax | TAN(number)The |
| Output | Number |
| Definition | Returns the tangent of an angle. |
| Example | TAN(PI ( )/4) = 1.0 |
| Notes | See also ATAN, ATAN2, COT and PI. To convert an angle from degrees to radians, use RADIANS. |
| Syntax | IF <test1> THEN <then1>
|
| Definition | A required part of an IF, ELSEIF or CASE expression, used to define what result to return if a specific value or test is true. |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes |
| Syntax | TODAY() |
| Output | Date |
| Definition | Returns the current local system date. |
| Example | TODAY() = 1986-03-25 |
| Notes |
See also If the data source is a live connection, the system date could be in another time zone. For more information on how to address this, see the Knowledge Base. |
| Syntax | TRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with leading and trailing spaces removed. |
| Example | TRIM(" Calculation ") = "Calculation" |
| Notes | See also LTRIM and RTRIM. |
| Syntax | UPPER(string) |
| Output | String |
| Definition | Returns the provided <string> in all uppercase characters. |
| Example | UPPER("Calculation") = "CALCULATION" |
| Notes | See also PROPER and LOWER. |
| Syntax | USERDOMAIN( ) |
| Output | String |
| Definition | Returns the domain for the current user. |
| Notes | This function checks:
|
| Syntax | USERNAME( ) |
| Output | String |
| Definition | Returns the username for the current user. |
| Example | USERNAME( ) This returns the username of the signed-in user, such as "hmyrer". [Manager] = USERNAME( ) If manager "hmyrer" is signed in, this example returns TRUE only if the Manager field in the view contains "hmyrer". |
| Notes | This function checks:
User filters When used as a filter, a calculated field such as |
| Syntax | VAR(expression) |
| Definition | Returns the statistical variance of all values in the given expression based on a sample of the population. |
| Syntax | VARP(expression) |
| Definition | Returns the statistical variance of all values in the given expression on the entire population. |
| Syntax | WEEK(date) |
| Output | Integer |
| Definition | Returns the week of the given <date> as an integer. |
| Example | WEEK(#1986-03-25#) = 13 |
| Notes | See also DAY, MONTH, Quarter, YEAR and the ISO equivalents |
| Syntax | CASE <expression> |
| Definition | A required part of a CASE expression. Finds the first <value> that matches <expression> and returns the corresponding <then>. |
| Example | CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes | Used with CASE, THEN, ELSE and END.
CASE <expression> The values that |
| Syntax | YEAR(date) |
| Output | Integer |
| Definition | Returns the year of the given <date> as an integer. |
| Example | YEAR(#1986-03-25#) = 1,986 |
| Notes | See also DAY, WEEK, MONTH, Quarter and the ISO equivalents |
| Syntax | ZN(expression) |
| Output | Depends on the data type of the <expression>, or 0. |
| Definition | Returns <expression> if it isn't null; otherwise returns zero. |
| Example | ZN([Test Grade]) "If the test grade isn't null, return its value. If the test grade is null, return 0." |
| Notes |
See also ISNULL. |
| Syntax | ABS(number) |
| Output | Number (positive) |
| Definition | Returns the absolute value of the given <number>. |
| Example | ABS(-7) = 7 The second example returns the absolute value for all the numbers contained in the Budget Variance field. |
| Notes | See also SIGN. |
| Syntax | ACOS(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arccosine (angle) of the given <number>. |
| Example | ACOS(-1) = 3.14159265358979 |
| Notes | The inverse function, COS, takes the angle in radians as the argument and returns the cosine. |
| Syntax | ASIN(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arcsine (angle) of a given <number>. |
| Example | ASIN(1) = 1.5707963267949 |
| Notes | The inverse function, SIN, takes the angle in radians as the argument and returns the sine. |
| Syntax | ATAN(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arctangent (angle) of a given <number>. |
| Example | ATAN(180) = 1.5652408283942 |
| Notes | The inverse function, |
| Syntax | ATAN2(y number, x number) |
| Output | Number (angle in radians) |
| Definition | Returns the arctangent (angle) between two numbers (x and y). The result is in radians. |
| Example | ATAN2(2, 1) = 1.10714871779409 |
| Notes | See also ATAN, TAN and COT. |
| Syntax | CEILING(number) |
| Output | Integer |
| Definition | Rounds a <number> to the nearest integer of equal or greater value. |
| Example | CEILING(2.1) = 3 |
| Notes | See also FLOOR and ROUND. |
| Database limitations |
|
| Syntax | COS(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the cosine of an angle. |
| Example | COS(PI( ) /4) = 0.707106781186548 |
| Notes | The inverse function, See also |
| Syntax | COT(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the cotangent of an angle. |
| Example | COT(PI( ) /4) = 1 |
| Notes | See also ATAN, TAN and PI. To convert an angle from degrees to radians, use RADIANS. |
| Syntax | DEGREES(number)The number argument is the angle in radians. |
| Output | Number (degrees) |
| Definition | Converts an angle in radians to degrees. |
| Example | DEGREES(PI( )/4) = 45.0 |
| Notes | The inverse function, See also |
| Syntax | DIV(integer1, integer2) |
| Output | Integer |
| Definition | Returns the integer part of a division operation, in which <integer1> is divided by <integer2>. |
| Example | DIV(11,2) = 5 |
| Syntax | EXP(number) |
| Output | Number |
| Definition | Returns e raised to the power of the given <number>. |
| Example | EXP(2) = 7.389 |
| Notes | See also LN. |
| Syntax | FLOOR(number) |
| Output | Integer |
| Definition | Rounds a number to the nearest <number> of equal or lesser value. |
| Example | FLOOR(7.9) = 7 |
| Notes | See also CEILING and ROUND. |
| Database limitations |
|
| Syntax | HEXBINX(number, number) |
| Output | Number |
| Definition | 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. |
| Example | HEXBINX([Longitude]*2.5, [Latitude]*2.5) |
| Notes | 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. |
| Syntax | HEXBINY(number, number) |
| Output | Number |
| Definition | 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]*2.5, [Latitude]*2.5) |
| Notes | See also HEXBINX. |
| Syntax | LN(number) |
| Output | Number The output is |
| Definition | Returns the natural logarithm of a <number>. |
| Example | LN(50) = 3.912023005 |
| Notes | See also EXP and LOG. |
| Syntax | LOG(number, [base])If the optional base argument isn't present, base 10 is used. |
| Output | Number |
| Definition | Returns the logarithm of a number for the given base. |
| Example | LOG(16,4) = 2 |
| Notes | See also POWER LN. |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | PI() |
| Output | Number |
| Definition | Returns the numeric constant pi: 3.14159... |
| Example | PI() = 3.14159 |
| Notes | Useful for trig functions that take their input in radians. See also RADIANS. |
| Syntax | POWER(number, power) |
| Output | Number |
| Definition | Raises the <number> to the specified <power>. |
| Example | POWER(5,3) = 125 |
| Notes | You can also use the ^ symbol, such as 5^3 = POWER(5,3) = 125 |
| Syntax | RADIANS(number) |
| Output | Number (angle in radians) |
| Definition | Converts the given <number> from degrees to radians. |
| Example | RADIANS(180) = 3.14159 |
| Notes | The inverse function, DEGREES, takes an angle in radians and returns the angle in degrees. |
| Syntax | ROUND(number, [decimals]) |
| Output | Number |
| Definition | Rounds The optional |
| Example | ROUND(1/3, 2) = 0.33 |
| Notes | Some databases, such as SQL Server, allow specification of a negative length, where -1 rounds number to 10s, -2 rounds to 100s and so on. This is not true of all databases. For example, it is not true of Excel or Access.
|
| Syntax | SIGN(number) |
| Output | -1, 0 or 1 |
| Definition | 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 | SIGN(AVG(Profit)) = -1 |
| Notes | See also ABS. |
| Syntax | SIN(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the sine of an angle. |
| Example | SIN(0) = 1.0 |
| Notes | The inverse function, See also |
| Syntax | SQRT(number) |
| Output | Number |
| Definition | Returns the square root of a <number>. |
| Example | SQRT(25) = 5 |
| Notes | See also SQUARE. |
| Syntax | SQUARE(number) |
| Output | Number |
| Definition | Returns the square of a <number>. |
| Example | SQUARE(5) = 25 |
| Notes | See also SQRT and POWER. |
| Syntax | TAN(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the tangent of an angle. |
| Example | TAN(PI ( )/4) = 1.0 |
| Notes | See also ATAN, ATAN2, COT and PI. To convert an angle from degrees to radians, use RADIANS. |
| Syntax | ZN(expression) |
| Output | Any, or o |
| Definition | Returns the Use this function to replace null values with zeros. |
| Example | ZN(Grade) = 0 |
| Notes | This is a very useful function when using fields that may contain nulls in a calculation. Wrapping the field with ZN can prevent errors caused by calculating with nulls. |
| Syntax | ASCII(string) |
| Output | Number |
| Definition | Returns the ASCII code for the first character of a <string>. |
| Example | ASCII('A') = 65 |
| Notes | This is the inverse of the CHAR function. |
| Syntax | CHAR(number) |
| Output | String |
| Definition | Returns the character encoded by the ASCII code <number>. |
| Example | CHAR(65) = 'A' |
| Notes | This is the inverse of the ASCII function. |
| Syntax | CONTAINS(string, substring) |
| Output | Boolean |
| Definition | Returns true if the given string contains the specified substring. |
| Example | CONTAINS("Calculation", "alcu") = true |
| Notes | See also the logical function Depending on the data source, CONTAINS may be case sensitive. That is, for some data sources, |
| Syntax | ENDSWITH(string, substring) |
| Output | Boolean |
| Definition | Returns true if the given string ends with the specified substring. Trailing white spaces are ignored. |
| Example | ENDSWITH("Tableau", "leau") = true |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | FIND(string, substring, [start]) |
| Output | Number |
| Definition | Returns the index position of substring in string, or 0 if the substring isn't found. The first character in the string is position 1. If the optional numeric argument |
| Example | FIND("Calculation", "alcu") = 2FIND("Calculation", "Computer") = 0FIND("Calculation", "a", 3) = 7FIND("Calculation", "a", 2) = 2FIND("Calculation", "a", 8) = 0 |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | FINDNTH(string, substring, occurrence) |
| Output | Number |
| Definition | Returns the position of the nth occurrence of substring within the specified string, where n is defined by the occurrence argument. |
| Example | FINDNTH("Calculation", "a", 2) = 7 |
| Notes |
See also the supported RegEx in the additional functions documentation. |
| Syntax | LEFT(string, number) |
| Output | String |
| Definition | Returns the left-most <number> of characters in the string. |
| Example | LEFT("Matador", 4) = "Mata" |
| Notes | See also MID and RIGHT. |
| Syntax | LEN(string) |
| Output | Number |
| Definition | Returns the length of the string. |
| Example | LEN("Matador") = 7 |
| Notes | Not to be confused with the spatial function LENGTH. |
| Syntax | LOWER(string) |
| Output | String |
| Definition | Returns the provided <string> in all lowercase characters. |
| Example | LOWER("ProductVersion") = "productversion" |
| Notes | See also UPPER and PROPER. |
| Syntax | LTRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with any leading spaces removed. |
| Example | LTRIM(" Matador ") = "Matador " |
| Notes | See also RTRIM. |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | (MID(string, start, [length]) |
| Output | String |
| Definition | Returns a string starting at the specified If the optional numeric argument |
| Example | MID("Calculation", 2) = "alculation"MID("Calculation", 2, 5) ="alcul" |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | PROPER(string) |
| Output | String |
| Definition | Returns the provided |
| Example | PROPER("PRODUCT name") = "Product Name"PROPER("darcy-mae") = "Darcy-Mae" |
| Notes | Spaces and non-alphanumeric characters such as punctuation are treated as separators. |
| Database limitations | PROPER is only available for some flat files and in extracts. If you need to use PROPER in a data source that doesn't otherwise support it, consider using an extract. |
| Syntax | REPLACE(string, substring, replacement |
| Output | String |
| Definition | Searches <string> for <substring> and replaces it with <replacement>. If <substring> is not found, the string is not changed. |
| Example | REPLACE("Version 3.8", "3.8", "4x") = "Version 4x" |
| Notes | See also REGEXP_REPLACE in the additional functions documentation. |
| Syntax | RIGHT(string, number) |
| Output | String |
| Definition | Returns the right-most <number> of characters in the string. |
| Example | RIGHT("Calculation", 4) = "tion" |
| Notes | See also LEFT and MID. |
| Syntax | RTRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with any trailing spaces removed. |
| Example | RTRIM(" Calculation ") = " Calculation" |
| Notes | See also LTRIM and TRIM. |
| Syntax | SPACE(number) |
| Output | String (specifically, just spaces) |
| Definition | Returns a string that is composed of the specified number of repeated spaces. |
| Example | SPACE(2) = " " |
| Syntax | SPLIT(string, delimiter, token number) |
| Output | String |
| Definition | Returns a substring from a string, using a delimiter character to divide the string into a sequence of tokens. |
| Example | SPLIT ("a-b-c-d", "-", 2) = "b"SPLIT ("a|b|c|d", "|", -2) = "c" |
| Notes | The string is interpreted as an alternating sequence of delimiters and tokens. So for the string
See also supported RegEX in the additional functions documentation. |
| Database limitations | 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 strings. See SPLIT function limitations later in this topic. |
| Syntax | STARTSWITH(string, substring) |
| Output | Boolean |
| Definition | Returns true if string starts with substring. Leading white spaces are ignored. |
| Example | STARTSWITH("Matador, "Ma") = TRUE |
| Notes | See also CONTAINS, as well as supported RegEX in the additional functions documentation. |
| Syntax | TRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with leading and trailing spaces removed. |
| Example | TRIM(" Calculation ") = "Calculation" |
| Notes | See also LTRIM and RTRIM. |
| Syntax | UPPER(string) |
| Output | String |
| Definition | Returns the provided <string> in all uppercase characters. |
| Example | UPPER("Calculation") = "CALCULATION" |
| Notes | See also PROPER and LOWER. |
| Syntax | DATE(expression) |
| Output | Date |
| Definition | Returns a date given a number, string or date <expression>. |
| Example | DATE([Employee Start Date]) DATE("September 22, 2018") DATE("9/22/2018")DATE(#2018-09-22 14:52#) |
| Notes | Unlike
|
| Syntax | DATEADD(date_part, interval, date) |
| Output | Date |
| Definition | Returns the <date> with the specified number <interval> added to the specified <date_part> of that date. For example, adding three months or 12 days to a starting date. |
| Example | Push out all due dates by one week DATEADD('week', 1, [due date])Add 280 days to the date February 20, 2021 DATEADD('day', 280, #2/20/21#) = #November 27, 2021# |
| Notes | Supports ISO 8601 dates. |
| Syntax | DATEDIFF(date_part, date1, date2, [start_of_week]) |
| Output | Integer |
| Definition | Returns the difference between <date1> and <date2> expressed in units of <date_part>. For example, subtracting the dates someone entered and left a band to see how long they were in the band. |
| Example | Number of days between 25th March 1986 and 20th February 2021 DATEDIFF('day', #3/25/1986#, #2/20/2021#) = 12,751How many months someone was in a band DATEDIFF('month', [date joined band], [date left band]) |
| Notes | Supports ISO 8601 dates. |
| Syntax | DATENAME(date_part, date, [start_of_week]) |
| Output | String |
| Definition | Returns <date_part> of <date> as a string. |
| Example | DATENAME('year', #3/25/1986#) = "1986"DATENAME('month', #1986-03-25#) = "March" |
| Notes | Supports ISO 8601 dates. A very similar calculation is DATEPART, which returns the value of the specified date part as a continuous integer. By changing the attributes of the calculation’s result (dimension or measure, continuous or discrete) and the date formatting, the results of An inverse function is DATEPARSE, which takes a string value and formats it as a date. |
| Syntax | DATEPARSE(date_format, date_string) |
| Output | Date |
| Definition | The <date_format> argument describes how the <date_string> field is arranged. Because of the variety of ways the string field can be ordered, the <date_format> must match exactly. For a full explanation and formatting details, see Convert a Field to a Date Field. |
| Example | DATEPARSE('yyyy-MM-dd', "1986-03-25") = #March 25, 1986# |
| Notes |
Inverse functions, which take dates apart and return the value of their parts, are |
| Database limitations |
|
| Syntax | DATEPART(date_part, date, [start_of_week]) |
| Output | Integer |
| Definition | Returns <date_part> of <date> as an integer. |
| Example | DATEPART('year', #1986-03-25#) = 1986DATEPART('month', #1986-03-25#) = 3 |
| Notes | Supports ISO 8601 dates. A very similar calculation is An inverse function is |
| Syntax | DATETRUNC(date_part, date, [start_of_week]) |
| Output | Date |
| Definition | Truncates the <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. |
| Example | DATETRUNC('day', #9/22/2018#) = #9/22/2018#DATETRUNC('iso-week', #9/22/2018#) = #9/17/2018#(the Monday of the week containing 22/09/2018) DATETRUNC(quarter, #9/22/2018#) = #7/1/2018# (the first day of the quarter containing 22/09/2018) Note: For week and iso-week, the |
| Notes | Supports ISO 8601 dates. You shouldn't use For example, |
| Syntax | DAY(date) |
| Output | Integer |
| Definition | Returns the day of the given <date> as an integer. |
| Example | Day(#September 22, 2018#) = 22 |
| Notes | See also WEEK, MONTH, QUARTER, YEAR and the ISO equivalents. |
| Syntax | ISDATE(string) |
| Output | Boolean |
| Definition | Returns true if a given <string> is a valid date. |
| Example | ISDATE(09/22/2018) = true ISDATE(22SEP18) = false |
| Notes | The required argument must be a string. ISDATE cannot be used for a field with a date data type – the calculation will return an error. |
| Syntax | ISOQUARTER(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based quarter of a given <date> as an integer. |
| Example | ISOQUARTER(#1986-03-25#) = 1 |
| Notes | See also ISOWEEK, ISOWEEKDAY, ISOYEAR and the non-ISO equivalents. |
| Syntax | ISOWEEK(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based week of a given <date> as an integer. |
| Example | ISOWEEK(#1986-03-25#) = 13 |
| Notes | See also ISOWEEKDAY, ISOQUARTER, ISOYEAR and the non-ISO equivalents. |
| Syntax | ISOWEEKDAY(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based weekday of a given <date> as an integer. |
| Example | ISOWEEKDAY(#1986-03-25#) = 2 |
| Notes | See also ISOWEEK, ISOQUARTER, ISOYEAR and the non-ISO equivalents. |
| Syntax | ISOYEAR(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based year of a given <date> as an integer. |
| Example | ISOYEAR(#1986-03-25#) = 1,986 |
| Notes | See also ISOWEEK, ISOWEEKDAY, ISOQUARTER and the non-ISO equivalents. |
| Syntax | MAKEDATE(year, month, day) |
| Output | Date |
| Definition | Returns a date value constructed from the specified <year>, <month> and <day>. |
| Example | MAKEDATE(1986,3,25) = #1986-03-25# |
| Notes | Note: Incorrectly entered values will be adjusted into a date, such as Available for Tableau Data Extracts. Check for availability in other data sources.
|
| Syntax | MAKEDATETIME(date, time) |
| Output | Datetime |
| Definition | 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. |
| Example | MAKEDATETIME("1899-12-30", #07:59:00#) = #12/30/1899 7:59:00 AM#MAKEDATETIME([Date], [Time]) = #1/1/2001 6:00:00 AM# |
| Notes | This function is available only for MySQL-compatible connections (which for Tableau are MySQL and Amazon Aurora).
|
| Syntax | MAKETIME(hour, minute, second) |
| Output | Datetime |
| Definition | Returns a date value constructed from the specified <hour>, <minute> and <second>. |
| Example | MAKETIME(14, 52, 40) = #1/1/1899 14:52:40# |
| Notes | Because Tableau does not support a time data type, only datetime, the output is a datetime. The date portion of the field will be 1/1/1899. Similar function to |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MONTH(date) |
| Output | Integer |
| Definition | Returns the month of the given <date> as an integer. |
| Example | MONTH(#1986-03-25#) = 3 |
| Notes | See also DAY, WEEK, QUARTER, YEAR and the ISO equivalents |
| Syntax | NOW() |
| Output | Datetime |
| Definition | Returns the current local system date and time. |
| Example | NOW() = 1986-03-25 1:08:21 PM |
| Notes |
See also If the data source is a live connection, the system date and time could be in another time zone. For more information on how to address this, see the Knowledge Base. |
| Syntax | QUARTER(date) |
| Output | Integer |
| Definition | Returns the quarter of the given <date> as an integer. |
| Example | QUARTER(#1986-03-25#) = 1 |
| Notes | See also DAY, WEEK, MONTH, YEAR and the ISO equivalents |
| Syntax | TODAY() |
| Output | Date |
| Definition | Returns the current local system date. |
| Example | TODAY() = 1986-03-25 |
| Notes |
See also NOW, a similar calculation that returns a datetime instead of a date. If the data source is a live connection, the system date could be in another time zone. For more information on how to address this, see the Knowledge Base. |
| Syntax | WEEK(date) |
| Output | Integer |
| Definition | Returns the week of the given <date> as an integer. |
| Example | WEEK(#1986-03-25#) = 13 |
| Notes | See also DAY, MONTH, QUARTER, YEAR and the ISO equivalents |
| Syntax | YEAR(date) |
| Output | Integer |
| Definition | Returns the year of the given <date> as an integer. |
| Example | YEAR(#1986-03-25#) = 1,986 |
| Notes | See also DAY, WEEK, MONTH, QUARTER and the ISO equivalents |
| Syntax | <expr1> AND <expr2> |
| Definition | Performs a logical conjunction on two expressions. (If both sides are true, the logical test returns true.) |
| Output | Boolean (true or false) |
| Example | IF [Season] = "Spring" AND "[Season] = "Fall" “If both (Season = Spring) and (Season = Autumn) are true simultaneously, then return ‘It's the apocalypse and footwear doesn't matter’.” |
| Notes | Often used with IF and IIF. See also NOT and OR. If both expressions are If you create a calculation in which the result of an Note: The |
| Syntax | CASE <expression>
|
| Output | Depends on data type of the <then> values. |
| Definition | Evaluates the |
| Example | "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes | Used with WHEN, THEN, ELSE and END.
|
| Syntax | CASE <expression>
|
| Definition | An optional piece of an IF or CASE expression used to specify a default value to return if none of the tested expressions are true. |
| Example | IF [Season] = "Summer" THEN 'Sandals' CASE [Season] |
| Notes | Used with CASE, WHEN, IF, ELSEIF, THEN and END
|
| Syntax | [ELSEIF <test2> THEN <then2>] |
| Definition | An optional piece of an IF expression used to specify additional conditions beyond the initial IF. |
| Example | IF [Season] = "Summer" THEN 'Sandals' |
| Notes | Used with IF, THEN, ELSE and END
Unlike |
| Definition | Used to close an IF or CASE expression. |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes |
| Syntax | IF <test1> THEN <then1> |
| Output | Depends on data type of the <then> values. |
| Definition | Tests a series of expressions and returns the |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." |
| Notes |
| Syntax | IFNULL(expr1, expr2) |
| Output | Depends on the data type of the <expr> values. |
| Definition | Returns |
| Example | IFNULL([Assigned Room], "TBD") "If the Assigned Room field isn't null, return its value. If the Assigned room field is null, return TBD instead." |
| Notes | Compare with ISNULL. See also ZN. |
| Syntax | IIF(<test>, <then>, <else>, [<unknown>]) |
| Output | Depends on the data type of the values in the expression. |
| Definition | Checks whether a condition is met (<test>) and returns <then> if the test is true, <else> if the test is false and an optional value for <unknown> if the test is null. If the optional unknown isn't specified, IIF returns null. |
| Example | IIF([Season] = 'Summer', 'Sandals', 'Other footwear') "If Season = Summer, then return Sandals. If not, return Other footwear" IIF([Season] = 'Summer', 'Sandals', "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither are true, return Sneakers." IIF('Season' = 'Summer', 'Sandals', "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If none of the expressions are true, return Sneakers." |
| Notes |
That is to say, in the calculation below, the result will be Red, not Orange, because the expression stops being evaluated as soon as A=A is evaluated as true:
|
| Syntax | <expr1> IN <expr2> |
| Output | Boolean (true or false) |
| Definition | Returns TRUE if any value in <expr1> matches any value in <expr2>. |
| Example | SUM([Cost]) IN (1000, 15, 200) "Is the value of the Cost field 1000, 15 or 200?" [Field] IN [Set] "Is the value of the field present in the set?" |
| Notes | The values in See also WHEN. |
| Syntax | ISDATE(string) |
| Output | Boolean (true or false) |
| Definition | Returns true if a <string> is a valid date. The input expression must be a string (text) field. |
| Example | ISDATE("2018-09-22")"Is the string 2018-09-22 a properly formatted date?" |
| Notes | What is considered a valid date depends on the locale of the system evaluating the calculation. For example: In the USA:
In the UK:
|
| Syntax | ISNULL(expression) |
| Output | Boolean (true or false) |
| Definition | Returns true if the |
| Example | ISNULL([Assigned Room]) "Is the Assigned Room field null?" |
| Notes | Compare with IFNULL. See also ZN. |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | NOT <expression> |
| Output | Boolean (true or false) |
| Definition | Performs logical negation on an expression. |
| Example | IF NOT [Season] = "Summer" "If Season doesn't equal Summer, then return Don't wear sandals. If not, return Wear sandals." |
| Notes |
| Syntax | <expr1> OR <expr2> |
| Output | Boolean (true or false) |
| Definition | Performs a logical disjunction on two expressions. |
| Example | IF [Season] = "Spring" OR [Season] = "Fall" "If either (Season = Spring) or (Season = Fall) is true, then return Sneakers." |
| Notes | Often used with IF and IIF. See also DATE and NOT. If either expression is If you create a calculation that displays the result of an Note: The |
| Syntax | IF <test1> THEN <then1>
|
| Definition | A required part of an IF, ELSEIF or CASE expression, used to define what result to return if a specific value or test is true. |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes |
| Syntax | CASE <expression>
|
| Definition | A required part of a CASE expression. Finds the first <value> that matches <expression> and returns the corresponding <then>. |
| Example | CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes | Used with CASE, THEN, ELSE and END.
CASE <expression> The values that |
| Syntax | ZN(expression) |
| Output | Depends on the data type of the <expression>, or 0. |
| Definition | Returns <expression> if it isn't null; otherwise returns zero. |
| Example | ZN([Test Grade]) "If the test grade isn't null, return its value. If the test grade is null, return 0." |
| Notes |
See also ISNULL. |
| Syntax | ATTR(expression) |
| Definition | Returns the value of the expression if it has a single value for all rows. Otherwise returns an asterisk. Null values are ignored. |
| Syntax | AVG(expression) |
| Definition | Returns the average of all the values in the expression. Null values are ignored. |
| Notes | AVG can only be used with numeric fields. |
| Syntax | COLLECT(spatial) |
| Definition | An aggregate calculation that combines the values in the argument field. Null values are ignored. |
| Notes | COLLECT can only be used with spatial fields. |
| Syntax | CORR(expression1, expression2) |
| Output | Number from -1 to 1 |
| Definition | Returns the Pearson correlation coefficient of two expressions. |
| Example | example |
| Notes | 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, 0 denotes no linear relationship between the variance and −1 is an exact negative relationship. The square of a CORR result is equivalent to the R-Squared value for a linear trend line model. See Trend Line Model Terms. Use with table-scoped LOD expressions: You can use CORR to visualise correlation in a disaggregated scatter using 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 |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | COUNT(expression) |
| Definition | Returns the number of items. Null values are not counted. |
| Syntax | COUNTD(expression) |
| Definition | Returns the number of distinct items in a group. Null values are not counted. |
| Syntax | COVAR(expression1, expression2) |
| Definition | Returns the sample covariance of two expressions. |
| Notes | 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 If The value of |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | COVARP(expression 1, expression2) |
| Definition | Returns the population covariance of two expressions. |
| Notes | 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 If |
| Database limitations |
For other data sources, consider either extracting the data or using |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MEDIAN(expression) |
| Definition | Returns the median of an expression across all records. Null values are ignored. |
| Notes | MEDIAN can only be used with numeric fields. |
| Database limitations |
For other data source types, you can extract your data into an extract file to use this function. See Extract Your Data. |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | PERCENTILE(expression, number) |
| Definition | Returns the percentile value from the given expression corresponding to the specified <number>. The <number> must be between 0 and 1 (inclusive) and must be a numeric constant. |
| Example | PERCENTILE([Score], 0.9) |
| Database limitations | 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, EXASolution 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. |
| Syntax | STDEV(expression) |
| Definition | Returns the statistical standard deviation of all values in the given expression based on a sample of the population. |
| Syntax | STDEVP(expression) |
| Definition | Returns the statistical standard deviation of all values in the given expression based on a biased population. |
| Syntax | SUM(expression) |
| Definition | Returns the sum of all values in the expression. Null values are ignored. |
| Notes | SUM can only be used with numeric fields. |
| Syntax | VAR(expression) |
| Definition | Returns the statistical variance of all values in the given expression based on a sample of the population. |
| Syntax | VARP(expression) |
| Definition | Returns the statistical variance of all values in the given expression on the entire population. |
| Syntax | FULLNAME( ) |
| Output | String |
| Definition | Returns the full name for the current user. |
| Example | FULLNAME( ) This returns the full name of the signed-in user, such as "Hamlin Myrer". [Manager] = FULLNAME( ) If manager "Hamlin Myrer" is signed in, this example returns TRUE only if the Manager field in the view contains "Hamlin Myrer". |
| Notes | This function checks:
User filters When used as a filter, a calculated field such as |
| Syntax | ISFULLNAME("User Full Name") |
| Output | Boolean |
| Definition | Returns |
| Example | ISFULLNAME("Hamlin Myrer") |
| Notes | The This function checks:
|
| Syntax | ISMEMBEROF("Group Name") |
| Output | Boolean or null |
| Definition | Returns |
| Example | ISMEMBEROF('Superstars')ISMEMBEROF('domain.lan\Sales') |
| Notes | The If the user is signed in to Tableau Cloud or Tableau Server, group membership is determined by Tableau groups. The function will return TRUE if the given string is "All Users" The If a change is made to a user's group membership, the change in the data that is based on the group membership is reflected in a workbook or view with a new session. The existing session will reflect stale data. |
| Syntax | ISUSERNAME("username") |
| Output | Boolean |
| Definition | Returns TRUE if the current user's username matches the specified username or FALSE if it does not match. |
| Example | ISUSERNAME("hmyrer") |
| Notes | The This function checks:
|
| Syntax | USERDOMAIN( ) |
| Output | String |
| Definition | Returns the domain for the current user. |
| Notes | This function checks:
|
| Syntax | USERNAME( ) |
| Output | String |
| Definition | Returns the username for the current user. |
| Example | USERNAME( ) This returns the username of the signed-in user, such as "hmyrer". [Manager] = USERNAME( ) If manager "hmyrer" is signed in, this example returns TRUE only if the Manager field in the view contains "hmyrer". |
| Notes | This function checks:
User filters When used as a filter, a calculated field such as |
| Syntax | USERATTRIBUTE('attribute_name') |
| Output | String or null |
| Definition | If Returns null if |
| Example | Suppose ‘Region’ is the user attribute included in the JWT or SAML response and passed to Tableau. As the workbook author, you can set up your visualisation to filter data based on a specified region. In that filter, you can reference the following calculation. [Region] = USERATTRIBUTE("Region")When User2 from the West region views the embedded visualisation, Tableau shows the appropriate data for the West region only. |
| Notes | You can use the USERATTRIBUTEINCLUDES function if you expect <'attribute_name'> to return multiple values. |
| Syntax | USERATTRIBUTEINCLUDES('attribute_name', 'expected_value') |
| Output | Boolean |
| Definition | Returns
Returns |
| Example | Suppose ‘Region’ is the user attribute included in the JWT or SAML response and passed to Tableau. As the workbook author, you can set up your visualisation to filter data based on a specified region. In that filter, you can reference the following calculation. USERATTRIBUTEINCLUDES('Region', [Region])If User2 from the West region accesses the embedded visualisation, Tableau checks if the Region user attribute matches one of [Region] field values. When true, the visualisation shows the appropriate data. When User3 from the North region accesses the same visualisation, she’s unable to see any data because there’s no match with [Region] field values. |
| Syntax | RAWSQL_BOOL("sql_expr", [arg1], …[argN]) |
| Output | Boolean |
| Definition | Returns a Boolean result from a given SQL expression. |
| Example | RAWSQL_BOOL("%1 > %2", [Sales], [Profit])In the example, %1 is equal to [Sales] and %2 is equal to [Profit]. |
| Syntax | RAWSQLAGG_BOOL("sql_expr", [arg1], …[argN]) |
| Output | Boolean |
| Definition | Returns a Boolean result from a given aggregate SQL expression. |
| Example | RAWSQLAGG_BOOL("SUM( %1) >SUM( %2)", [Sales], [Profit]) In the example, %1 is equal to [Sales] and %2 is equal to [Profit]. |
| Syntax | RAWSQL_DATE("sql_expr", [arg1], …[argN]) |
| Output | Date |
| Definition | Returns a date result from a given SQL expression. |
| Example | RAWSQL_DATE("%1", [Order Date])In this example, %1 is equal to [Order Date]. |
| Syntax | RAWSQLAGG_DATE("sql_expr", [arg1], …[argN]) |
| Output | Date |
| Definition | Returns a date result from a given aggregate SQL expression |
| Example | RAWSQLAGG_DATE("MAX(%1)", [Order Date])In this example, %1 is equal to [Order Date]. |
| Syntax | RAWSQL_DATETIME("sql_expr", [arg1], …[argN]) |
| Output | Datetime |
| Definition | Returns a datetime result from a given SQL expression. |
| Example | RAWSQL_DATETIME("%1", [Order Date])In this example, %1 is equal to [Order Date]. |
| Syntax | RAWSQLAGG_DATETIME("sql_expr", [arg1], …[argN]) |
| Output | Datetime |
| Definition | Returns a datetime result from a given aggregate SQL expression. |
| Example | RAWSQLAGG_DATETIME("MIN(%1)", [Order Date])In this example, %1 is equal to [Order Date]. |
| Syntax | RAWSQL_INT("sql_expr", [arg1], …[argN]) |
| Output | Integer |
| Definition | Returns an integer result from a given SQL expression. |
| Example | RAWSQL_INT("500 + %1", [Sales])In this example, %1 is equal to [Sales]. |
| Syntax | RAWSQLAGG_INT("sql_expr", [arg1,] …[argN]) |
| Output | Integer |
| Definition | Returns an integer result from a given aggregate SQL expression. |
| Example | RAWSQLAGG_INT("500 + SUM(%1)", [Sales])In this example, %1 is equal to [Sales]. |
| Syntax | RAWSQL_REAL("sql_expr", [arg1], …[argN]) |
| Output | Numeric |
| Definition | Returns a numeric result from a given SQL expression. |
| Example | RAWSQL_REAL("-123.98 * %1", [Sales])In this example, %1 is equal to [Sales] |
| Syntax | RAWSQLAGG_REAL("sql_expr", [arg1,] …[argN]) |
| Output | Numeric |
| Definition | Returns a numeric result from a given aggregate SQL expression. |
| Example | RAWSQLAGG_REAL("SUM( %1)", [Sales])In this example, %1 is equal to [Sales]. |
| Syntax | RAWSQL_SPATIAL("sql_expr", [arg1], …[argN]) |
| Output | Spatial |
| Definition | Returns a spatial result from a given SQL expression. |
| Example | RAWSQL_SPATIAL("%1", [Geometry])In this example, %1 is equal to [Geometry]. |
| Note | There is no RAWSQLAGG version of this function. |
| Syntax | RAWSQL_STR("sql_expr", [arg1], …[argN]) |
| Output | String |
| Definition | Returns a string from a given SQL expression. |
| Example | RAWSQL_STR("%1", [Customer Name])In this example, %1 is equal to [Customer Name]. |
| Syntax | RAWSQLAGG_STR("sql_expr", [arg1,] …[argN]) |
| Output | String |
| Definition | Returns a string from a given aggregate SQL expression. |
| Example | RAWSQLAGG_STR("AVG(%1)", [Discount])In this example, %1 is equal to [Discount]. |
| Syntax | AREA(Spatial Polygon, 'units') |
| Output | Number |
| Definition | Returns the total surface area of a <spatial polygon>. |
| Example | AREA([Geometry], 'feet') |
| Notes | Supported unit names (must be in quotation marks in the calculation, such as
|
| Syntax | BUFFER(Spatial point, distance, 'units')
|
| Output | Geometry |
| Definition | For spatial points, returns a polygon shape centred over a For linestrings, computes the polygons formed by including all points within the radius distance from the linestring. For polygons, it calculates a polygon that is either an inset (negative distance) or outset (positive distance) of each given polygon. |
| Example | BUFFER([Spatial Point Geometry], 25, 'mi') BUFFER(MAKEPOINT(47.59, -122.32), 3, 'km') BUFFER(MAKELINE(MAKEPOINT(0, 20),MAKEPOINT (30, 30)),20,'km')) |
| Notes | Supported unit names (must be in quotation marks in the calculation, such as
|
| Syntax | DIFFERENCE(Spatial, Spatial) |
| Output | Spatial Polygon |
| Definition | Computes the portions of regions remaining when all regions in the second argument are carved out of the first argument in areas that overlap. Discards regions from the second argument in areas that don't overlap. |
| Example | DIFFERENCE(Spatial Polygon1, Spatial Polygon2) |
| Notes | Supports spatial polygons and multipolygons, not spatial points or lines. |
| Syntax | DISTANCE(SpatialPoint1, SpatialPoint2, 'units') |
| Output | Number |
| Definition | Returns the distance measurement between two points in the specified <unit>. |
| Example | DISTANCE([Origin Point],[Destination Point], 'km') |
| Notes | Supported unit names (must be in quotation marks in the calculation, such as
|
| Database limitations | This function can only be created with a live connection but will continue to work if the data source is converted to an extract. |
| Syntax | INTERSECTION (spatial, spatial) |
| Output | Polygon |
| Definition | Computes and returns the portions of regions in the second argument that overlap regions in the first argument. |
| Example | INTERSECTION (Spatial Polygon1, Spatial Polygon2) |
| Notes | Supports spatial polygons and multipolygons, not spatial points or lines. |
| Syntax | INTERSECTS (geometry1, geometry2) |
| Output | Boolean |
| Definition | Returns true or false indicating whether two geometries overlap in space. |
| Notes | Supported combinations: point/polygon, line/polygon and polygon/polygon. |
| Syntax | LENGTH(geometry, 'units') |
| Output | Number |
| Definition | Returns the geodetic path length of the line string or strings in the <geometry> using the given <units>. |
| Example | LENGTH([Spatial], 'metres') |
| Notes | The result is <NaN> if the geometry argument has no linestrings, though other elements are permitted. |
| Syntax | MAKELINE(SpatialPoint1, SpatialPoint2) |
| Output | Geometry (line) |
| Definition | Generates a line mark between two points |
| Example | MAKELINE(MAKEPOINT(47.59, -122.32), MAKEPOINT(48.5, -123.1)) |
| Notes | Useful for building origin-destination maps. |
| Syntax | MAKEPOINT(latitude, longitude, [SRID]) |
| Output | Geometry (point) |
| Definition | Converts data from If the optional |
| Example | MAKEPOINT(48.5, -123.1) MAKEPOINT([AirportLatitude], [AirportLongitude]) MAKEPOINT([Xcoord],[Ycoord], 3493) |
| Notes |
You can use |
| Syntax | NO_CUTOUTS (spatial) |
| Output | Corrected spatial polygon |
| Definition | Returns a corrected spatial polygon if a flat-earth interpretation requires polygon inversions; otherwise, returns the original. |
| Notes | Spatial file formats like Keyhole Markup Language (.kml) require polygon boundaries to follow a specific coordinate direction. If a data set draws boundaries in reverse, Tableau interprets the exterior space as the shape. |
| Syntax | OUTLINE(spatial polygon) |
| Output | Geometry |
| Definition | Converts a polygon geometry into linestrings. |
| Notes | Useful for creating a separate layer for an outline that can be styled differently than the fill. Supports polygons within multipolygons. |
| Syntax | PARSE_WKT (String) |
| Output | Spatial (Geography) |
| Definition | Converts a text string field containing well-known text (WKT) representations of geographic entities (such as points, linestrings or polygons) into a spatial value. |
| Notes | Coordinates are assumed to use WGS-84 latitude and longitude. For more information about WKT, see Well-Known Text Representation of Geometry. |
| Syntax | SHAPETYPE(geometry) |
| Output | String |
| Definition | Returns a string describing the structure of the spatial <geometry>, such as Empty, Point, MultiPoint, LineString, MultiLinestring, Polygon, MultiPolygon, Mixed and unsupported. |
| Example | SHAPETYPE(MAKEPOINT(48.5, -123.1)) = "Point" |
| Syntax | SYMDIFFERENCE(spatial, spatial) |
| Output | Geometry |
| Definition | Computes any portions of regions from the second argument that overlap regions in the first argument and discards from both. Returns the remaining portions of regions from both arguments. |
| Example |
|
| Syntax | UNION(spatial 1, [spatial 2]) |
| Output | Geometry |
| Definition | Combines spatial geometries by dissolving adjacent or overlapping boundaries into a single spatial geometry. |
| Notes | When used with one argument ( When used with two arguments ( For points and linestrings, |
| Syntax | VALIDATE(spatial geometry) |
| Output | Geometry |
| Definition | Confirms topological correctness of the geometry in your spatial value. If the value cannot be used for analysis due to problems such as a polygon’s perimeter intersecting itself, then the result will be a null. If the geometry is correct, the result will be the original geometry. |
| Example |
|
| Syntax | REGEXP_REPLACE(string, pattern, replacement) |
| Output | String |
| Definition | Returns a copy of the given string where the regular expression pattern is replaced by the replacement string. |
| Example | REGEXP_REPLACE('abc 123', '\s', '-') = 'abc-123' |
| Notes | 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. |
| Syntax | REGEXP_MATCH(string, pattern) |
| Output | Boolean |
| Definition | Returns true if a substring of the specified string matches the regular expression pattern. |
| Example | REGEXP_MATCH('-([1234].[The.Market])-','\[\s*(\w*\.)(\w*\s*\])')=true |
| Notes | 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. |
| Syntax | REGEXP_EXTRACT(string, pattern) |
| Output | String |
| Definition | Returns the portion of the string that matches the regular expression pattern. |
| Example | REGEXP_EXTRACT('abc 123', '[a-z]+\s+(\d+)') = '123' |
| Notes | 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. |
| Syntax | REGEXP_EXTRACT_NTH(string, pattern, index) |
| Output | String |
| Definition | 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. |
| Example | REGEXP_EXTRACT_NTH('abc 123', '([a-z]+)\s+(\d+)', 2) = '123' |
| Notes | 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. |
| Selection tool | Rectangle | Radial | Lasso | Drive Time |
|---|---|---|---|---|
| Shape | Rectangle | Circle | Freeform path | Drive-time polygon |
| Basis | Visual boundary | Straight-line distance | Visual boundary | Travel time and routing |
| Network required | No | No | No | Yes |
| Extends past view | No | Yes | No | Yes |
| Fields excluded by default | Reasons for exclusion |
|---|---|
All unvisualised measures when there are more than 1,000 measures in the data source. All unvisualised dimensions when there are more than 1,000 dimensions in the data source. | Computing explanations for more than 1000 unvisualised measures or dimensions can take longer to compute, sometimes several minutes. These fields are excluded by default for initial analysis, but you can choose to include them for further analysis. In this situation, you might see an alert asking if you want Explain Data to consider more fields. Click the alert link to get more information. Click Explain All to run an analysis that includes more fields. |
| Fields that use geometry, latitude or longitude | Geometry, latitude or longitude by themselves can never be explanations. It is highly likely that an explanation that calls out the latitude or the longitude as an explanation is due to a spurious correlation and not a probable explanation. |
| Dimensions with high cardinality (dimensions with > 500 members) | High cardinality dimensions take longer to compute. Dimensions with more than 500 unique values will not be considered for analysis. |
| Groups, bins or sets | Not currently supported. |
| Table calculations | Table calculations cannot be analysed when table calculations are at a different level of detail than the view. |
| Unvisualised measures that can't be averaged | Unvisualised measures that can't be averaged include measures that are calculated fields where the calculation expression includes aggregations (display as AGG() fields when added to the sheet). |
| Discrete measures and continuous dimensions | Not currently supported. |
| Hidden fields | Not available. |
| Calculated fields with errors | No values present to analyse. |
| Number of records | Time to retrieve |
|---|---|
100,000 | 1.7 minutes |
250,000 | 4 minutes |
500,000 | 8.5 minutes |
Sales
| Product Catalogue
|
| Product ID | Product Name | Product ID | Sale Amount | Transaction Date |
| 1 | 10 Inch Tablet | 1 | 100 | 10/1/2012 |
| 1 | 10 Inch Tablet | 1 | 2000 | 10/2/2012 |
| 2 | Smart Phone | 2 | 50 | 9/30/2012 |
| 3 | Desk Lamp | 3 | 10 | 8/21/2012 |
| Location | Hyperforce Region | Pod (Pod Name) | IP Address and Range after Hyperforce Migration (Alternatively, search for the Hyperforce region in https://ip-ranges.salesforce.com/ip-ranges.json) | |
|---|---|---|---|---|
| Asia Pacific | Australia | ap-southeast-2 | prod-apsoutheast-a | 141.163.192.0/23 |
| India | ap-south-2 | prod-in-a | 141.163.216.0/24 | |
Indonesia | ap-southeast-3 | prod-apsoutheast-c | 141.163.212.0/24 | |
Japan | ap-northeast-1 | prod-apnortheast-a | 141.163.208.0/23 | |
Singapore | ap-southeast-1 | prod-apsoutheast-b | 141.163.196.0/23 | |
| South Korea | ap-northeast-2 | prod-kr-a | 141.163.200.0/23 | |
| Canada | Quebec | ca-central-1 | prod-ca-a | 155.226.152.0/23 |
| Europe | Germany | eu-central-1 | dub01 (DUB01) | 145.224.208.0/23 |
eu-west-1a (EW1A) | ||||
| Switzerland | eu-central-2 | prod-ch-a | 145.224.198.0/24 | |
| UK | eu-west-2 | prod-uk-a | 145.224.200.0/23 | |
| United States - West | Oregon | us-west-2 | 10ax (10AX) | 155.226.128.0/21 |
10ay (10AY) | ||||
10az (10AZ) | ||||
uw2b (UW2B) | ||||
prod-uswest-c | ||||
| United States - East | Virginia | us-east-1 | prod-useast-a | 155.226.144.0/22 |
prod-useast-b | ||||
us-east-1 (useast-1) | ||||
prod-useast-c | ||||
| Location | Hyperforce Region | Pod (Pod Name) | IP Address before Hyperforce Migration | |
|---|---|---|---|---|
| Asia Pacific | Australia | ap-southeast-2 | prod-apsoutheast-a | 3.25.37.32/28 |
Japan | ap-northeast-1 | prod-apnortheast-a | 18.176.203.96/28 | |
| Canada | Quebec | ca-central-1 | prod-ca-a | 3.98.24.208/28 |
| Europe | Germany Note: Formerly Ireland region prior to the Hyperforce migration. | eu-central-1 | dub01 (DUB01) | 34.246.74.86 52.215.158.213 |
eu-west-1a (EW1A) | 34.246.62.141 34.246.62.203 | |||
| UK | eu-west-2 | prod-uk-a | 18.134.84.240/28 | |
| United States - West | Oregon | us-west-2 | 10ax (10AX) | 34.208.207.197 52.39.159.250 |
10ay (10AY) | 34.218.129.202 52.40.235.24 | |||
10az (10AZ) | 34.218.83.207 52.37.252.60 | |||
us-west-2b (UW2B) | 34.214.85.34 34.214.85.244 | |||
| United States - East | Virginia | us-east-1 | prod-useast-a | 3.219.176.16/28 |
prod-useast-b | 3.219.176.16/28 | |||
us-east-1 (useast-1) | 50.17.26.34 52.206.162.101 | |||
| Location | Hyperforce Region | Pod (Pod Name) | IP Address and Range/VPCE ID | |
|---|---|---|---|---|
| Asia Pacific | Australia | ap-southeast-2 | prod-apsoutheast-a | 141.163.192.0/23 |
| India | ap-south-2 | prod-in-a | 141.163.216.0/24 vpce-02e14aeeeccOa2eef | |
Indonesia | ap-southeast-3 | prod-apsoutheast-c | 141.163.212.0/24 | |
Japan | ap-northeast-1 | prod-apnortheast-a | 141.163.208.0/23 | |
Singapore | ap-southeast-1 | prod-apsoutheast-b | 141.163.196.0/23 | |
| South Korea | ap-northeast-2 | prod-kr-a | 141.163.200.0/23 vpce-053ebbbe86f5411ca | |
| Canada | Quebec | ca-central-1 | prod-ca-a | 155.226.152.0/23 |
| Europe | Germany | eu-central-1 | dub01 (DUB01) | 145.224.208.0/23 vpce-091ff41bc3686e6e8 |
eu-west-1a (EW1A) | ||||
| Switzerland | eu-central-2 | prod-ch-a | 145.224.198.0/24 vpce-0fbf9d552ffbb6be2 | |
| UK | eu-west-2 | prod-uk-a | 145.224.200.0/23 | |
| United States - West | Oregon | us-west-2 | 10ax (10AX) | 155.226.128.0/21 vpce-090a7c76e361d5013 |
10ay (10AY) | ||||
10az (10AZ) | ||||
uw2b (UW2B) | ||||
prod-uswest-c | ||||
| United States - East | Virginia | us-east-1 | prod-useast-a | 155.226.144.0/22 vpce-0ea40e596e16259d1 |
prod-useast-b | ||||
us-east-1 (useast-1) | ||||
prod-useast-c | ||||
| Not easily accessible - Too many marks | More accessible - Aggregated view |
|---|---|
 |  |
|
|
| Not easily accessible - Too little text | More accessible - Adding descriptive text to provide context |
|---|---|
 |  |
|
|
| Not easily accessible - Too little text | More accessible - More descriptive text |
|---|---|
 |  |
|
|
| Not easily accessible - Using only colour to differentiate marks | More accessible - Using colour and shape to differentiate marks |
|---|---|
 |  |
|
|
| Published separately | Embedded in workbook |
|---|---|
Publishing data sources is a step toward centralising data management. You can create policies geared toward minimising data source proliferation and helping people find the right data for the work they do. | Each embedded data source has a separate connection to the data. Each has the potential to show something different than the other at any given time (and data source proliferation is common). |
Meant to be shared; becomes available for other Tableau users to connect to. | Data is available only inside the workbook; it is not available for other Tableau Desktop users to connect to. |
Without content management and self-service guidelines, seeing a long list of data sources to connect to can be confusing to users who rely on the data to do their work, and is more difficult to manage on the server. | Users create their own connections, and they know exactly what data they’re getting. |
Someone who changes a shared data source might be uncertain or unaware of the effects that those changes have on connected workbooks. | Changing the data requires opening the workbook, where you can see the result of the change. |
Even if effects of data source changes on connected workbooks are planned, updating those connected workbooks is cumbersome. | Same as above; however, if multiple workbooks use similar data and need to be updated, it might be worth connecting to a published data source instead. |
Extracts can be refreshed on a schedule. You set up one refresh schedule for the extract, and all workbooks that connect to it always show the most current data. | Embedded extracts that aren’t refreshed can be useful for showing snapshots in time. If you want to keep the data fresh, each workbook must have its own refresh schedule. |
Generally helps you to optimise performance on the server or site. | Performance might be affected when the server contains multiple workbooks that connect to the same original data, and each workbook has its own refresh schedule. |
| Data Story Type | Description |
Change Over Time | What it does: Uses a chronology to illustrate a trend. Discussions it starts: Why did this happen, or why does it keep happening? What can we do prevent or make this happen? |
Drill Down | What it does: Sets context so that your audience better understands what's going on in a particular category. Discussions it starts: Why is this person, place or thing different? How does the performance of this person, place, or thing compare? |
Zoom Out | What it does: Describes how something your audience cares about relates to the bigger picture. Discussion it starts: How does something you care about compare to the bigger picture? What effect does one area have on the bigger picture? |
Contrast | What it does: Shows how two or more subjects differ. Discussions it starts: Why are these items different? How can we make A perform like B? Which area should we focus on and which area is doing fine? |
Intersections | What it does: Highlights important shifts when one category overtakes another. Discussions it starts: What causes these shifts? Are these shifts good or bad? How do these shifts affect other aspects of our plan? |
Factors | What it does: Explains a subject by dividing it into types or categories. Discussions it starts: Is there a particular category we should focus on more? How much do these items affect the metric we care about? |
Outliers | What it does: Shows anomalies or where things are exceptionally different. Discussions it starts: Why is this item different? |
| Before | After |
|---|---|
 |  |
| Original data source | Second data source |
 |  |
| Creates Vertical Bars | Creates Horizontal Bars |
 |  |
| Not supported. Table X has two incoming relationships that are both from tables downstream from Base Table A | Supported. Tables S and T both have multiple incoming relationships, but each one is from a different base table. | Supported. Although it may visually look like there's a cycle, the incoming relationships for both Table S and Table T can be traced back to different base tables. |
 |  |  |
| Creates Simple Scatter Plot | Creates Matrix of Scatter Plots |
 |  |
 |  |
| Less accessible – low contrast | More accessible – higher contrast |
 |  |
| Less accessible – too many marks | More accessible – aggregated view |
|---|---|
|  |
| Less accessible – too many marks | More accessible – aggregated and grouped view |
|---|---|
|  |
| Less accessible – unnecessary marks | More accessible – unnecessary marks removed |
|---|---|
|  |
| Not easily accessible | More accessible – Colour Blind palette and shapes |
|---|---|
 |  |
| Less accessible – too many marks | More accessible – less marks in the view |
|---|---|
|  |
One-to-one
Example: Every car has its own number plate and a number plate is specific to an individual car. Car-to-number plate is one-to-one. Note that even if a car is unregistered or a registration number hasn’t yet been assigned to a car, that discrepancy is described by the referential integrity. A car can only have one number plate and a number plate can only be assigned to one car, so the cardinality remains one-to-one. |
 |
One-to-many or Many-to-one
Examples: Many employees have the same manager. Employees-to-manager is many-to-one. Manager-to-employee is one-to-many. |
|
Many-to-many
Examples: An actor is in many films and a film has many actors. Actor-to-film is many-to-many. Multiple books can be purchased in the same transaction and a book can be purchased multiple times. ISBN-to-OrderID is many-to-many. |
 |
| Low Intensity (50%) | High Intensity (80%) |
 |  |
Change over time
Related topics
|
Showing a change over time for a measure is one of the fundamental categories of visualisations. There are many options for exploring change over time, including line charts, slope charts and highlight tables. To show change over time, you need to know the value you expect to change, and how to work with Date fields in Tableau. What kind of question does this chart answer?
|
Correlation
Related topics
|
Sometimes you have two variables and are looking for the relationship between them. For example, you may be looking for the relationship between classroom size and school graduation rate, or how much lung capacity relates to endurance. (But remember, correlation does not always equal causation.) Correlation can be shown with scatter plots or highlight tables, and you can use Tableau's analytics objects to show the strength of the correlation. What types of question can this chart answer?
|
Magnitude
Related topics
|
Magnitude shows the relative size or value of two or more discrete items. If you are comparing sales for different regions, you are looking at magnitude. Magnitude charts include bar charts, packed bubble charts, and line charts. What types of question can this chart answer?
|
Deviation
Related topics
|
Deviation charts show how far a value varies from some baseline, such as the average or median. If you wanted to know which items had unusually high or low profit margins, you would use a deviation chart. You can use bullet charts, bar charts, and combination charts to show deviation. You can also find the statistical significance of the deviation using a Z-score. What types of question can this chart answer?
|
Distribution
Related topics
|
When you are trying to find the frequency of events within a population, you are looking at the distribution. If you are showing the number of respondents to a survey by age, or the frequency of incoming calls by day, a distribution chart might be the best choice. Distribution charts include histograms, population pyramids, Pareto charts and box plots. What types of question can this chart answer?
|
Ranking
Related topics
|
Sometimes you not only want to depict the magnitude of some value, but also the relative ranking of all the members of your dimension. Showing the top ten sales people or demonstrating the under-performing states use a ranking chart. Ranking charts are usually bar charts that integrate rank calculations, top n sets, or key progress indicators. What types of question can this chart answer?
|
Part-to-Whole
Related topics
|
Part-to-Whole charts show how much of a whole an individual part takes up. For example, if you are showing how much each region contributes to overall sales, or how expensive each different shipping mode is for an individual product, you would use a part to whole chart. Part-to-Whole charts can be pie charts, area charts, stacked bar charts, or treemaps. What types of question can this chart answer?
|
Spatial
Related topics
|
Spatial charts can precise locations and geographical patterns in your data. Showing the airport terminals with the most foot traffic or a map of all sales across the country are examples of spatial maps. Spatial maps include filled maps, point distribution maps, symbol maps, and density maps. What types of question can this chart answer?
|
Flow
Related topics
|
Flow charts can be maps that convey movement over time, such as Sankey diagrams. Flow maps include path over time and path between origin and destination charts. What types of question can this chart answer?
|
| All Dimensions | Sub-Category | Region |
|---|---|---|
 |  |  |
| The 5 marks are combined and the rest of the marks are added to an "Other" category. | All marks associated with any of the three sub-categories are combined and everything else is added to an "Other" category. | All marks associated with the four regions are combined and everything else is added to an "Other" category. |
| Tableau Desktop version | Web version |
|
|
| Tableau Desktop version | Web version |
|
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| Tableau Desktop version | Web version |
|
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| Tableau Desktop version | Web version |
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| Tableau Desktop version | Web version |
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| Tableau Desktop version | Web version |
|
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| Limit | Default | Error message | Checked when |
| Data sources per composed data source | 500 | Too many data sources in this composed data source. | You open or use a composed data source, including loading a workbook using the data source. |
| Total dependencies | 100 | Publishing a data source with more than 100 PDS dependencies isn’t supported. | You publish a composed data source. |
| Nesting depth | 20 | Publishing a data source with more than 20 nested layers isn’t supported. | You publish a composed data source. |
 |  |
| Predict_Sales_City | Predict_Sales_State | Predict_Sales_Region |
MODEL_QUANTILE(0.5,sum([Sales]), | MODEL_QUANTILE(0.5,sum([Sales]), | MODEL_QUANTILE(0.5,sum([Sales]), |
Snowflake uses Okta as the default identity provider (IdP) that provides access tokens and authenticates identities. You’ll need to configure settings in Snowflake and Okta for OAuth and single sign-on (SSO) capabilities. In Okta, you’ll define Okta as an OAuth authentication server and identify Snowflake as an OAuth resource. Follow the steps in this Snowflake help topic: Configuring an Identity Provider for Snowflake. |  |
|  |
| Example story | Story breakdown |
| The first two sentences use average and range functions to write about the average, maximum and minimum values across the period you’re analysing. |
| The third sentence is about overall performance of the measure over the period. For example, a sentence can be about whether sales increased, decreased or trended differently during a specific period. |
| The fourth sentence uses progression analysis. This sentence writes about the largest increase and decrease based on the measure during the period using both a percentage basis and an absolute basis. |
| This sentence is a Correlation insight. This type of analytic insight writes about notable correlations between different series in your data. |
| This sentence is a Segment insight. This type of analytic insight writes about noteworthy increases and decreases over time. |
| This sentence is a Trend line insight. This type of insight writes about how well trends fit your data with a certain percentage of confidence, and trend lines allow you to make predictions based on historic trends. |
| Example story | Story breakdown |
| The first sentence calculates the total value of your measure. |
| The second sentence writes about the dimension drivers. In this example, the dimension drivers are the products that contributed the most to total sales. |
| The third and fourth sentences analyse the distribution of the data. This analyses the averages, medians, concentration of data (if any exist), and how the data is skewed. This helps identify how balanced these grouped variables are compared to one another. |
| This sentence uses Clustering to write about measures that can be grouped. This helps identify whether there are distinct groups that stand out in the data. |
| The final sentence writes about notable outliers. |
| Example story | Story breakdown |
| The first two sentences are powered by regression analytics. Regression shows how one measure affects another. Notice that in the first sentence, the story has identified a relationship between profit and sales. |
| The third sentence is derived from clustering. Clustering analytics tries to identify key groups or clusters across all the variables in the data. |
| The fourth sentence is written about outliers – values that fall significantly above or below the average. |
| The remaining sentences for scatter plot stories use range and average analysis to write insights. |
| Example story | Story breakdown |
| The first sentence calculates the total value of your measure. |
| The second sentence writes about drivers. In this example, the drivers are segments that contributed the most to total sales. |
| The final sentence analyses the distribution of the data. |
| November | December |
|---|---|
 |  |
| Orders | Vendors |
|---|---|
 |  |
| For Tableau Desktop | For Tableau Prep Builder | For Tableau Server, Tableau Prep Conductor, Tableau Prep Flow Authoring |
|---|---|---|
|
|
|
| For Tableau Desktop | For Tableau Prep Builder | For Tableau Server |
|---|---|---|
|
|
|
| For Tableau Desktop | For Tableau Prep Builder | For Tableau Server, Tableau Prep Conductor, Tableau Prep Flow Authoring |
|---|---|---|
|
|
To enable your connector for Prep, you also need to add your taco to the following locations:
|
| Discrete date part | Continuous date truncation |
 |  |
| Mode | Who Can Access |
|---|---|
Viewing mode | Tableau Viewers, Explorers and Creators who have the Run Explain Data permission capability can run and explore Explain Data explanations in viewing mode. |
Editing mode
| Tableau Creators can run Explain Data when editing a view in Tableau Desktop, Tableau Cloud or Tableau Server. Explorers who have the Run Explain Data permission capability and editing permissions can run Explain Data when editing a workbook in Tableau Cloud or Tableau Server. Creators and Explorers who have editing permissions can open new worksheets for further analysis. They can also use Explain Data Settings to control who can use Explain Data and what they can see. |
 | A. Day of month B. Month C. Year D. Hour, minute, second, millisecond, period |
 | A. Format B. String |
| Date Part | Symbol | Example Output |
|---|---|---|
| Year | yy y, yyyy Y | 26 2026 2026 (used for Week of Year-based calendars) |
| Quarter of year | Q QQQ QQQQ | 2 02 Q2 2nd quarter |
| Month | M MM MMM MMMM | 9 09 Sep September |
| Week of year | w, ww | 47 |
| Day of week | E, EE, EEE EEEE EEEEE | Mon Monday M |
| Day of month | d dd | 1, 15 01, 15 |
| Day of year (1–365) | D | 23, 143 |
Hour (1–12) | h hh | 8 08 |
| Hour (0–23) | H HH | 8 08 |
| Minute | m mm | 8 08 |
| Second in a minute | s ss | 5 05 |
| Fractional second | S SS SSS SSSS | 2 23 235 2350 |
| Milliseconds in day | A | 34532 |
| Period (am/pm marker) | a, aa, aaa | AM, am, PM |
| Time Zone | z, zz, zzz zzzz Z, ZZ, ZZZ ZZZZ | PDT Pacific Daylight Time -0800 PST-08:00 |
| Action | Result |
| Convert Discount from a measure to a dimension... | Sales values are no longer aggregated according to discount rate, resulting in a line chart instead of a scatter plot. |
| Convert Discount from continuous to discrete... | Tableau shows headers at the bottom of the view, instead of a continuous axis. |
| Workbooks | Data sources |
|---|---|
|
|
| Reason | Scenarios |
|---|---|
| You don’t have the correct permissions. |
|
| You can’t access the complete data. |
|
| The password for the workbook’s data source is not embedded or is no longer valid. |
|
| The data isn’t at the correct level of granularity. |
|
| The date dimension is not supported. |
|
| Min | The minimum value of the field. |
| Max | The maximum value of the field. |
| Diff | The difference between the minimum and maximum values of the field. |
| CntD | The number of distinct values (rows) in the data. |
| Version 9.x palette name | Version 9.x HEX Values |
|---|---|
Tableau 10 Now called Tableau Classic 10.
| <color-palette name="Classic 10" type="regular"> |
Tableau 10 Medium Now called Tableau Classic Medium.
| <color-palette name="Classic 10 Medium" type="regular">
|
Tableau 10 Light
| <color-palette name="Classic 10 Light" type="regular">
|
Tableau 20 Now called Tableau Classic 20.
| <color-palette name="Classic 20" type="regular">
<color>#9edae5</color>
<color>#17becf</color>
<color>#dbdb8d</color>
<color>#bcbd22</color>
<color>#c7c7c7</color>
<color>#7f7f7f</color>
<color>#f7b6d2</color>
<color>#e377c2</color>
<color>#c49c94</color>
<color>#8c564b</color>
<color>#c5b0d5</color>
<color>#9467bd</color>
<color>#ff9896</color>
<color>#d62728</color>
<color>#98df8a</color>
<color>#2ca02c</color>
<color>#ffbb78</color>
<color>#ff7f0e</color>
<color>#aec7e8</color>
<color>#1f77b4</color>
|
Grey 5
Replaced with Seattle Greys. | <color-palette name="Classic Gray 5" type="regular">
<color>#cfcfcf</color>
<color>#8f8782</color>
<color>#414451</color>
<color>#a5acaf</color>
<color>#60636a</color>
|
Colour Blind 10
Updated as Colour Blind. | <color-palette name="Classic Color Blind" type="regular">
|
Traffic Light
Updated asTraffic Light. | <color-palette name="Classic Traffic Light" type="regular">
|
Purple-Grey 6
Discontinued. | <color-palette name="Classic Purple-Gray 6" type="regular">
|
Purple-Grey 12
Updated as Purple-Pink-Grey. | <color-palette name="Classic Purple-Gray 12" type="regular">
|
Green-Orange 6
Discontinued. | <color-palette name="Classic Green-Orange 6" type="regular">
|
Green-Orange 12
Updated as Green-Orange-Teal. | <color-palette name="Classic Green-Orange 12" type="regular">
|
Blue-Red 6
Discontinued. | <color-palette name="Classic Blue-Red 6" type="regular">
|
Blue-Red 12
Updated as Blue-Red-Brown. | <color-palette name="Classic Blue-Red 12" type="regular">
|
Cyclic
Updated as Hue Circle. | <color-palette name="Classic Cyclic" type="regular"> |
Green
Updated. | <color-palette name="Classic Green" type="ordered-sequential">
|
Grey
Updated. | <color-palette name="Classic Gray" type="ordered-sequential">
|
Blue
Updated. | <color-palette name="Classic Blue" type="ordered-sequential">
|
Red
Updated. | <color-palette name="Classic Red" type="ordered-sequential">
|
Orange
Updated. | <color-palette name="Classic Orange" type="ordered-sequential">
|
Area Red
Discontinued. | <color-palette name="Classic Area Red" type="ordered-sequential">
|
Area Green
Discontinued. | <color-palette name="Classic Area Green" type="ordered-sequential">
|
Area Brown
Discontinued. | <color-palette name="Classic Area-Brown" type="ordered-sequential">
|
Red-Green Diverging
Updated. | <color-palette name="Classic Red-Green" type="ordered-diverging">
|
Red-Blue Diverging
Updated. | <color-palette name="Classic Red-Blue" type="ordered-diverging">
|
Red-Black Diverging
Updated. | <color-palette name="Classic Red-Black" type="ordered-diverging">
|
Area Red-Green Diverging
Discontinued. | <color-palette name="Classic Area Red-Green" type="ordered-diverging"> |
Orange-Blue Diverging
Updated. | <color-palette name="Classic Orange-Blue" type="ordered-diverging">
|
Green-Blue Diverging
Updated. | <color-palette name="Classic Green-Blue" type="ordered-diverging">
|
Red-White-Green Diverging
Updated. | <color-palette name="Classic Red-White-Green" type="ordered-diverging">
|
Red-White-Black Diverging
Updated. | <color-palette name="Classic Red-White-Black" type="ordered-diverging">
|
Orange-White-Blue Diverging
Updated. | <color-palette name="Classic Orange-White-Blue" type="ordered-diverging">
|
Red-White-Black Light
Discontinued. | <color-palette name="Classic Red-White-Black Light" type="ordered-diverging">
|
Orange-White-Blue Light Diverging
Discontinued. | <color-palette name="Classic Orange-White-Blue Light" type="ordered-diverging">
|
Red-White-Green Light Diverging
Discontinued. | <color-palette name="Classic Red-White-Green Light" type="ordered-diverging">
|
Red-Green Light Diverging
Discontinued. | <color-palette name="Classic Red-Green Light" type="ordered-diverging">
|
| If the smallest iframe dimension is... | This device layout appears... |
|---|---|
| 500 pixels or less | Phone |
| Between 501 and 800 pixels | Tablet |
| Greater than 800 pixels | Desktop |
| Latitude | Longitude |
| 32.2000 | -101.5000 |
| 38.5800 | -92.5800 |
| 41.2000 | -89.6800 |
| 39.2800 | -87.4000 |
| 41.7800 | -87.7800 |
| 39.5000 | -90.0800 |
| Columns shelf: | Longitude (continuous dimension, longitude geographic role assigned) |
| Rows shelf: | Latitude (continuous dimension, latitude geographic role assigned) |
| Mark type: | Automatic |
| Storm Name | Date | Latitude | Longitude | Basin | Wind Speed (kt) |
| PAKHAR | 3/26/12 12:00:00 | 9.5000 | 115.700 | West Pacific | 0 |
| PAKHAR | 3/26/12 06:00:00 | 9.5000 | 115.400 | West Pacific | 0 |
| PAKHAR | 3/26/12 12:00:00 | 9.5000 | 115.100 | West Pacific | 0 |
| PAKHAR | 3/26/12 18:00:00 | 9.4000 | 114.800 | West Pacific | 0 |
| PAKHAR | 3/27/12 12:00:00 | 9.4000 | 114.500 | West Pacific | 0 |
| PAKHAR | 3/27/12 06:00:00 | 9.4000 | 114.300 | West Pacific | 35 |
| Columns shelf: | Longitude (continuous measure, longitude geographic role assigned) |
| Rows shelf: | Latitude (continuous measure, latitude geographic role assigned) |
| Detail: | Dimension (unique ID for each path) |
| Path: | Date field or order field to define order to connect the data points |
| Mark type: | Line |
| Line | Line Group (Path ID) | Order of Points | Station | Latitude | Longitude | Traffic |
| 1 | 1 | 1 | La Défense (Grande Arche) | 48.891934 | 2.237883 | 14,275,382 |
| 1 | 1 | 2 | Esplanade de la Défense | 48.887843 | 2.250442 | 9,843,051 |
| 1 | 1 | 3 | Pont de Neuilly | 48.884509 | 2.259892 | 6,902,931 |
| 10 BOUCLE | 10 | 1 | Boulogne-Jean-Jaurès | 48.842222 | 2.238836 | 3,847,782 |
| 10 BOUCLE | 10 | 2 | Porte d'Auteuil | 48.848074 | 2.258648 | 687,237 |
| 10 BOUCLE | 10 | 3 | Michel-Ange-Auteuil | 48.847740 | 2.264297 | 2,222,709 |
| Columns shelf: | Longitude (continuous measure, longitude geographic role assigned) |
| Rows shelf: | Latitude (continuous measure, latitude geographic role assigned) |
| Detail: | Path ID field (discrete dimension) |
| Path: | Order field (continuous dimension) |
| Mark type: | Line |
| Origin-Destination | Station | Path ID | Latitude | Longitude |
| Origin | BT-01 | BT-01_BT-01 | 47.61841 | -122.35101 |
| Destination | BT-01 | BT-01_BT-01 | 47.61841 | -122.35101 |
| Origin | BT-01 | BT-01_BT-03 | 47.61841 | -122.35101 |
| Destination | BT-03 | BT-01_BT-03 | 47.61576 | -122.34843 |
| Origin | BT-01 | BT-01_BT-04 | 47.61841 | -122.35101 |
| Destination | BT-04 | BT-01_BT-04 | 47.61613 | -122.34108 |
| Origin | BT-01 | BT-01_BT-05 | 47.61841 | -122.35101 |
| Destination | BT-05 | BT-01_BT-05 | 47.61303 | -122.34410 |
| Origin-Destination | Location Name | Path ID | Latitude | Longitude |
| Origin | BT-01 | BT-01_BT-01 | 47.61841 | -122.35101 |
| Destination | BT-01 | BT-01_BT-01 | 47.61841 | -122.35101 |
| Origin | BT-01 | BT-01_BT-03 | 47.61841 | -122.35101 |
| Destination | BT-03 | BT-01_BT-03 | 47.61576 | -122.34843 |
| Columns shelf: | Longitude (continuous dimension, longitude geographic role assigned) |
| Rows shelf: | Latitude (continuous dimension, latitude geographic role assigned) |
| Detail: | Path ID field (discrete dimension) |
| Mark type: | Line |
| Earthquake Date Time | ID | Magnitude | Magnitude^10 | Latitude | Longitude |
| 1/1/73 | centennial19730101114235 | 6.00000 | 17,488,747.04 | -35.570 | -15.427 |
| 02/01/1973 | pde19730102005320300_66 | 5.50000 | 25,329,516.21 | -9.854 | 117.427 |
| 03/01/1973 | pde19730103022942800_33 | 4.80000 | 6,492,506.21 | 1.548 | 126.305 |
| 04/01/1973 | pde19730104003142000_33 | 4.50000 | 3,405,062.89 | 41.305 | -29.272 |
| 05/01/1973 | pde19730105003948200_36 | 4.70000 | 5,259,913.22 | 0.683 | -80.018 |
| 06/01/1973 | pde19730106061852300_83 | 4.90000 | 7,979,226.63 | -22.354 | -69.310 |
| Columns shelf: | Longitude (continuous measure, longitude geographic role assigned) |
| Rows shelf: | Latitude (continuous measure, latitude geographic role assigned) |
| Detail: | One or more dimension fields |
| Size: | A measure field (aggregated) |
| Mark type: | Automatic |
| State | County | Obesity Percent - 2012 |
| Alabama | Autauga County | 30.9000 |
| Alabama | Baldwin County | 26.7000 |
| Alabama | Barbour County | 40.8000 |
| Alabama | Bibb County | 40.1000 |
| Alabama | Blount County | 32.4000 |
| Alabama | Bullock County | 44.5000 |
| Columns shelf: | Longitude (continuous measure, longitude geographic role assigned) |
| Rows shelf: | Latitude (continuous measure, latitude geographic role assigned) |
| Detail: | One or more geographic units (dimensions with geographic roles assigned) |
| Colour: | Measure or dimension |
| Mark type: | Automatic or Map |
| Forecast mark type | Prediction intervals displayed using |
| Line | Bands |
| Shape, square, circle, bar or pie | Whiskers |
Actian Matrix* Alibaba AnalyticDB for MySQL‡ Alibaba Data Lake Analytics‡ Alibaba MaxCompute‡ Amazon Athena‡ Amazon Aurora for MySQL‡ Amazon EMR Hadoop Hive‡ Amazon Redshift‡ Apache Drill‡ Aster Database* Azure Data Lake Storage Gen2‡ Box‡ Cloudera Hadoop‡ Databricks‡ Datorama by Salesforce‡ Denodo‡ Dremio by Dremio‡ Dropbox‡ Esri Connector‡ Exasol‡ | Google BigQuery**‡ Google BigQuery JDBC**‡ Google Cloud SQL‡ Google Drive‡ Impala‡ Kognito* Kyvos‡ Hortonworks Hadoop Hive IBM BigInsights IBM DB2‡ IBM PDA (Netezza)* Kyvos‡ MariaDB‡ MarkLogic* Microsoft Azure SQL Database‡ Microsoft Azure Synapse Analytics‡ Microsoft SQL Server‡ MonetDB* MongoDB BI Connector‡ MySQL‡ | OData‡ OneDrive‡ Oracle‡ Pivotal Greenplum Database‡ PostgreSQL‡ Progress OpenEdge* Presto‡ Qubole Presto‡ SAP HANA (for virtual connections only)‡ SAP Sybase ASE* SAP Sybase IQ* Salesforce‡ SharePoint Lists‡ SingleStore (formerly MemSQL)‡ Snowflake‡ Spark SQL‡ Teradata***‡ Vertica‡ |
Alibaba AnalyticsDB for MySQL‡ Alibaba Data Lake Analytics‡ Amazon Athena‡ Amazon Aurora for MySQL‡ Amazon EMR Hadoop Hive‡ Amazon Redshift‡ Apache Drill‡ Azure Data Lake Storage Gen2‡ Azure Synapse Analytics (SQL Server compatible) Box‡ Cloudera Hadoop‡ Databricks‡ Datorama by Salesforce‡ Denodo‡ Dremio by Dremio‡ | Dropbox*‡ Esri Connector‡ Exasol‡ Google BigQuery*‡ Google Cloud SQL (MySQL compatible)‡§ Google Drive‡ Hortonworks Hadoop Hive Impala‡ Kyvos‡ MariaDB‡ Microsoft Azure SQL Database‡ Microsoft Azure Synapse Analytics‡ Microsoft SQL Server‡ MongoDB BI Connector‡ MySQL‡ | OData‡ OneDrive*‡ Oracle‡ Pivotal Greenplum Database‡ PostgreSQL‡ Presto‡ Qubole Presto‡ Salesforce‡ SAP HANA (for virtual connections only)‡ SharePoint Lists‡ SingleStore (formerly MemSQL)‡ Snowflake‡ Spark SQL‡ Teradata**‡ Vertica‡ |
Google Drive OData |
| Feature | Status for Cube Data Sources |
| Actions | With Microsoft Analysis Services connections, drill-down actions defined in the cube are not available in Tableau. Cube data sources do not accept actions from relational or other cube data sources. For example, suppose you have a workbook with a view that uses a MySQL data source, a second view that uses cube data source A, and a third view that uses cube data source B. Actions in the view using the MySQL data source won't affect the views using the cube data sources, and actions in the view for one cube data source won’t affect the other. But actions in the views using the cube data sources will affect the view using the MySQL data source. |
| Advanced analytics features | Level of detail expressions, trend lines, forecasting, and clustering are not supported for cube data sources. |
| Aggregate calculation functions | Cube data sources are pre-aggregated and thus do not support aggregation functions, such as SUM(), AVG(), and CNT().It may be possible to use Table Calculations to perform aggregation operations on the cell-level results from the cube in Tableau. |
| Aliases | Aliases for cube databases are created by the cube's designer and can be activated in Tableau by selecting the data source from the Data menu and then choosing Alias File. Talk to your database administrator to find out whether your database has aliases available. Aliases are not supported by Microsoft Analysis Services databases. By default, the alias for every member of every dimension is initially defined to be the original member name. |
| Bins | For cube data sources, the Create Bin command is not available for measures. You can, however, write a calculation that takes cube cell results and bins them. For example:
|
| Cube KPI data type | When connected to Microsoft Analysis Services, any KPI calculations defined in the cube are not available. However, you can write your own KPI calculations in Tableau. You can also use Tableau parameters to create highly flexible what-if KPI analysis. For more information, see Visualise Key Progress Indicators. |
| Cube lag functions | For cube data sources, you cannot use cube lag functions in the Tableau calculation editor. You can use Tableau Table Calculations to calculate certain percentages and totals instead. For more information, see Transform Values with Table Calculations. Alternatively, you can use an MDX Lag function directly in Tableau using a calculated member. For example:
|
| Custom multidimensional expression (MDX) statements | When connected to a cube, you cannot make a connection to a custom MDX statement. All sub-cube definitions need to be created on the server by implementing necessary cube perspectives, partitions, dimensions or cell security. |
| Data blending | Cube data sources can only be used as the primary data source for blending data in Tableau. They cannot be used as secondary data sources. For details, see Troubleshoot Data Blending. |
| Date dimensions | For cube data sources, date dimensions are typically organised into hierarchies that contain levels such as year, quarter, and month. In addition, some multidimensional data sources have time intelligence enabled, which makes it possible to look at data levels different ways, such as Months by Year, Months by Quarter, Weekends, etc. These levels are represented as attributes of the hierarchy. For details, see Dates and Times. |
| Data source filters | Data source filters are not available for cube data sources. All field values must be defined in the cube prior to analysis in Tableau. |
| Extracts | You cannot create extracts from most cube data sources. Cube and relational data sources have incompatible data structures, which makes extracting data from a cube and storing it in a relational data source, such as the data engine, impossible in most cases. Starting in 10.4, you can create SAP BW extracts without the need for a special product key from Tableau. For information about support for and limitations of SAP BW extracts, see SAP NetWeaver Business Warehouse. |
| Filters | When you display a filter for a cube dimension, all levels of the hierarchy for that dimension are included in the filter. For example:
You can use cube attributes as filters, to show just a single level instead of a hierarchy. In the Data pane, attributes appear in the Dimensions section and are indicated by this icon: Slicing filters behave differently with a cube data source than with a relational data source. See Create Slicing Filters for details. Some dimension filter card options are not available. For example, single value (drop-down), multiple values (custom list), etc. Instead, dimensional filters shown in the view retain their hierarchical look and feel, and cannot be changed into specific list types. You can create a Tableau set containing certain values from the hierarchy and then use the set as a filter in the view with the expected filter options (right-click the set in the Data pane, and then click Show Filter). |
| Groups | You cannot create groups when working with a cube data source. Any concept of groupings should be pre-defined in the cube as dimensional attributes or cube sets. However, you can write multidimensional expressions (MDX) directly in Tableau using a calculated member to create a group. For example:
|
| Hierarchies | For cube data sources, hierarchies must be defined in the cube prior to analysis. |
| Parameters | For cube data sources, you cannot use parameter values to filter dimensions in an MDX calculation. |
| Publishing | Workbooks using cube data source can be published to Tableau Server, but do not support pass-through connections. This means that you cannot make a connection from Tableau Server using such a data source. It also means you cannot create a workbook using the data source in Tableau Server. For details, see Cube Data Sources in the Tableau Server help. Publishing a cube data source to Tableau Server gives you the ability to store the data source on the server. However, to use the data source, you must download the data source to Tableau Desktop and use it locally. Workbooks that use cube data source cannot be published to Tableau Cloud. |
| Sets | Cube data sources support hierarchical sets, which filter data to the selected members and all of their descendants. For details, see Examples of sets. |
| Tableau string functions | With cube data sources, dimensions are not available in the calculation editor. However, you can write MDX inside Tableau using a calculated member to manipulate dimensional values. For example:
|
| Type conversions | For cube data sources, some type conversion functions are not available in the calculation editor. As a rule, data type conversions should be defined in the cube prior to analysis. In particular, changing the data type of a cube dimension to a date in Tableau sometimes gives incorrect information. This feature is supported for some cube dimensions, depending on how the dates are formatted in the cube. You can write Multidimensional Expressions (MDX) directly in Tableau using a calculated member to change the data type of a cube dimension to a date. For example:
|
| Symbol | Description |
| (:) | Time separator. In some locales, a different character is used to represent the time separator. The time separator separates hours, minutes and seconds when time values are formatted. The actual character used as the time separator in formatted output is determined by your system settings. |
| (/) | Date separator. In some locales, a different character is used to represent the date separator. The date separator separates the day, month and year when date values are formatted. The actual character used as the date separator in formatted output is determined by your system settings. |
| c | Display the date as ddddd and display the time asttttt, in that order. Display only date information if there’s no fractional part to the date serial number; display only time information if there’s no integer portion. |
| d | Display the day as a number without a leading zero (1–31). |
| dd | Display the day as a number with a leading zero (01–31). |
| ddd | Display the day as an abbreviation (Sun, Sat). |
| dddd | Display the day as a full name (Sunday, Saturday). |
| ddddd | Display the date as a complete date (including day, month and year), formatted according to your system's short date format setting. The default short date format is m/d/yy. |
| dddddd | Display a date serial number as a complete date (including day, month and year) formatted according to the long date setting recognised by your system. The default long date format is mmmm dd, yyyy. |
| aaaa | The same as dddd, only it's the localised version of the string. |
| w | Display the day of the week as a number (1 for Sunday through 7 for Saturday). |
| ww | Display the week of the year as a number (1–54). |
| M | Display the month as a number without a leading zero (1 12). If m immediately follows h or hh, the minute rather than the month is displayed. |
| MM | Display the month as a number with a leading zero (01–12). If m immediately follows h or hh, the minute rather than the month is displayed. |
| MMM | Display the month as an abbreviation (Jan–Dec). |
| MMMM | Display the month as a full month name (January–December). |
| MMMMM | Display the month as a single letter abbreviation (J–D) |
| oooo | The same as MMMM, but localised. |
| q | Display the quarter of the year as a number (1–4). |
| y | Display the day of the year as a number (1–366). |
| yy | Display the year as a 2-digit number (00–99). |
| yyyy | Display the year as a 4-digit number (100–9999). |
| h | Display the hour as a number without leading zeros (0–23). |
| Hh | Display the hour as a number with leading zeros (00–23). |
| N | Display the minute as a number without leading zeros (0 59). |
| Nn | Display the minute as a number with leading zeros (00 59). |
| S | Display the second as a number without leading zeros (0 59). |
| Ss | Display the second as a number with leading zeros (00 59). |
| 000 | Display milliseconds. Use a period character as a separator before specifying milliseconds. |
| t t t t t | Display a time as a complete time (including hour, minute and second), formatted using the time separator defined by the time format recognised by your system. A leading zero is displayed if the leading zero option is selected and the time is before 10:00 A.M. or P.M. The default time format is h:mm:ss. |
| AM/PM | Use the 12-hour clock and display an uppercase AM with any hour before noon; display an uppercase PM with any hour between noon and 11:59 P.M. |
| am/pm | Use the 12-hour clock and display a lowercase AM with any hour before noon; display a lowercase PM with any hour between noon and 11:59 P.M. |
| A/P | Use the 12-hour clock and display an uppercase A with any hour before noon; display an uppercase P with any hour between noon and 11:59 P.M. |
| a/p | Use the 12-hour clock and display a lowercase A with any hour before noon; display a lowercase P with any hour between noon and 11:59 P.M. |
| AMPM | Use the 12-hour clock and display the AM string literal as defined by your system with any hour before noon; display the PM string literal as defined by your system with any hour between noon and 11:59 P.M. AMPM can be either uppercase or lowercase, but the case of the string displayed matches the string as defined by your system settings. The default format is AM/PM. |
| Symbol | Description |
| g | Short era name (such as H for the Heisei era). |
| gg | Era name (such as 平成). |
| ggg | Long era name (for Japanese, this is the same as the regular era name). |
| e | Era-based year, such as 1 for the first year of an era. |
| ee | Era-based year, such as 01 for the first year of an era. If there’s only one digit, then the era-based year will have a zero added to the front. |
| Date Part | Symbol | Example Output |
|---|---|---|
| Year | yy y, yyyy Y | 26 2026 2026 (used for Week of Year-based calendars) |
| Quarter of year | Q QQQ QQQQ | 2 02 Q2 2nd quarter |
| Month | M MM MMM MMMM | 9 09 Sep September |
| Week of year | w, ww | 47 |
| Day of week | E, EE, EEE EEEE EEEEE | Mon Monday M |
| Day of month | d dd | 1, 15 01, 15 |
| Day of year (1–365) | D | 23, 143 |
Hour (1–12) | h hh | 8 08 |
| Hour (0–23) | H HH | 8 08 |
| Minute | m mm | 8 08 |
| Second in a minute | s ss | 5 05 |
| Fractional second | S SS SSS SSSS | 2 23 235 2350 |
| Milliseconds in day | A | 34532 |
| Period (am/pm marker) | a, aa, aaa | AM, am, PM |
| Time Zone | z, zz, zzz zzzz Z, ZZ, ZZZ ZZZZ | PDT Pacific Daylight Time -0800 PST-08:00 |
| Unit of time | Notes |
|---|---|
| Era | n/a |
| Year | All symbols are supported in .hyper extracts except for "U". Notes:
|
| Month | All symbols are supported in .hyper extracts except for "I". Notes:
|
| Week | All symbols are supported in .hyper extracts except for "W". Notes:
|
| Day | Notes:
|
| Hour | Only "h" and "H" symbols are supported in .hyper extracts. Notes:
|
| Minute | Note: In contrast to ICU, .hyper extracts don't allow negative values for this field. Negative values will cause an error. |
| Second | Notes:
|
| Quarter | Note: In contrast to ICU, .hyper extracts only allow values 1–4. All other values cause an error. |
| Weekday | Notes:
|
| Period | n/a |
| Normal | Light | Dark |
 |  |  |
| Streets | Outdoors | Satellite |
 |  |  |
| Layer Name | Description | present in map style |
|---|---|---|
| Base | Shows the base map including water and land areas. | All |
| Land Cover | Shades wilderness areas and parks to give the map more depth. | All except Satellite |
| Terrain | Displays a relief of vertical elevation changes. | All except Satellite |
| Coastlines | Displays coastlines. | Light, Dark, Normal |
| Streets, Highways/Motorways, Routes | Marks dual-carriageways and motorways as well as small city streets. This layer includes the motorway and street names as well. | All |
| Light Country/Region Borders | Shows a light grey outline of country/region borders and names. | Light, Dark, Normal |
| Light Country/Region Names | Shows country and region names in a light grey. | Light, Dark, Normal |
| Country/Region Borders | Highlights country and region borders in a darker grey. | All |
| Country/Region Names | Highlights country and region names in a darker grey. | All |
| Light State/Province Borders | Shows a light grey outline of state borders and names. | Light, Dark, Normal |
| Light State/Province Names | Shows state and province names in a light grey. | Light, Dark, Normal |
| State/Province Borders | Highlights state and province borders in a darker grey. | All |
| State/Province Names | Highlights state and province names in a darker grey. | All |
| County Borders | Highlights second-level administration borders and US county borders. | Light, Dark, Normal |
| County Names | Highlights second-level administration names and US county names. | Light, Dark, Normal |
| Postcode Boundaries | Marks zip code and postcodes boundaries for US and select countries. You must zoom in to see this layer. | Light, Dark, Normal |
| Postcode Labels | Shows labels of zip code and postcodes boundaries for US and select countries. You must zoom in to see this layer. | Light, Dark, Normal |
| Area Code Boundaries | Marks US area code boundaries. You must zoom in to see this layer. | Light, Dark, Normal |
| Area Code Labels | Shows labels for the US area codes. You must zoom in to see this layer. | Light, Dark, Normal |
| US Metro Boundaries (CBSA) | Marks US Metropolitan Statistical Areas and Micropolitan area boundaries. | Light, Dark, Normal |
| US Metro Labels (CBSA) | Shows labels for the US Metropolitan Statistical Areas and Micropolitan areas. | Light, Dark, Normal |
| Water Labels | Shows labels for bodies of water. | All |
| Cities | Shows labels for cities. | All |
| Points of Interest | Displays labels for points of interest such as schools, parks, cemeteries, businesses and important buildings. This layer is dependent on the zoom level. | All |
| Neighbourhoods | Shows labels for neighbourhoods in cities. You must zoom in to see this layer. | All |
| Subway/Underground and Train Stations | Displays the names of subway/underground and train stations. You must zoom in to see this layer. | All except Satellite |
| Building Footprints | Shows the outline of buildings, where available. You must zoom in to see this layer. | Satellite, Streets, Outdoors |
| House Numbers | Displays the house numbers of buildings, with and without building footprints. You must zoom in to see this layer. | Streets, Outdoors |
| Contour Lines | Displays lines indicating vertical elevation change in metres. This layer is dependent on zoom level. | Outdoors |
| Aggregation | Description | Result for measure that contains 1, 2, 2, 3 |
|---|---|---|
| Attribute | Returns the value of the given expression if it only has a single value for all rows in the group, otherwise it displays an asterisk (*) character. Null values are ignored. This aggregation is useful when aggregating a dimension. To set a measure in the view to this aggregation, right-click (control-click on Mac) the measure and choose Attribute. The field then changes to show the text ATTR:
| * |
| Dimension | Returns all unique values in a measure or dimension. | 3 values (1, 2, 3) |
| Sum | Returns the sum of the numbers in a measure. Null values are ignored. | 1 value (8) |
| Average | Returns the arithmetic mean of the numbers in a measure. Null values are ignored. | 1 value (2) |
| Count (Distinct) | Returns the number of unique values in a measure or dimension. When applied to a dimension, Tableau creates a new temporary column that is a measure because the result of a count is a number. You can count numbers, dates, booleans and strings. Null values are ignored in all cases. This aggregation isn’t available for the following types of workbooks:
If you’re connected to a workbook that uses of one of these types, Count (Distinct) is unavailable and Tableau shows the message "Requires extract". To use this aggregation, extract your data. See Extract Your Data. | 1 value (3) |
| Minimum | Returns the smallest number in a measure or continuous dimension. Null values are ignored. | 1 value (1) |
| Maximum | Returns the largest number in a measure or in the given expression based on a sample population. Null values are ignored. Returns a Null if there are fewer than 2 members in the sample that aren’t Null. Use this function if your data represents a sample of the population. | 1 value (3) |
| Std. Dev (Pop.) | Returns the standard deviation of all values in the given expression based on a biased population. Assumes that its arguments consist of the entire population. Use this function for large sample sizes. | 1 value (0.7071) |
| Variance | Returns the variance of all values in the given expression based on a sample. Null values are ignored. Returns a Null if there are fewer than 2 members in the sample that are not Null. Use this function if your data represents a sample of the population. | 1 value (0.6667) |
| Variance (Pop.) | Returns the variance of all values in the given expression based on a biased population. Assumes that its arguments consist of the entire population. Use this function for large sample sizes. | 1 value (0.5000) |
| Disaggregate | Returns all records in the underlying data source. To disaggregate all measures in the view, select Aggregate Measures from the Analysis menu (to clear the check mark). Tableau allows you to view data in disaggregated form (relational databases only). When data are disaggregated, you can view the individual rows of your data source. For example, after discovering that the sum of sales for rubber bands is $14,600, you might want to see the distribution of individual sales transactions. To answer this question, you must create a view that shows individual rows of data. That is, you must disaggregate the data (see How to Disaggregate Data). Another way to look at disaggregated data is to view the underlying data for all or part of a view. For more details, see View Underlying Data. | 4 values (1, 2, 2, 3) |
| Capability | Data Blending | Custom Geocoding |
| Plot your own locations on a map view | Yes | Yes |
| Use any data | Yes | No, text files only |
| Add new geographic roles | No | Yes |
| Add to an existing geographic role | No | Yes |
| Create new geographic hierarchies | No | Yes |
| Can be reused for other workbooks | No | Yes |
| Data Source | Support |
| Amazon EMR Hadoop Hive | Supported for Hive 0.13 and later. |
| Aster Database | Supported for version 4.5 and later. |
| Cloudera Hadoop | Supported for Hive 0.13 and later. |
| Cloudera Impala | Supported for Impala 1.2.2 and later. |
| Cubes (multidimensional data sources) | Not supported. |
| DataStax Enterprise | Not supported. |
| Firebird | Supported for version 2.0 and later. |
| Generic ODBC | Limited. Depends on the specific data source. |
| Google Big Query | Supported for standard SQL, not supported for legacy SQL. |
| Hortonworks Hadoop Hive | Supported for Hive 0.13 and later. On version 1.1 of HIVE level of detail expressions that produce cross joins are not reliable. Cross join occur when there is no explicit field to join on. For example, for a level of detail expression |
| IBM DB2 | Supported for version 8.1 and later. |
| MarkLogic | Supported for version 7.0 and later. |
| Microsoft Access | Not supported. |
| Microsoft Jet-based connections (legacy connectors for Microsoft Excel, Microsoft Access, and text) | Not supported. |
| Microsoft SQL Server | SQL Server 2005 and later. |
| Mongo DB | Not supported. |
| IBM PDA (Netezza) | Supported version 7.0 and later. |
| Oracle | Supported version 9i and later. |
| Actian Matrix (ParAccel) | Supported version 3.1 and later. |
| Pivotal Greenplum | Supported for version 3.1 and later. |
| PostgreSQL | Supported version 7 and later. |
| SAP Sybase IQ | Supported version 15.1 and later. |
| Splunk | Not supported. |
| Vertica | Supported for version 6.1 and later. |
| Icon | Data type |
|---|---|
 | Text (string) values |
 | Date values |
 | Date & Time values |
 | Numerical values (integer or decimal) |
 | Boolean operators (relational only) |
 | Geographic values (used with maps) |
 | Image role (used with image link URLs) |
 | Cluster Group (used with Find Clusters in Data) |
| Syntax | DATE(expression) |
| Output | Date |
| Definition | Returns a date given a number, string or date <expression>. |
| Example | DATE([Employee Start Date]) DATE("September 22, 2018") DATE("9/22/2018")DATE(#2018-09-22 14:52#) |
| Notes | Unlike
|
| Syntax | DATEADD(date_part, interval, date) |
| Output | Date |
| Definition | Returns the <date> with the specified number <interval> added to the specified <date_part> of that date. For example, adding three months or 12 days to a starting date. |
| Example | Push out all due dates by one week DATEADD('week', 1, [due date])Add 280 days to the date February 20, 2021 DATEADD('day', 280, #2/20/21#) = #November 27, 2021# |
| Notes | Supports ISO 8601 dates. |
| Syntax | DATEDIFF(date_part, date1, date2, [start_of_week]) |
| Output | Integer |
| Definition | Returns the difference between <date1> and <date2> expressed in units of <date_part>. For example, subtracting the dates someone entered and left a band to see how long they were in the band. |
| Example | Number of days between 25th March 1986 and 20th February 2021 DATEDIFF('day', #3/25/1986#, #2/20/2021#) = 12,751How many months someone was in a band DATEDIFF('month', [date joined band], [date left band]) |
| Notes | Supports ISO 8601 dates. |
| Syntax | DATENAME(date_part, date, [start_of_week]) |
| Output | String |
| Definition | Returns <date_part> of <date> as a string. |
| Example | DATENAME('year', #3/25/1986#) = "1986"DATENAME('month', #1986-03-25#) = "March" |
| Notes | Supports ISO 8601 dates. A very similar calculation is DATEPART, which returns the value of the specified date part as a continuous integer. By changing the attributes of the calculation’s result (dimension or measure, continuous or discrete) and the date formatting, the results of An inverse function is DATEPARSE, which takes a string value and formats it as a date. |
| Syntax | DATEPARSE(date_format, date_string) |
| Output | Date |
| Definition | The <date_format> argument describes how the <date_string> field is arranged. Because of the variety of ways the string field can be ordered, the <date_format> must match exactly. For a full explanation and formatting details, see Convert a Field to a Date Field. |
| Example | DATEPARSE('yyyy-MM-dd', "1986-03-25") = #March 25, 1986# |
| Notes |
Inverse functions, which take dates apart and return the value of their parts, are |
| Database limitations |
|
| Syntax | DATEPART(date_part, date, [start_of_week]) |
| Output | Integer |
| Definition | Returns <date_part> of <date> as an integer. |
| Example | DATEPART('year', #1986-03-25#) = 1986DATEPART('month', #1986-03-25#) = 3 |
| Notes | Supports ISO 8601 dates. A very similar calculation is An inverse function is |
| Syntax | DATETRUNC(date_part, date, [start_of_week]) |
| Output | Date |
| Definition | Truncates the <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. |
| Example | DATETRUNC('day', #9/22/2018#) = #9/22/2018#DATETRUNC('iso-week', #9/22/2018#) = #9/17/2018#(the Monday of the week containing 22/09/2018) DATETRUNC(quarter, #9/22/2018#) = #7/1/2018# (the first day of the quarter containing 22/09/2018) Note: For week and iso-week, the |
| Notes | Supports ISO 8601 dates. You shouldn't use For example, |
| Syntax | DAY(date) |
| Output | Integer |
| Definition | Returns the day of the given <date> as an integer. |
| Example | Day(#September 22, 2018#) = 22 |
| Notes | See also WEEK, MONTH, QUARTER, YEAR and the ISO equivalents. |
| Syntax | ISDATE(string) |
| Output | Boolean |
| Definition | Returns true if a given <string> is a valid date. |
| Example | ISDATE(09/22/2018) = true ISDATE(22SEP18) = false |
| Notes | The required argument must be a string. ISDATE cannot be used for a field with a date data type – the calculation will return an error. |
| Syntax | ISOQUARTER(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based quarter of a given <date> as an integer. |
| Example | ISOQUARTER(#1986-03-25#) = 1 |
| Notes | See also ISOWEEK, ISOWEEKDAY, ISOYEAR and the non-ISO equivalents. |
| Syntax | ISOWEEK(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based week of a given <date> as an integer. |
| Example | ISOWEEK(#1986-03-25#) = 13 |
| Notes | See also ISOWEEKDAY, ISOQUARTER, ISOYEAR and the non-ISO equivalents. |
| Syntax | ISOWEEKDAY(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based weekday of a given <date> as an integer. |
| Example | ISOWEEKDAY(#1986-03-25#) = 2 |
| Notes | See also ISOWEEK, ISOQUARTER, ISOYEAR and the non-ISO equivalents. |
| Syntax | ISOYEAR(date) |
| Output | Integer |
| Definition | Returns the ISO8601 week-based year of a given <date> as an integer. |
| Example | ISOYEAR(#1986-03-25#) = 1,986 |
| Notes | See also ISOWEEK, ISOWEEKDAY, ISOQUARTER and the non-ISO equivalents. |
| Syntax | MAKEDATE(year, month, day) |
| Output | Date |
| Definition | Returns a date value constructed from the specified <year>, <month> and <day>. |
| Example | MAKEDATE(1986,3,25) = #1986-03-25# |
| Notes | Note: Incorrectly entered values will be adjusted into a date, such as Available for Tableau Data Extracts. Check for availability in other data sources.
|
| Syntax | MAKEDATETIME(date, time) |
| Output | Datetime |
| Definition | 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. |
| Example | MAKEDATETIME("1899-12-30", #07:59:00#) = #12/30/1899 7:59:00 AM#MAKEDATETIME([Date], [Time]) = #1/1/2001 6:00:00 AM# |
| Notes | This function is available only for MySQL-compatible connections (which for Tableau are MySQL and Amazon Aurora).
|
| Syntax | MAKETIME(hour, minute, second) |
| Output | Datetime |
| Definition | Returns a date value constructed from the specified <hour>, <minute> and <second>. |
| Example | MAKETIME(14, 52, 40) = #1/1/1899 14:52:40# |
| Notes | Because Tableau does not support a time data type, only datetime, the output is a datetime. The date portion of the field will be 1/1/1899. Similar function to |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MONTH(date) |
| Output | Integer |
| Definition | Returns the month of the given <date> as an integer. |
| Example | MONTH(#1986-03-25#) = 3 |
| Notes | See also DAY, WEEK, QUARTER, YEAR and the ISO equivalents |
| Syntax | NOW() |
| Output | Datetime |
| Definition | Returns the current local system date and time. |
| Example | NOW() = 1986-03-25 1:08:21 PM |
| Notes |
See also If the data source is a live connection, the system date and time could be in another time zone. For more information on how to address this, see the Knowledge Base. |
| Syntax | QUARTER(date) |
| Output | Integer |
| Definition | Returns the quarter of the given <date> as an integer. |
| Example | QUARTER(#1986-03-25#) = 1 |
| Notes | See also DAY, WEEK, MONTH, YEAR and the ISO equivalents |
| Syntax | TODAY() |
| Output | Date |
| Definition | Returns the current local system date. |
| Example | TODAY() = 1986-03-25 |
| Notes |
See also NOW, a similar calculation that returns a datetime instead of a date. If the data source is a live connection, the system date could be in another time zone. For more information on how to address this, see the Knowledge Base. |
| Syntax | WEEK(date) |
| Output | Integer |
| Definition | Returns the week of the given <date> as an integer. |
| Example | WEEK(#1986-03-25#) = 13 |
| Notes | See also DAY, MONTH, QUARTER, YEAR and the ISO equivalents |
| Syntax | YEAR(date) |
| Output | Integer |
| Definition | Returns the year of the given <date> as an integer. |
| Example | YEAR(#1986-03-25#) = 1,986 |
| Notes | See also DAY, WEEK, MONTH, QUARTER and the ISO equivalents |
| Format | Data Type | Value |
| 'March 25, 1986' | String | 'March 25, 1986' |
| #3/25/1986# | Date | #3/25/1986# |
| 25/03/1986 | Floating decimal | 0.00006042 |
| 25/03/1986 | Integer | 1,958 |
| March 25, 1986 | - | invalid |
| Variable | Meaning |
| t | Index of a period in a time series. |
| n | Time series length. |
| m | Number of periods in a season/cycle. |
| A(t) | Actual value of the time series at period t. |
| F(t) | Fitted or forecast value at period t. |
| Discrete Dimensions |  |
| Continuous Dimensions* |  |
| Discrete Measures |  |
| Continuous Measures |  |
| Continuous Quantity field | Discrete Quantity field | |
 |  |
| Related | Joined |
Using the related data source:
| Using the joined data source:
Our numbers here look a bit off. |
Primary data source
| Secondary data source
|
| Object Parameter | Values | Description | Examples |
|---|---|---|---|
dataDetails | no | Hides the Data Details button in the toolbar, which lets users see details about the data used in that view. | <param name='dataDetails' value='no' /> |
showDataDetails | yes | If Tableau Catalogue is enabled, it shows the view with the Data Details pane open. | <param name='showDataDetails' value='yes' /> |
alerts | no | Hides the Alerts button in the toolbar, which lets users create data-driven alerts. | <param name='alerts' value='no'/> |
customViews | no | Hides the View button in the toolbar, which lets users save custom views. | <param name='customViews' value='no'/> |
device | desktop; tablet; phone | If a dashboard has layouts for mobile devices, displays a specific layout, regardless of screen size. If this parameter isn't set, Tableau Server or Tableau Cloud detects screen size and loads a corresponding layout. See Embed Dashboards for examples. | <param name='device' value='phone'/> |
filter | string | Filters the data displayed when the view opens. You can also filter using URL parameters. | <param name='filter' value='Team=Blue'/> |
host_url | string | Required. The server name as it appears in the URL. | <param name='host_url' value='http://myserver.exampleco.com/'>
|
linktarget | string | The target window name for external hyperlinks. | <param name="linktarget" value="_blank"/> |
load-order | number | When multiple views are embedded, determines the order in which they load on the page. Negative numbers are allowed. | <param name="load-order" value="2"/> |
mobile | yes | Displays touch-optimised quick filters for mobile devices. | <param
name='mobile' value='yes'/> |
name | string | Required object parameter, with this structure: [workbook name]/[sheet name]/[optional custom view name] Format optional custom view names like this: username@domain/[custom view name] | <param name='name' value='ExampleCoSales/Sales'/>
|
:original_view | yes | If the name parameter refers to a workbook or sheet URL (and does not explicitly refer to a custom view) including this parameter displays the view as the original view. | <param name='filter' value=':original_view=yes'/> |
path(Tableau Server only. Not applicable to Tableau Cloud.) | string | For trusted authentication only, cannot be used with the ticket parameter. Overrides value of the name parameter and is used as the URL. For more information, see Display the View with the Ticket in the Tableau Server Administrator help. | <param name='path' value='trusted/Etdpsm_Ew6rJY-9kRrALjauU/views/workbookQ4/SalesQ4'/>
|
showShareOptions | true; false | Controls whether the Share options are displayed in an embedded view. | <param name='showShareOptions' value='true' /> |
site_root | string | Required. The site name. The Default site value is null (value=''). If your server is multi-site and you want to use trusted authentication, see Display the View with the Ticket in the Tableau Server help. | <param name='site_root' value='/#/Sales'/>
|
subscriptions | no | Hides the Subscriptions button in the toolbar, which lets users set up email subscriptions to receive snapshots of views at regular intervals. |
|
tabs | yes; no | Displays or hides tabs. | <param name='tabs' value='yes'/> |
ticket(Tableau Server only. Not applicable to Tableau Cloud.) | string | For trusted authentication only, cannot be used with the path object parameter. Must be used with name object to construct the trusted ticket redemption URL. For more information, see Display the View with the Ticket in the Tableau Server help. | <param name='ticket' value='9D1ObyqDQmSIOyQpKdy4Sw==:dg62gCsSE0QRArXNTOp6mlJ5'/>
|
toolbar | yes; no; top | The toolbar is displayed on the bottom by default. The toolbar is placed above the view when you set this parameter to topand excluded from the embedded view when you set it to no. | <param name='toolbar' value='top'/> |
tooltip | yes; no | Tooltips are displayed by default If you set this parameter to no, however, tooltips are excluded from the embedded view. | <param name='tooltip' value='no'/> |
| URL Parameter | Values | Description | Examples |
|---|---|---|---|
:dataDetails | no | Hides the Data Details button in the toolbar, which lets users see details about the data used in that view. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:dataDetails=no |
:showDataDetails | yes | If Tableau Catalogue is enabled, it shows the view with the Data Details pane open. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:showDataDetails=yes |
:alerts | no | Hides the Alerts button in an embedded view. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:alerts=no |
:customViews | no | Remember my changes option. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:customViews=no |
:device | desktop; tablet; phone | If a dashboard has layouts for mobile devices, displays a specific layout, regardless of screen size. If this parameter isn't set, Tableau Server or Tableau Cloud detects screen size and loads a corresponding layout. See Embed Dashboards for examples. | http://tabserver/views/sales/sales_dashboard?:device=tablet |
:display_count(Tableau Public only) | yes | Shows the total number of pageviews when you click the Tableau logo at the lower left. | https://public.tableau.com/en-us/s/gallery/what-emoji-say-about-music?:display_count=yes |
:embed | yes | Required URL parameter. Hides the top navigation area, better blending of the view into your web page. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes |
:format | pdf; png | Displays a view as a PDF or .png file. | http://tabserver/views/Sales/Q2?:format=pdf |
:highdpi | false | Renders a view using standard DPI (dots per inch) for high-resolution displays and devices. | http://tableauserver/views/Sales/Q2?:highdpi=false |
:linktarget | string | The target window name for external hyperlinks. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:linktarget=_blank |
:openid_hd | string | Used when authenticating with OpenID Connect. Specifies the hosted domain to which a user belongs. For example, you might use this option if you do not want to render the domain selection pane. Used in conjunction with :openid_login_hint to specify the full user identifier. | http://tabserver/views/Sales/Q2?:openid_hd=example.com |
:openid_login_hint | string | Used when authenticating with OpenID Connect. Specifies the full user identifier (email address). Used in conjunction with :openid_hd to specify the hosted domain to which the user belongs. | http://tabserver/views/Sales/Q2?:openid_login_hint=tara@example.com |
:record_performance(Tableau Server only. Not applicable to Tableau Cloud.) | yes | Starts a performance recording for a view. Add this at the end of the URL, immediately before the session ID (:iid=<n>). For more information, see Create a Performance Recording in Tableau Server help. | http://tabserver/views/Sales2013/Regions?:recordperformance=yes |
:refresh | yes | Renders the view using the latest data from Tableau Server or Tableau Cloud. See Refresh Data or Pause Automatic Updates for details. Tip: To continually refresh a view, in the | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:refresh=yes |
:render | true; false; number | If client-side rendering is enabled (the default), setting this to false forces server-side rendering for the session. Setting this to true forces client-side rendering for the session.A number from 1 to 100 can be entered to set the complexity threshold above which views are rendered by the server. For more information, see About Client-Side Rendering in Tableau Server help. | http://tabserver/views/Date-Time/DateCalcs?:render=false |
:revert | all; filters; sorts; axes; shelves | Returns the item to its original state. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:revert=all |
:showAppBanner | false | Hides the “Open in Tableau Mobile” banner in mobile web browsers. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:showAppBanner=false |
:showAskData | false | Hides the Ask Data button in the toolbar in an embedded view. By default the Ask Data button displays. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:showAskData=false |
:showShareOptions | true; false | Controls whether the Share options are displayed in an embedded view. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:showShareOptions=true |
:showVizHome(Tableau Public only) | yes; no | Shows or hides the content navigation interface of Tableau Public. Set to no when embedding vizzes in other web pages. | https://public.tableau.com/en-us/s/gallery/what-emoji-say-about-music?:showVizHome=no |
:subscriptions | no | Hides the Subscribe button in an embedded view. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:subscriptions=no |
:tabs | yes; no | Displays or hides tabs. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:tabs=no |
:toolbar | yes; no; top | The toolbar is displayed by default on the bottom when this parameter is not set. When no the toolbar is excluded from the embedded view. When top, the toolbar is placed above the view. | http://tabserver/views/Date-Time/DateCalcs?:embed=yes&:toolbar=no |
:tooltip | yes; no | Tooltips are displayed by default in a view when this parameter is not set. If set to no, tooltips are excluded from the embedded view. | http://tabserver/views/workbookQ4/SalesQ4?:embed=yes&:tooltip=no |
| If the smallest iframe dimension is... | This device layout appears... |
|---|---|
| 500 pixels or less | Phone |
| Between 501 and 800 pixels | Tablet |
| Greater than 800 pixels | Desktop |
| Parameter | Values | Description | Example |
|---|---|---|---|
| src (required) | string | The URL of the metric on Tableau Server or Tableau Cloud. | https://mycompany/#/metrics/1 |
link-target (HTML) linkTarget (JavaScript) (optional) | string | The URL that viewers will be directed to if they click on the metric. If no target is specified, the embedded metric will link to the source URL. | http://example.com |
| Profit vs. Sales with default aggregation | Profit vs. Sales with explicit aggregation |
 |  |
| Log File Location | Example of Record |
|---|---|
<install path>\Tableau Server\data\tabsvc\log\vizqlserver <install path>\Tableau Server\data\tabsvc\log\backgrounder <install path>\Tableau Server\data\tabsvc\log\dataserver <install path>\Tableau Server\data\tabsvc\log\vizportal | Found matching TDC 'C:\\ProgramData\\Tableau\\Tableau Server\\data\\tabsvc\\vizqlserver\\Datasources\\odbc-sqlite.tdc for class='genericodbc', vendor='SQLite', and driver='SQLite3 ODBC Driver' |
This explanation shows:
Exploration options:
Next steps for analysis:
|
In this example, a single extreme value of 463 hours rented is contributing to the higher-than-expected sum of Total Time Rented of 613 hours. A likely reason for this high value could be that someone forgot to dock the bike when they returned it. In this case, the author might want to exclude this value for future analysis.
| |
Visualise the DifferenceThis section shows:
Exploration options:
Next steps for analysis:
| 
In this example, when the extreme value of 483 is excluded, the analysed mark is no longer high compared to other marks in the view. Other marks now stand out. The author might want to explore the other marks to consider why these other locations have higher hours for bike rentals. |
This explanation shows:
Exploration options:
Next steps for analysis:
|
In this example, the percentage of null values in the target measure is shown as a blue circle. |
This explanation shows:
Exploration options:
Next steps for analysis:
|
In this example, the number of records for Trip Distance is listed for each value of Ride Month, which is a dimension in the original visualisation. August has the highest total trip distance value. You might explore whether August has the highest value for trip distance because more rides occurred in August, or if it has the highest trip distance because some rides were longer. |
This explanation shows:
Exploration options:
Next steps for analysis:
|  In this example, the average trip distance for August is not significantly higher or lower than most months. This suggests that trip distance is higher for August because there were more rides in August, rather than from people taking longer rides. |
This explanation shows:
Exploration options:
Next steps for analysis:
|  In this example, the statistical analysis has exposed that many of the rides come from the station neighbourhood of Back Bay. Note that Station Neighbourhood is an unvisualised dimension that has some relationship to Trip Distance in the underlying data for the source visualisation. |
This explanation shows:
Exploration options:
Next steps for analysis:
|  In this example, the statistical analysis has exposed that more rides were taken from South Station and MIT and fewer rides were taken from Charles Circle and Kendall, compared to rides taken for marks overall. Note that Station Name is an unvisualised dimension that has some relationship to Trip Distance in the underlying data for the source visualisation. |
This explanation shows:
Exploration options:
Next steps for analysis:
|  In this example, one possible reason why trip distance is high is because the average total time rented is also high. |
This explanation shows:
Exploration options:
Next steps for analysis:
|  In this example, a high percentage of records are associated with overcast weather. Because the data is about bike rentals in Boston, and the analysed mark is Trip Distance for August, we can assume that the weather is typically warm and humid. People might have rented bikes more often on overcast days to avoid the heat. It's also possible there were more overcast days in August. |
| Tableau Desktop version | Web version |
|
|
| Section | Description | Example |
|---|---|---|
Prediction The prediction reflects the goal of the use case. | The goal is to either maximise or minimise the outcome. For example, your goal can be to minimise shipping time or to maximise the average sales revenue per shipment. |
|
Top Predictors Conditions that most significantly affect the predicted outcome, in decreasing order of magnitude. | A condition is a data value associated with a field. A predictor consists of one or two conditions. If two conditions are shown, they are joined by and to represent the intersection of those conditions. Green (arrow up) indicates that the predictor improves the predicted outcome. Red (arrow down) indicates that the predictor worsens the predicted outcome. |
|
How To Improve This Suggested actions the user can take to improve the predicted outcome. | Improvements are associated with factors over which users can possibly control, such as the shipping method or a subscriber’s membership level. |
|
| Original data | Aggregation without roll-up | Aggregation with roll-up |
 |  |  |
| 31/10/2024 |
| 31/10/2024 |
10/12/2024 |
| 31/10/2024 |
| 31/10/2024 |
| 10/12/2024 |
| 31st October 2024 |
| 31st October 2024 |
| 12th October 2024 |
| Null |
| 31/10/2024 |
| 12/10/2024 |
| 31/10/2024 |
| 2024-10-31 |
10/12/2024 |
| 12/10/2024 |
| 31/10/2024 |
| Null |
| 10/12/2024 |
| 12/10/2024 |
| Fruit from data source A | Fruit from data source B | Fruit from data source C |
| Apples | Apples | Apples |
| Oranges | Grapefruit | Grapefruit |
| Bananas | Oranges | Oranges |
| Pears | Tomatoes | |
| Bananas |
| Fruit from data source A - Source field | Fruit from data source B - Target field | Fruit from data source C - Target field |
| Apples | Apples | Apples |
| Oranges | Oranges | Oranges |
| Bananas | Bananas |
| Field | Reason for inclusion |
| Life Expectancy Female and Life Expectancy Male | Where people are living longer, there are more likely to be people who are interested in traveling later in life. |
| Population Urban | It is easier to market services in areas with greater population density. |
| Population 65+ | The target population is older residents with the time and funds to travel. |
| TourismPerCapita | This is a measure that you must create as a named calculated field. The formula is:
Tourism Outbound aggregates the money (in US dollars) that residents of a country/region spend annually on international travel. But this total must be divided by the population of each country/region to determine the average amount each resident spends on international travel. |
| Name | Formula |
| First Purchase Date | {FIXED [Customer Name] : MIN([Order Date])} |
| Days Since First Purchase | DATETRUNC('day', [Order Date])-DATETRUNC('day', [First Purchase Date]) |
| This workbook theme... | Is associated with these Tableau versions... |
|---|---|
| Smooth | Version 10.x and newer |
| Clean | Versions 8.0.x – 9.3.x |
| Modern | Versions 3.5 – 7.0.x |
| Classic | Versions 1.0 – 3.2 |
| Geographic Role | Assign this role to a field if it contains: |
| Airport | International Air Transport Association (IATA) or International Civil Aviation Organisation (ICAO) airport codes. |
| Area Code (US) | US telephone area codes; numbers only. |
| CBSA/MSA (US) | US Core-Based Statistical Areas (CBSA), which includes Metropolitan Statistical Areas (MSA), as defined by the US Office of Management and Budget. CBSA/MSA Codes and Names are recognised. |
| City | Worldwide cities with population of 15,000 or more. Names are in English (UK or US), French, German, Spanish, Brazilian-Portuguese, Japanese, Korean and Chinese (Simplified and Traditional). |
| Congressional District (US) | US congressional districts. |
| Country/Region | Worldwide countries, regions, and territories. Names are in English (UK or US), French (Canada and France), German, Spanish, Brazilian-Portuguese, Japanese, Korean, Chinese (Simplified and Traditional), Swedish, Thai and Dutch. Tableau also recognises, FIPS 10, ISO 3166-1 alpha 2, and ISO 3166-1 alpha 3. Names are included in various forms, including long, short, and various abbreviations. |
| County | Second-level administrative divisions for select countries. For example, US counties, French départements, German kriese, etc. Note: Second-level administrative division definitions vary by country. In Tableau, all second-level administrative divisions are geocoded with the County geographic role. For more information, see the Location Data that Tableau Supports for Building Map Views section. |
| NUTS Europe | NUTS (Nomenclature of Territorial Units for Statistics) levels 1–3 codes. Codes and names, including synonyms, are supported. |
| Latitude | Latitude in decimal degrees. Only available for numeric fields. |
| Longitude | Longitude in decimal degrees. Only available for numeric fields. |
| State/Province | Worldwide state, province, and other first-level administrative divisions. Names are in English (UK or US), French, German, Spanish, Brazilian-Portuguese, Japanese, Korean and Chinese (Simplified and Traditional). Note: Some names are available only in their local form. |
| ZIP Code/Postcode | ZIP codes and postcodes for select countries. For example, US five-digit zip codes, Australian four-digit postcodes, German five-digit postcodes, etc. For more information, see the Location Data that Tableau Supports for Building Map Views section. |
| NUMBER FORMAT | FORMAT OPTIONS |
| Automatic: format is automatically selected based on either the format specified by the data source or the data contained in the field. | None. |
| Number (Standard): format is based on locale selected. | Locale: number format changes based on the geographical location selected. |
| Number (Custom): format is customised to your choice. | Decimal Places: the number of decimal places to display. Negative Values: how negative values are displayed. Units: the number is displayed using the specified units. For example, if the number is 20,000 and the units are thousands, the number will be displayed as 20K. Prefix/Suffix: characters that precede and follow each displayed number. Include thousands separators: whether the number shows separators every thousand (example: 100,000 vs. 100000). |
| Currency (Standard): format and currency symbol is based on locale selected. | Locale: currency format based on the geographical location selected. |
| Currency (Custom): format and currency symbol is customised to your choice. | Decimal Places: the number of decimal places to display. Negative Values: how negative values are displayed. Units: the number is displayed using the specified units. For example, if the number is 20,000 and the units are thousands, the number is displayed as 20K. Prefix/Suffix: characters that precede and follow each displayed number. Include thousands separators: whether the number shows separators every thousand (example: 100,000 vs. 100000). |
| Scientific: numbers are displayed in scientific notation. | Decimal: the number of decimal places to display. |
| Percentage: numbers are displayed as a percentage with the percent symbol. The value of 1 is interpreted as 100% and 0 as 0% | Decimal: the number of decimal places to display. |
| Custom: format is based entirely on what is specified in the format options. | Custom: type in the format you want to use, including special characters (optional). See "Define a custom number format" in this topic for details. |
| USE CASE | NUMBER CODE SYNTAX | EXAMPLE OUTPUT |
| Show only positive values | #,##; ; (note a blank space after the 2nd and 3rd semicolon) | Positive values: 1,234 Negative values: (only the blank space displays) Zero values: (only the blank space displays) |
| Show only negative values | ;-#,##; | Positive values: (nothing is displayed) Negative values: -1,234 Zero values: (nothing is displayed) |
| Show only zero values | ;;0; | Positive values: (nothing is displayed) Negative values: (nothing is displayed) Zero values: 0 |
| Hide zero values | #,###;-#,###;; | Positive values: 1,234 Negative values: -1,234 Zero values: (nothing is displayed) |
| Show negative values in brackets | #,###;(#,###);; | Positive values: 1,234 Negative values: (1,234) Zero values: (nothing is displayed) |
| Add a character prefix to a value | $#,###.##;-$#,###.##;$0; | Positive values: $1,234.56 Negative values: -$1,234.56 Zero values: $0 |
| Add a character suffix to a value | #%;-#%;0%; | Positive values: 12% Negative values: -34% Zero values: 0% |
| Add text descriptors | "$"#,#" Surplus";"$"-##" Shortage"; "$"0; | Positive values: $1,234 Surplus Negative values: $-1,234 Shortage Zero values: $0 |
| NUMBER FORMAT | FORMAT OPTIONS |
| Automatic: format is automatically selected based on either the format specified by the data source or the data contained in the field. | None. |
| Number (Custom): format is customised to your choice. | Decimal Places: the number of decimal places to display. Units: the number is displayed using the specified units. For example, if the number is 20,000 and the units are thousands, the number is displayed as 20K. Include separators: whether the number shows separators every thousand (example: 100,000 vs. 100000). |
| Currency (Custom): format and currency symbol is customised to your choice. | Decimal Places: the number of decimal places to display. Units: the number is displayed using the specified units. For example, if the number is 20,000 and the units are thousands, the number is displayed as 20K. Include separators: whether the number shows separators every thousand (example: 100,000 vs. 100000). |
| Percentage (Custom): numbers are displayed as a percentage with the percent symbol. The value of 1 is interpreted as 100% and 0 as 0% | Decimal Places: the number of decimal places to display. |
| Scientific (Custom): numbers are displayed in scientific notation. | Decimal Places: the number of decimal places to display. |
Use Explain Data | Author Workbooks and Control Access |
| Category | Product Name | Sales |
| Furniture | Floor Lamp | $96.00 |
| bq-fetch-tasks | Number of parallel background tasks to use when fetching data using HTTP. The default is 10. |
| bq-large-fetch-rows | Number of rows to fetch in each batch for spool queries. The default is 50000. |
| bq-fetch-rows | Number of rows to fetch in each batch for non-spool queries. The default is 10000. |
| bq-response-rows | Number of rows returned in non-spool non-batched queries. The default is 10000. |
| CAP_BIGQUERY_FORCE_SPOOL_JOB | Force all queries to use the temp table approach. The default value is “no.” Change the value to “yes” to turn on this attribute. |
| Includes Other | Does not include Other |
|---|---|
 |  |
| Highlight method | Benefits | When you might use this |
|---|---|---|
| Select marks |
|
|
| Legends |
|
|
| Highlighter |
|
|
| Actions (Tableau Desktop only) |
|
|
| Explanation type | Evaluation |
|---|---|
Extreme values | Extreme values are aggregated marks that are outliers, based on a model of the visualised marks. The selected mark is considered to contain an extreme value if a record value is in the tails of the distribution of the expected values for the data. An extreme value is determined by comparing the aggregate mark with and without the extreme value. If the mark becomes less surprising by removing a value, then it receives a higher score. When a mark has extreme values, it doesn't automatically mean it has outliers, or that you should exclude those records from the view. That choice is up to you depending on your analysis. The explanation is simply pointing out an interesting extreme value in the mark. For example, it could reveal a mistyped value in a record where a banana cost 10 pounds instead of 10 pence. Or, it could reveal that a particular sales person had a great quarter. |
Number of records | The number of records explanation models the aggregate sum in terms of the aggregate count; average value of records models it in terms of the aggregate average. The better the model explains the sum, the higher the score. This explanation describes whether the sum is interesting because the count is high or low, or because the average is high or low. |
Average value of the mark | This type of explanation is used for aggregate marks that are sums. It explains whether the mark is consistent with the other marks because in terms of its aggregate count or average, noting the relation SUM(X) = COUNT(X) * AVG(X). This explanation describes whether the sum is interesting because the count is high or low, or because the average is high or low. |
Contributing Dimensions | This explanation models the target measure of the analysed mark in terms of the breakdown among categories of the unvisualised dimension. The analysis balances the complexity of the model with how well the mark is explained. An unvisualised dimension is a dimension that exists in the data source but isn't currently being used in the view. This type of explanation is used for sums, counts and averages. The model for unvisualised dimensions is created by splitting out marks according to the categorical values of the explaining column, and then building a model with the value that includes all of the data points in the source visualisation. For each row, the model attempts to recover each of the individual components that made each mark. The analysis indicates whether the model predicts the mark better when components corresponding to the unvisualised dimension are modelled and then added up, versus using a model where the values of the unvisualised dimension are not known. Aggregate dimension explanations explore how well mark values can be explained without any conditioning. Then, the model conditions on values for each column that is a potential explanation. Conditioning on the distribution of an explanatory column should result in a better prediction. |
Contributing Measures | This explanation models the mark in terms of this unvisualised measure, aggregated to its mean across the visualised dimensions. An unvisualised measure is a measure that exists in the data source but isn't currently being used in the view. A Contributing Measures explanation can reveal a linear or quadratic relationship between the unvisualised measure and the target measure. |
| Syntax | MODEL_PERCENTILE(
|
| Definition | 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])) |
| Syntax | MODEL_QUANTILE(
|
| Definition | 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])) |
| year(Order%20Date) | Integer |
| quarter(Order%20Date) | Integer between 1 and 4 |
| month(Order%20Date) | Integer between 1 and 12 |
| day(Order%20Date) | Integer between 1 and 31 |
| hour(Order%20Date) | Integer 0–23 |
| minute(Order%20Date) | Integer 0-59 |
| second(Order%20Date) | Integer 0-59 |
| week(Order%20Date) | Integer 1-53 |
| my(Order%20Date) | Six-digit integer: YYYYMM |
| mdy(Order%20Date) | Eight-digit integer: YYYYMMDD |
SQL Server table
| Excel table  |
| requirement | description |
|---|---|
Salesforce licence | One of the following licences:
These licences are available for an extra cost. |
Salesforce user account | Account that is configured to access Einstein Discovery. If you use the Einstein Discovery in Tableau licence, your user account must have the View Einstein Discovery Recommendations Via Connect API system permission assigned to it. If you use either the Tableau CRM Plus licence or Einstein Predictions licence:
To configure user accounts, see Set Up Einstein Discovery in Salesforce help. |
Administrator settings | Salesforce administrators will need to:
|
| requirement | description |
|---|---|
Tableau licence and permissions | Authors who need to configure the Einstein Discovery dashboard extension will need a Creator or Explorer licence and permissions that allow them to edit and save workbooks. Creators, Explorers and Viewers will need to be signed in to the Salesforce org account to access predictions in the Einstein Discovery dashboard extension in Tableau. |
Tableau user account | In Tableau Cloud and Tableau Server, users can save Salesforce user account credentials along with their Tableau user account. |
Administrator settings | Tableau Server administrators will need to configure Tableau Server for OAuth (enables access to predictions from Tableau). For more information, see Configure Einstein Discovery Integration in Tableau Server help. To let users see predictions in published table calculations, Tableau Server administrators need to enable analytics extensions for the site. For more information, see Configure Connection with Analytics Extensions in Tableau Server help. For more information on Tableau Server configuration, see Configure Einstein Discovery Integration (Tableau Server). For more information on Tableau Cloud configuration, see Configure Einstein Discovery Integration (Tableau Cloud). |
Bill Bill Payment Credit Memo Deposit | Estimate Invoice Journal Entry Payment Purchase | Purchase Order Refund Receipt Sales Receipt Vendor Credit |
| Gregorian | ISO-8601 | Differences between calendars |
|---|---|---|
| Year | ISOYEAR | ISO-8601 years always start on the first Monday closest to 1 January. This means the year may start anywhere between 29 December and 4 January. Gregorian calendars always start the year on 1 January. This can cause some discrepancy in years between the two calendar systems around those dates. Each ISO-8601 year is either a long or a short year, with 52 or 53 weeks, depending on when the ISO-8601 year begins. |
| Quarter | ISOQUARTER | The first three quarters in the ISO-8601 always have 13 weeks. The last quarter has either 13 weeks (in a short year) or 14 weeks (in a long year). |
| Month | The ISO-8601 week-based calendar doesn’t use months. Many retail and financial systems divide ISO-8601 quarters into three segments of 4-4-5 weeks, though other "month" patterns also exist. These can be defined using calculations. See Create a 4-4-5 calendar. | |
| Week Number | ISOWEEK | All weeks in the ISO-8601 week-based calendar have exactly 7 days and start on a Monday. Each week belongs to single year, unlike the Gregorian calendar which permits weeks to extend across years. Long years have 53 weeks, short years have 52 weeks. |
| Day | The ISO-8601 week-based calendar doesn’t use numerical days (such as the 14th or 23rd). | |
| Weekday | ISOWEEKDAY | ISO-8601 weekdays always start on Monday and are represented as single digits. Monday is 1, Tuesday is 2, up to 7 for Sunday. |
| Join Type | Result |
Inner
| When you use an inner join to combine tables, the result is a table that contains values that have matches in both tables. When a value doesn't match across both tables, it is dropped entirely. |
Left
| When you use a left join to combine tables, the result is a table that contains all values from the left table and corresponding matches from the right table. When a value in the left table doesn't have a corresponding match in the right table, you see a null value in the data grid. |
Right
| When you use a right join to combine tables, the result is a table that contains all values from the right table and corresponding matches from the left table. When a value in the right table doesn't have a corresponding match in the left table, you see a null value in the data grid. |
Full outer
| When you use a full outer join to combine tables, the result is a table that contains all values from both tables. When a value from either table doesn't have a match with the other table, you see a null value in the data grid. |
| Union
| Though union is not a type of join, union is another method for combining two or more tables by appending rows of data from one table to another. Ideally, the tables that you union have the same number of fields, and those fields have matching names and data types. For more information about union, see Union Your Data. |
| For example, here's a snippet of a JSON file: | The JSON file generates these schema levels: |
 |  |
| What to do | Keystrokes |
|---|---|
| Move focus to previous | Up |
| Move focus to next | Down |
| (Single column) move focus to previous, (Multi-column) move focus to left | Left |
| (Single column) move focus to next, (Multi-column) move focus to right | Right |
| Move focus to first item | Home |
| Move focus to last item | End |
| Toggle item selection | Spacebar |
Toggle highlighting on and off Note: This is the keyboard equivalent of Highlight Selected Items. | Enter |
Clear all item selections Note: To view legend item text with more contrast, select individual legend items, and then switch highlighting on and off. | Esc |
| What to do | Keystrokes |
|---|---|
Dropdown list collapsed: Move focus to previous item and commit to value, Dropdown list open: Move focus to previous item and commit to value; doesn’t commit to value | Up |
Dropdown list collapsed: Move focus to next item and commit to value, Dropdown list open: Move focus to next item and commit to value; doesn’t commit to value | Down |
Dropdown list collapsed: Open or close domain list, Dropdown list open: Commit selection of focused item | Spacebar |
| Dropdown list open: Collapse domain list without making a selection | Esc |
| What to do | Keystrokes |
|---|---|
| Move focus to a visualisation (viz) | Within a dashboard or workbook, press Enter |
With a viz in focus, open the View Data window Note: The screen reader you’re using might require some combination of modifier keys (Shift, Ctrl, Alt, Cmd) in conjunction with Enter. See the documentation for your screen reader. | Shift+Enter |
| Move focus to any cell within the data grid | Arrow keys |
| Interact with cells in a grid | Use the arrow keys to navigate to the cell. Press Enter to focus on an element within a cell. Then interact with the element using keyboard navigation, such as Enter or Space. To return to navigation mode, press Esc. |
| Move a column | Within the data grid, use the arrow keys to move focus to a cell in the desired column. Press Enter, use the down arrow key to select Move Left or Move Right and then press Enter. |
| Sort by column | Within the data grid, use the arrow keys to move focus to a cell in the desired column. Press Enter, use the down arrow key to select Sort Ascending or Sort Descending and then press Enter. |
| Remove a column | Within the data grid, use the arrow keys to move focus to a cell in the desired column. Press Enter, use the down arrow key to select Remove, and then press Enter. |
| Move focus to another data table | Press Tab to move the focus to the Summary tab. Use the down arrow key to move the focus to the desired data table within the Tabs pane. |
| Edit number of rows | Press Tab to move the focus to the row count field. Type the desired row number, and then press Enter. |
| Show or hide aliases | Press Tab to move the focus to the Settings button. Press Enter to show aliases, and press Enter again to hide aliases. |
| Add or remove fields | Press Tab to move the focus to the Show Fields button. Press Enter to display a list of fields in the data source. Use the arrow keys to move the focus to each field name. Press Enter to remove any undesired fields from the data grid. To add fields back to the data grid, press Enter on the desired field to reselect it. |
| Download the data as it displays in the View Data window | Press Tab to move the focus to the Download button, and then press Enter. A CSV file containing your customised view of the data downloads in your browser. |
| Close the View Data window | Windows: ALT+F4 Mac OS: Cmd+W |
| What to do | Keystrokes |
|---|---|
| Move focus to a visualisation (viz) | Within a dashboard or workbook, press Enter |
| With a viz in focus, move to the left, top, right or bottom headers | Arrow keys |
| Navigate into a header | Enter |
Navigate within a header or nested header | Arrow keys |
| Toggle header highlighting on/off | Spacebar |
| Back out of a header | Esc |
| Description | Windows shortcut | Mac shortcut |
| New workbook | Ctrl+N | Command+N |
| New worksheet | Ctrl+M | Command+T |
| Describe sheet | Ctrl+E | Command+E |
| Cycle forward through open worksheets | Ctrl+Tab, Ctrl+F6 | Shift+Command+Right bracket |
| Cycle backward through open worksheets | Ctrl+Shift+Tab, Ctrl+Shift+F6 | Shift+Command+Left bracket |
| Switch in and out of Presentation Mode | F7 , Ctrl+H | Option+Return |
| Switch in and out of Full Screen mode | Control+Command+F | |
Open file
| Ctrl+O | Command+O |
| Save file | Ctrl+S | Command+S |
| Save to Tableau Public | Ctrl+Shift+S | Shift+Command+S |
| Revert workbook to last saved state | F12 | Option+Command+E |
| Close the current workbook | Alt+F4 | Command+W |
| Ctrl+P | Command+P | |
| Open Help | F1 | Control+Command+? |
| Description | Windows shortcut | Mac shortcut |
| New worksheet | Ctrl+Alt+T | Option+Command+T |
| Switch in and out of Full Screen mode | F11 | Control+Command+F |
| Save file | Ctrl+S | Command+S |
| Save workbook as | Ctrl+Shift+S | Shift+Command+S |
| Close the current workbook | Alt+F4 | Option+Q |
| Print (or export as PDF) | Ctrl+P | Command+P |
| Open Help | F1 | Control+Command+/ |
| Description | Windows shortcut | Mac shortcut |
| Connect to data source | Ctrl+D | Command+D |
| Activate the find command in the Data pane | Ctrl+F | Command+F |
| Refresh data source | F5 | Command+R |
| Run data updates on a view | F9 | Shift+Command+0 |
| Toggle automatic data updates on and off | F10 | Option+Command+0 |
| Description | Windows shortcut | Mac shortcut |
| Connect to data source | Ctrl+D | Command+D |
| Refresh data source | Alt+F5 | Option+F5 |
| Rename data source | Alt+F2 | Option+F2 |
| New data source | Ctrl+Alt+D | Control+D |
| Edit data source | Ctrl+Alt+Shift+D | Control+Shift+D |
| Description | Windows shortcut | Mac shortcut |
|---|---|---|
| Show Me! | Ctrl+1 , Ctrl+Shift+1 | Command+1 |
| Add the selected field to the sheet. (Only works with a single field.) | Enter or double-click | Return or double-click |
| Place selected field on Columns shelf | Alt+Shift+C | Option+Shift+C |
| Place selected field on Filters shelf | Alt+Shift+F | Option+Shift+F |
| Place selected field on Size | Alt+Shift+I | Option+Shift+I |
| Place selected field on Detail | Alt+Shift+L | Option+Shift+L |
| Place selected field on Colour | Alt+Shift+O | Option+Shift+O |
| Place selected field on Pages shelf | Alt+Shift+P | Option+Shift+P |
| Place selected field on Rows shelf | Alt+Shift+R | Option+Shift+R |
| Place selected field on Shape | Alt+Shift+S | Option+Shift+S |
| Place selected field on Text/Label | Alt+Shift+T | Option+Shift+T |
| Place selected field on Rows shelf | Alt+Shift+X | Option+Shift+X |
| Place selected field on Columns shelf | Alt+Shift+Y | Option+Shift+Y |
| Open the Drop Field menu | Right-click+drag to shelf | Option+drag to shelf |
| Open the View Data Model window | Ctrl+Shift+I | Command+Shift+I |
| Copy a field in the view and place it on another shelf or card | Ctrl+drag | Command+drag |
| Swap rows and columns | Ctrl+W | Control+Command+W |
| Flip orientation of column labels at bottom of view | Ctrl+L | |
| Toggle dashboard grid on and off | G | G |
| Toggle between Dashboard and Layout tabs | T | T |
| Cut text selection (in captions, titles, formulas, etc.) | Ctrl+X | Command+X |
| Paste clipboard | Ctrl+V | Command+V |
| Undo | Ctrl+Z | Command+Z |
| Redo | Ctrl+Y | Command+Shift+Z |
| Clear the current worksheet | Alt+Shift+Backspace | Option+Shift+Delete |
| Move floating dashboard object | Arrow key moves 1 pixel, Shift+Arrow moves 10 pixels | Arrow key moves 1 pixel, Shift+Arrow moves 10 pixels |
Resize floating dashboard object | Alt+Arrow key resizes in 1-pixel increments, Shift+Alt+Arrow resizes in 10-pixel increments | Option+Arrow key resizes in 1-pixel increments, Shift+Option+Arrow resizes in 10-pixel increments |
| Description | Windows shortcut | Mac shortcut |
|---|---|---|
| Add the selected field to the sheet. (Only works with a single field.) | Double-click | Double-click |
| Copy a field in the view and place it on another shelf or card | Ctrl+drag | Command+drag |
| Toggle dashboard grid on and off | G | G |
| Toggle between Dashboard and Layout tabs | T | T |
| Open the View Data Model window | Ctrl+Shift+I | Command+Shift+I |
| Cut text selection (in captions, titles, formulas, etc.) | Ctrl+X | Command+X |
| Paste clipboard | Ctrl+V | Command+V |
| Undo | Ctrl+Z | Command+Z |
| Redo | Ctrl+Y | Command+Shift+Z |
| Open current workbook in Tableau Desktop | Ctrl+O | Option+Command+O |
| Clear the current worksheet | Alt+Shift+Backspace | Option+Shift+Delete |
| Move floating dashboard object | Arrow key moves 1 pixel, Shift+arrow moves 10 pixels | Arrow key moves 1 pixel, Shift+arrow moves 10 pixels |
Resize floating dashboard object | Alt+Arrow key resizes in 1-pixel increments, Shift+Alt+Arrow resizes in 10-pixel increments | Option+Arrow key resizes in 1-pixel increments, Shift+Option+Arrow resizes in 10-pixel increments |
| Rename column field (when field is selected in the data schema pane) | F2 | F2 |
| Rename calculated field (when calculated field editor is open) | F2 | F2 |
| Smaller cell size | Ctrl+B | Command+B |
| Bigger cell size | Ctrl+Shift+B | Command+Shift+B |
| Make rows narrower | Ctrl+Left arrow | Control+Command+Left arrow |
| Make rows wider | Ctrl+Right arrow | Control+Command+Right arrow |
| Make columns shorter | Ctrl+Down arrow | Control+Command+Down arrow |
| Make columns taller | Ctrl+Up arrow | Control+Command+Up arrow |
| Description | Windows shortcut | Mac shortcut |
|---|---|---|
| Start or stop forward playback on the Pages shelf | F4 | F4 |
| Start or stop backward playback on the Pages shelf | Shift+F4 | Shift+F4 |
| Skip forward one page | Ctrl+Period | Command+Period |
| Skip backward one page | Ctrl+Comma | Command+Comma |
| Description | Windows shortcut | Mac shortcut |
| Select a mark | Click | Click |
| Select a group of marks | Drag | Drag |
| Add individual marks to the selection | Ctrl+click | Command+click |
| Add a group of marks to the selection | Ctrl+drag | Command+drag |
| Use Rectangular Selection tool | A | A |
| Use Lasso Selection Tool | D | D |
| Use Radial Selection Tool | S | S |
| Select all data | Ctrl+A | Command+A |
| Copy selected data | Ctrl+C | Command+C |
| Clear the mark selection | Esc | Esc |
| Pan around the view | Shift+drag | Shift+drag |
| Zoom in to a point in the view (if not map, requires zoom mode) | Double-click, Ctrl+Shift+click | Double-click, Shift+Command+click |
| Zoom out from a point on a map (if not map, requires zoom mode) | Ctrl+Shift+Alt+click | Shift+Option+Command+click |
| Zoom out | Shift+Double-click | Shift+Double+click |
| Zoom in to an area in the view (requires zoom mode if not map) | Ctrl+Shift+drag | Shift+Command+drag |
| Zoom in and out on a map | Scroll | Scroll |
| Drag a row and scroll through a long list simultaneously | Click+drag to bottom of pane+hold | Click+scroll, Command+hold |
| Description | Windows shortcut | Mac shortcut |
| Open file | Ctrl+O | Command+O |
| New flow | Ctrl+N | Command+N |
| Save file | Ctrl+S | Command+S |
| Save file as | Alt+Ctrl+S | Shift+Command+S |
| Quit | Ctrl+Q | Command+Q |
| Undo | Ctrl+Z | Command+Z |
| Redo | Ctrl+Y | Shift+Command+Z |
| Cut | Ctrl+X | Command+X |
| Copy | Ctrl+C | Command+C |
| Paste | Ctrl+V | Command+V |
| Select All | Ctrl+A | Command+A |
| Run All | Ctrl+R | Command+R |
| Publish flow | F10 |
| Normal Colour Legend | Colour Legend Highlighting Enabled | |
 |  |
| Syntax | <expr1> AND <expr2> |
| Definition | Performs a logical conjunction on two expressions. (If both sides are true, the logical test returns true.) |
| Output | Boolean (true or false) |
| Example | IF [Season] = "Spring" AND "[Season] = "Fall" “If both (Season = Spring) and (Season = Autumn) are true simultaneously, then return ‘It's the apocalypse and footwear doesn't matter’.” |
| Notes | Often used with IF and IIF. See also NOT and OR. If both expressions are If you create a calculation in which the result of an Note: The |
| Syntax | CASE <expression>
|
| Output | Depends on data type of the <then> values. |
| Definition | Evaluates the |
| Example | "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes | Used with WHEN, THEN, ELSE and END.
|
| Syntax | CASE <expression>
|
| Definition | An optional piece of an IF or CASE expression used to specify a default value to return if none of the tested expressions are true. |
| Example | IF [Season] = "Summer" THEN 'Sandals' CASE [Season] |
| Notes | Used with CASE, WHEN, IF, ELSEIF, THEN and END
|
| Syntax | [ELSEIF <test2> THEN <then2>] |
| Definition | An optional piece of an IF expression used to specify additional conditions beyond the initial IF. |
| Example | IF [Season] = "Summer" THEN 'Sandals' |
| Notes | Used with IF, THEN, ELSE and END
Unlike |
| Definition | Used to close an IF or CASE expression. |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes |
| Syntax | IF <test1> THEN <then1> |
| Output | Depends on data type of the <then> values. |
| Definition | Tests a series of expressions and returns the |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." |
| Notes |
| Syntax | IFNULL(expr1, expr2) |
| Output | Depends on the data type of the <expr> values. |
| Definition | Returns |
| Example | IFNULL([Assigned Room], "TBD") "If the Assigned Room field isn't null, return its value. If the Assigned room field is null, return TBD instead." |
| Notes | Compare with ISNULL. See also ZN. |
| Syntax | IIF(<test>, <then>, <else>, [<unknown>]) |
| Output | Depends on the data type of the values in the expression. |
| Definition | Checks whether a condition is met (<test>) and returns <then> if the test is true, <else> if the test is false and an optional value for <unknown> if the test is null. If the optional unknown isn't specified, IIF returns null. |
| Example | IIF([Season] = 'Summer', 'Sandals', 'Other footwear') "If Season = Summer, then return Sandals. If not, return Other footwear" IIF([Season] = 'Summer', 'Sandals', "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither are true, return Sneakers." IIF('Season' = 'Summer', 'Sandals', "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If none of the expressions are true, return Sneakers." |
| Notes |
That is to say, in the calculation below, the result will be Red, not Orange, because the expression stops being evaluated as soon as A=A is evaluated as true:
|
| Syntax | <expr1> IN <expr2> |
| Output | Boolean (true or false) |
| Definition | Returns TRUE if any value in <expr1> matches any value in <expr2>. |
| Example | SUM([Cost]) IN (1000, 15, 200) "Is the value of the Cost field 1000, 15 or 200?" [Field] IN [Set] "Is the value of the field present in the set?" |
| Notes | The values in See also WHEN. |
| Syntax | ISDATE(string) |
| Output | Boolean (true or false) |
| Definition | Returns true if a <string> is a valid date. The input expression must be a string (text) field. |
| Example | ISDATE("2018-09-22")"Is the string 2018-09-22 a properly formatted date?" |
| Notes | What is considered a valid date depends on the locale of the system evaluating the calculation. For example: In the USA:
In the UK:
|
| Syntax | ISNULL(expression) |
| Output | Boolean (true or false) |
| Definition | Returns true if the |
| Example | ISNULL([Assigned Room]) "Is the Assigned Room field null?" |
| Notes | Compare with IFNULL. See also ZN. |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | NOT <expression> |
| Output | Boolean (true or false) |
| Definition | Performs logical negation on an expression. |
| Example | IF NOT [Season] = "Summer" "If Season doesn't equal Summer, then return Don't wear sandals. If not, return Wear sandals." |
| Notes |
| Syntax | <expr1> OR <expr2> |
| Output | Boolean (true or false) |
| Definition | Performs a logical disjunction on two expressions. |
| Example | IF [Season] = "Spring" OR [Season] = "Fall" "If either (Season = Spring) or (Season = Fall) is true, then return Sneakers." |
| Notes | Often used with IF and IIF. See also AND and NOT. If either expression is If you create a calculation that displays the result of an Note: The |
| Syntax | IF <test1> THEN <then1>
|
| Definition | A required part of an IF, ELSEIF or CASE expression, used to define what result to return if a specific value or test is true. |
| Example | IF [Season] = "Summer" THEN 'Sandals' "If Season = Summer, then return Sandals. If not, look at the next expression. If Season = Winter, then return Boots. If neither of the expressions are true, return Sneakers." CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes |
| Syntax | CASE <expression>
|
| Definition | A required part of a CASE expression. Finds the first <value> that matches <expression> and returns the corresponding <then>. |
| Example | CASE [Season] "Look at the Season field. If the value is Summer, then return Sandals. If the value is Winter, then return Boots. If none of the options in the calculation match what is in the Season field, return Sneakers." |
| Notes | Used with CASE, THEN, ELSE and END.
CASE <expression> The values that |
| Syntax | ZN(expression) |
| Output | Depends on the data type of the <expression>, or 0. |
| Definition | Returns <expression> if it isn't null; otherwise returns zero. |
| Example | ZN([Test Grade]) "If the test grade isn't null, return its value. If the test grade is null, return 0." |
| Notes |
See also ISNULL. |
| CASE | IF | IIF |
CASE [Region] | IF [Region] = 'West' THEN 1 | IIF([Region] = 'West', 1, |
The CASE structure is very simple and easy to write and understand. However, the expression (here, [Region]) cannot be a logical operation, unlike with IF or IIF. Nulls are handled the same for CASE as they are for IF. | The IF THEN structure permits multiple ELSEIF clauses, which makes multiple evaluations much easier than with IIF. Null handling: any unknown (null) results are handled by the same ELSE clause as false results. Here, any region other than the four specified (including null) will be assigned a value of 5. | The IIF structure handles unknown results differently than false results and has a different syntax from IF. The trade-off for specific null handling is nesting, as above, which can be clumsy to write and understand. Null handling: any non-null region other than the four specified will be assigned a value of 5, but a null value will be assigned a 0. |
| Type of content | Consequence |
|---|---|
| Workbooks, metrics, flows and data roles | The content is permanently deleted. You can't undo this action. |
| Views | The view is removed from the site; however, it is still accessible if you edit or download the workbook. The effect is the same as if the view had been hidden upon publishing. For more information, see Show or hide sheets. |
| Projects | The project, and any Tableau content inside the project, is permanently deleted. External assets are moved to the External Assets Default Project. (In Tableau Server 2022.3 and earlier, external assets are irrelevant since they can't be in a folder to begin with.) |
| Collections | The collection is permanently deleted, but the items added to the collection are not deleted. |
| Built-In Hierarchy | Columns to include in the .csv file (in order; left to right) |
|---|---|
| Country (Name) | Country (Name) Latitude Longitude |
| Country (Name), State/Province | Country (Name) State/Province Latitude Longitude |
| Country (Name), State/Province, City | Country (Name) State/Province City Latitude Longitude |
| Country (Name), State/Province, County | Country (Name) State/Province County Latitude Longitude |
| Country (Name), ZIP Code/Postcode | Country (Name) ZIP Code/Postcode Latitude Longitude |
| Country (Name), Area Code | Country (Name) Area Code Latitude Longitude |
| Country (Name), CBSA | Country (Name) CBSA Latitude Longitude |
| Columns shelf: | Longitude (continuous dimension, longitude geographic role assigned) |
| Rows shelf: | Latitude (continuous dimension, latitude geographic role assigned) |
| Detail: | One or more fields with many underlying data points |
| Mark type: | Density |
| Number of records | Time to retrieve |
|---|---|
1,000 | 4.5 seconds |
10,000 | 45 seconds |
100,000 | 8 minutes |
1,000,000 | 75 minutes |
| Syntax | ABS(number) |
| Output | Number (positive) |
| Definition | Returns the absolute value of the given <number>. |
| Example | ABS(-7) = 7 The second example returns the absolute value for all the numbers contained in the Budget Variance field. |
| Notes | See also SIGN. |
| Syntax | ACOS(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arccosine (angle) of the given <number>. |
| Example | ACOS(-1) = 3.14159265358979 |
| Notes | The inverse function, COS, takes the angle in radians as the argument and returns the cosine. |
| Syntax | ASIN(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arcsine (angle) of a given <number>. |
| Example | ASIN(1) = 1.5707963267949 |
| Notes | The inverse function, SIN, takes the angle in radians as the argument and returns the sine. |
| Syntax | ATAN(number) |
| Output | Number (angle in radians) |
| Definition | Returns the arctangent (angle) of a given <number>. |
| Example | ATAN(180) = 1.5652408283942 |
| Notes | The inverse function, |
| Syntax | ATAN2(y number, x number) |
| Output | Number (angle in radians) |
| Definition | Returns the arctangent (angle) between two numbers (x and y). The result is in radians. |
| Example | ATAN2(2, 1) = 1.10714871779409 |
| Notes | See also ATAN, TAN and COT. |
| Syntax | CEILING(number) |
| Output | Integer |
| Definition | Rounds a <number> to the nearest integer of equal or greater value. |
| Example | CEILING(2.1) = 3 |
| Notes | See also FLOOR and ROUND. |
| Database limitations |
|
| Syntax | COS(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the cosine of an angle. |
| Example | COS(PI( ) /4) = 0.707106781186548 |
| Notes | The inverse function, See also |
| Syntax | COT(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the cotangent of an angle. |
| Example | COT(PI( ) /4) = 1 |
| Notes | See also ATAN, TAN and PI. To convert an angle from degrees to radians, use RADIANS. |
| Syntax | DEGREES(number)The number argument is the angle in radians. |
| Output | Number (degrees) |
| Definition | Converts an angle in radians to degrees. |
| Example | DEGREES(PI( )/4) = 45.0 |
| Notes | The inverse function, See also |
| Syntax | DIV(integer1, integer2) |
| Output | Integer |
| Definition | Returns the integer part of a division operation, in which <integer1> is divided by <integer2>. |
| Example | DIV(11,2) = 5 |
| Syntax | EXP(number) |
| Output | Number |
| Definition | Returns e raised to the power of the given <number>. |
| Example | EXP(2) = 7.389 |
| Notes | See also LN. |
| Syntax | FLOOR(number) |
| Output | Integer |
| Definition | Rounds a number to the nearest <number> of equal or lesser value. |
| Example | FLOOR(7.9) = 7 |
| Notes | See also CEILING and ROUND. |
| Database limitations |
|
| Syntax | HEXBINX(number, number) |
| Output | Number |
| Definition | 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. |
| Example | HEXBINX([Longitude]*2.5, [Latitude]*2.5) |
| Notes | 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. |
| Syntax | HEXBINY(number, number) |
| Output | Number |
| Definition | 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]*2.5, [Latitude]*2.5) |
| Notes | See also HEXBINX. |
| Syntax | LN(number) |
| Output | Number The output is |
| Definition | Returns the natural logarithm of a <number>. |
| Example | LN(50) = 3.912023005 |
| Notes | See also EXP and LOG. |
| Syntax | LOG(number, [base])If the optional base argument isn't present, base 10 is used. |
| Output | Number |
| Definition | Returns the logarithm of a number for the given base. |
| Example | LOG(16,4) = 2 |
| Notes | See also POWER LN. |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | PI() |
| Output | Number |
| Definition | Returns the numeric constant pi: 3.14159... |
| Example | PI() = 3.14159 |
| Notes | Useful for trig functions that take their input in radians. See also RADIANS. |
| Syntax | POWER(number, power) |
| Output | Number |
| Definition | Raises the <number> to the specified <power>. |
| Example | POWER(5,3) = 125 |
| Notes | You can also use the ^ symbol, such as 5^3 = POWER(5,3) = 125 |
| Syntax | RADIANS(number) |
| Output | Number (angle in radians) |
| Definition | Converts the given <number> from degrees to radians. |
| Example | RADIANS(180) = 3.14159 |
| Notes | The inverse function, DEGREES, takes an angle in radians and returns the angle in degrees. |
| Syntax | ROUND(number, [decimals]) |
| Output | Number |
| Definition | Rounds The optional |
| Example | ROUND(1/3, 2) = 0.33 |
| Notes | Some databases, such as SQL Server, allow specification of a negative length, where -1 rounds number to 10s, -2 rounds to 100s and so on. This is not true of all databases. For example, it is not true of Excel or Access.
|
| Syntax | SIGN(number) |
| Output | -1, 0 or 1 |
| Definition | 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 | SIGN(AVG(Profit)) = -1 |
| Notes | See also ABS. |
| Syntax | SIN(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the sine of an angle. |
| Example | SIN(0) = 1.0 |
| Notes | The inverse function, See also |
| Syntax | SQRT(number) |
| Output | Number |
| Definition | Returns the square root of a <number>. |
| Example | SQRT(25) = 5 |
| Notes | See also SQUARE. |
| Syntax | SQUARE(number) |
| Output | Number |
| Definition | Returns the square of a <number>. |
| Example | SQUARE(5) = 25 |
| Notes | See also SQRT and POWER. |
| Syntax | TAN(number)The number argument is the angle in radians. |
| Output | Number |
| Definition | Returns the tangent of an angle. |
| Example | TAN(PI ( )/4) = 1.0 |
| Notes | See also ATAN, ATAN2, COT and PI. To convert an angle from degrees to radians, use RADIANS. |
| Syntax | ZN(expression) |
| Output | Any, or o |
| Definition | Returns the Use this function to replace null values with zeros. |
| Example | ZN(Grade) = 0 |
| Notes | This is a very useful function when using fields that may contain nulls in a calculation. Wrapping the field with ZN can prevent errors caused by calculating with nulls. |
| SQL_ODBC_INTERFACE_CONFORMANCE | Currently unused. |
| SQL_SQL_CONFORMANCE | Integer bitmask. Defines the level which the data source conforms to the SQL standard: '1' for entry-level SQL-92 conformance, '2' for FIPS 127-2 transitional, '4' for Intermediate and '8' for Full conformance. |
| SQL_CATALOGUE_USAGE | Integer bitmask. Defines the SQL statements in which a catalogue identifier can be used. |
| SQL_SCHEMA_USAGE | Integer bitmask. Defines the SQL statements in which a schema identifier can be used. |
| SQL_AGGREGATE_FUNCTIONS | Integer bitmask. Defines which standard SQL aggregation forms are supported. |
| SQL_NUMERIC_FUNCTIONS | Integer bitmask. Defines which SQL scalar numeric functions are supported. |
| SQL_STRING_FUNCTIONS | Integer bitmask. Defines which SQL scalar string functions are supported. |
| SQL_TIMEDATE_FUNCTIONS | Integer bitmask. Defines which SQL scalar date / time functions are supported. |
| SQL_TIMEDATE_ADD_INTERVALS | Integer bitmask. Defines which date / time intervals are supported with the TIMESTAMPADD scalar function. |
| SQL_TIMEDATE_DIFF_INTERVALS | Integer bitmask. Defines which date / time intervals are supported with the TIMESTAMPDIFF scalar function. |
| SQL_DATETIME_LITERALS | Integer bitmask. Defines which SQL-92 literals are supported for representing DATE / TIME constants and INTERVALs. |
| SQL_SYSTEM_FUNCTIONS | Integer bitmask. Defines support for special SQL system scalar functions: IFNULL, DBNAME and USERNAME. |
| SQL_SQL92_VALUE_EXPRESSIONS | Integer bitmask. Defines which logical functions are supported for testing and manipulating values: CASE, CAST and NULLIF. |
| SQL_SQL92_NUMERIC_VALUE_FUNCTIONS | Integer bitmask. Defines which functions can produce a numeric value from non-numeric data, including: EXTRACT (for date / time part extraction), CHAR_LENGTH, CHARACTER_LENGTH and POSITION(.. IN ..). |
| SQL_SQL92_STRING_FUNCTIONS | Integer bitmask. Defines which string manipulation functions are supported. |
| SQL_SQL92_DATETIME_FUNCTIONS | Integer bitmask. Defines which date / time manipulation functions are supported for determining the current date, time or timestamp. |
| SQL_OJ_CAPABILITIES | Integer bitmask. Defines which type of outer joins are supported. |
| SQL_SQL92_RELATIONAL_JOIN_OPERATORS | Integer bitmask. Defines which types of JOIN operators are supported, e.g. INNER, OUTER. |
| SQL_SQL92_PREDICATES | Integer bitmask. Defines which predicates are supported for logical tests of values, e.g. IS NULL, LIKE, IN. |
| SQL_CONVERT_FUNCTIONS | Integer bitmask. Defines which ODBC scalar functions are supported for CASTing or CONVERTing one data type to another. |
| SQL_CONVERT_TINYINT | Integer bitmask. Determines which other data types that this named type can be converted to using the ODBC scalar function CONVERT. |
| SQL_CONVERT_SMALLINT | Integer bitmask. Same as above. |
| SQL_CONVERT_INTEGER | Integer bitmask. Same as above. |
| SQL_CONVERT_BIGINT | Integer bitmask. Same as above. |
| SQL_CONVERT_REAL | Integer bitmask. Same as above. |
| SQL_CONVERT_FLOAT | Integer bitmask. Same as above. |
| SQL_CONVERT_DOUBLE | Integer bitmask. Same as above. |
| SQL_CONVERT_CHAR | Integer bitmask. Same as above. |
| SQL_CONVERT_VARCHAR | Integer bitmask. Same as above. |
| SQL_CONVERT_LONGVARCHAR | Integer bitmask. Same as above. |
| SQL_CONVERT_DECIMAL | Integer bitmask. Same as above. |
| SQL_CONVERT_NUMERIC | Integer bitmask. Same as above. |
| SQL_CONVERT_BIT | Integer bitmask. Same as above. |
| SQL_CONVERT_GUID | Integer bitmask. Same as above. |
| SQL_CONVERT_BINARY | Integer bitmask. Same as above. |
| SQL_CONVERT_VARBINARY | Integer bitmask. Same as above. |
| SQL_CONVERT_LONGVARBINARY | Integer bitmask. Same as above. |
| SQL_CONVERT_DATE | Integer bitmask. Same as above. |
| SQL_CONVERT_TIME | Integer bitmask. Same as above. |
| SQL_CONVERT_TIMESTAMP | Integer bitmask. Same as above. |
| SQL_CONVERT_INTERVAL_DAY_TIME | Integer bitmask. Same as above. |
| SQL_CURSOR_COMMIT_BEHAVIOR | Short integer value. “0” if the prepared statements are closed upon commit for the data source. |
| SQL_MAX_IDENTIFIER_LEN | Integer value. Defines the maximum number of characters that can be used in an identifier. Tableau leaves room for one extra character as the string terminator. |
| SQL_TXN_CAPABLE | Short integer value. “0” if the data source does not support the transaction. |
| SQL_QUOTED_IDENTIFIER_CASE | Integer bitmask. |
| SQL_COLUMN_ALIAS | Boolean value. "Y" if the data source supports using aliases for columns listed in the SELECT clause. |
| SQL_IDENTIFIER_QUOTE_CHAR | String value. Indicates the character which can be used for quoting identifiers. Because the connection customisation is an XML document, any entities must properly be encoded. For example, double-quotes will be '"'. Additionally this character is assumed to work as the opening and closing character around identifiers, so some data sources which require '[ ]' to enclose identifiers will not be supported. |
| SQL_CATALOGUE_NAME_SEPARATOR | Character value. Indicates the separator character to use between identifiers when qualifying them with a catalogue, schema or table name. This is typically the period character. |
| SQL_SPECIAL_CHARACTERS | String value. Indicates the special characters which are allowed in identifier strings. |
| SQL_CATALOGUE_TERM | String value. This is the descriptive term for a database catalogue, which appears in the Tableau connection dialog for this ODBC data source. |
| SQL_SCHEMA_TERM | String value. This is the descriptive term for a database schema, which appears in the Tableau connection dialog for this ODBC data source. |
| SQL_TABLE_TERM | String value. This is the descriptive term for a database table, which appears in the Tableau connection dialog for this ODBC data source. |
| SQL_DRIVER_NAME | String value. This is the name of the database ODBC driver. |
| SQL_DRIVER_VER | String value. This is the version number of the ODBC driver. |
| SQL_DRIVER_ODBC_VER | String value. This is the version of the ODBC API which the driver supports. |
| SQL_ODBC_VER | String value. This is the version of ODBC which the Windows ODBC Driver Manager supports. This should not need to be customised. |
| SQL_DBMS_NAME | String value. This is the name of the database vendor. |
| SQL_DBMS_VER | String value. This is the version of the database system. |
| SQL_SERVER_NAME | String value. This is the named network address of the database server. |
| SQL_USER_NAME | String value. This is the name of the currently authenticated user. |
| Number of records | Time to retrieve |
|---|---|
50,662 records | 3 minutes 17 seconds |
95,214 rows | 6 minutes 14 seconds |
194,679 rows | 12 minutes 55 seconds |
Includes Shared Members The diet drinks are listed in both the Diet Drinks hierarchy and their respective drink hierarchies. | Does Not Include Shared Members The diet drinks are only listed once, in their respective drink hierarchies. |
 | |
| Tableau Desktop | Tableau Prep Builder |
 |  |
| Data Source | Support |
| Actian Vectorwise | Not supported. |
| Amazon EMR Hadoop Hive | Supported for Hive 0.13 and later. |
| Amazon Redshift | Supported. |
| Aster Database | Supported for version 4.5 and later. |
| Cloudera Hadoop | Supported for Hive 0.13 and later. |
| Cloudera Impala | Supported for Impala 1.2.2 and later. |
| Cubes (multidimensional data sources) | Not supported. |
| DataStax Enterprise | Not supported. |
| EXASOL | Supported. |
| Firebird | Supported for version 2.0 and later. |
| Generic ODBC | Limited. Depends on the specific data source. |
| Google Big Query | Supported for standard SQL, not supported for legacy SQL. |
| Hortonworks Hadoop Hive | Supported for Hive 0.13 and later. On version 1.1 of HIVE level of detail expressions that produce cross joins are not reliable. Cross join occur when there is no explicit field to join on. For example, for a level of detail expression |
| IBM BigInsights | Supported. |
| IBM DB2 | Supported for version 8.1 and later. |
| MarkLogic | Supported for version 7.0 and later. |
| Microsoft Access | Not supported. |
| Microsoft Jet-based connections (legacy connectors for Microsoft Excel, Microsoft Access, and text) | Not supported. |
| Microsoft SQL Server | SQL Server 2005 and later. |
| MySQL | Supported. |
| IBM PDA (Netezza) | Supported version 7.0 and later. |
| Oracle | Supported version 9i and later. |
| Actian Matrix (ParAccel) | Supported version 3.1 and later. |
| Pivotal Greenplum | Supported for version 3.1 and later. |
| PostgreSQL | Supported version 7 and later. |
| Progress OpenEdge | Supported. |
| SAP HANA | Supported. |
| SAP Sybase ASE | Supported. |
| SAP Sybase IQ | Supported version 15.1 and later. |
| Spark SQL | Supported. |
| Splunk | Not supported. |
| Tableau Data Extract | Supported. |
| Teradata | Supported. |
| Vertica | Supported for version 6.1 and later. |
| Tableau Desktop version | Web version |
|
|
| Tableau Desktop version | Web version |
|
|
| If you are using Einstein Discovery, select Enable. Your default browser will open, allowing you to authorise the connection to Salesforce. After connecting, go to the Einstein Discovery section of this help topic to continue. | For all other services (Tabpy, Matlab and Rserve), the following dialog will appear. |
 |  |
| Optional Parameters | Syntax | Description |
|---|---|---|
| maxMiddleValues | "maxMiddleValues": integer | Specifies the number of top predictors to return in the response. Set to an integer number. Can only be used with Regression and Binary Classification Models. |
| maxPrescriptions | "maxPrescriptions": integer | Specifies the maximum number of improvements to return in the response. Set to an integer number. Can only be used with Regression and Binary Classification Models. |
| showMultiClassProbabilities | "showMultiClassProbabilities": boolean | Choose whether to show the probabilities for a Multi-class Classification Model. Set to true or false. Can be only be used with Multi-class Classification Models. |
| Syntax | RAWSQL_BOOL("sql_expr", [arg1], …[argN]) |
| Output | Boolean |
| Definition | Returns a Boolean result from a given SQL expression. |
| Example | RAWSQL_BOOL("%1 > %2", [Sales], [Profit])In the example, %1 is equal to [Sales] and %2 is equal to [Profit]. |
| Syntax | RAWSQLAGG_BOOL("sql_expr", [arg1], …[argN]) |
| Output | Boolean |
| Definition | Returns a Boolean result from a given aggregate SQL expression. |
| Example | RAWSQLAGG_BOOL("SUM( %1) >SUM( %2)", [Sales], [Profit]) In the example, %1 is equal to [Sales] and %2 is equal to [Profit]. |
| Syntax | RAWSQL_DATE("sql_expr", [arg1], …[argN]) |
| Output | Date |
| Definition | Returns a date result from a given SQL expression. |
| Example | RAWSQL_DATE("%1", [Order Date])In this example, %1 is equal to [Order Date]. |
| Syntax | RAWSQLAGG_DATE("sql_expr", [arg1], …[argN]) |
| Output | Date |
| Definition | Returns a date result from a given aggregate SQL expression |
| Example | RAWSQLAGG_DATE("MAX(%1)", [Order Date])In this example, %1 is equal to [Order Date]. |
| Syntax | RAWSQL_DATETIME("sql_expr", [arg1], …[argN]) |
| Output | Datetime |
| Definition | Returns a datetime result from a given SQL expression. |
| Example | RAWSQL_DATETIME("%1", [Order Date])In this example, %1 is equal to [Order Date]. |
| Syntax | RAWSQLAGG_DATETIME("sql_expr", [arg1], …[argN]) |
| Output | Datetime |
| Definition | Returns a datetime result from a given aggregate SQL expression. |
| Example | RAWSQLAGG_DATETIME("MIN(%1)", [Order Date])In this example, %1 is equal to [Order Date]. |
| Syntax | RAWSQL_INT("sql_expr", [arg1], …[argN]) |
| Output | Integer |
| Definition | Returns an integer result from a given SQL expression. |
| Example | RAWSQL_INT("500 + %1", [Sales])In this example, %1 is equal to [Sales]. |
| Syntax | RAWSQLAGG_INT("sql_expr", [arg1,] …[argN]) |
| Output | Integer |
| Definition | Returns an integer result from a given aggregate SQL expression. |
| Example | RAWSQLAGG_INT("500 + SUM(%1)", [Sales])In this example, %1 is equal to [Sales]. |
| Syntax | RAWSQL_REAL("sql_expr", [arg1], …[argN]) |
| Output | Numeric |
| Definition | Returns a numeric result from a given SQL expression. |
| Example | RAWSQL_REAL("-123.98 * %1", [Sales])In this example, %1 is equal to [Sales] |
| Syntax | RAWSQLAGG_REAL("sql_expr", [arg1,] …[argN]) |
| Output | Numeric |
| Definition | Returns a numeric result from a given aggregate SQL expression. |
| Example | RAWSQLAGG_REAL("SUM( %1)", [Sales])In this example, %1 is equal to [Sales]. |
| Syntax | RAWSQL_SPATIAL("sql_expr", [arg1], …[argN]) |
| Output | Spatial |
| Definition | Returns a spatial result from a given SQL expression. |
| Example | RAWSQL_SPATIAL("%1", [Geometry])In this example, %1 is equal to [Geometry]. |
| Note | There is no RAWSQLAGG version of this function. |
| Syntax | RAWSQL_STR("sql_expr", [arg1], …[argN]) |
| Output | String |
| Definition | Returns a string from a given SQL expression. |
| Example | RAWSQL_STR("%1", [Customer Name])In this example, %1 is equal to [Customer Name]. |
| Syntax | RAWSQLAGG_STR("sql_expr", [arg1,] …[argN]) |
| Output | String |
| Definition | Returns a string from a given aggregate SQL expression. |
| Example | RAWSQLAGG_STR("AVG(%1)", [Discount])In this example, %1 is equal to [Discount]. |
 |  |  |
| Runner | Action | Time |
|---|---|---|
| Amanda | Start | 3/9/2016 15:04 |
| Oscar | Start | 3/9/2016 15:04 |
| William | Start | 3/9/2016 15:04 |
| Amanda | End | 3/9/2016 15:25 |
| Oscar | End | 3/9/2016 15:21 |
| William | End | 3/9/2016 15:16 |
| Single database | Multiple databases |
|
|
| Relationships | Establish the potential for joins between two tables based on related fields. Doesn’t merge data together to create a new, fixed table. During analysis, queries the relevant tables automatically using the contextually-appropriate joins to generate a custom table of data for that analysis. Maintains the appropriate level of detail, doesn’t lose data, keeps appropriate aggregations and handles nulls. Can be used across multiple published data sources. |
| Joins | Merge two tables of data based on a join clause and join type to form a new, fixed table of data. Often used to add new columns of data across the same basic row structure. May cause data loss with some join types if fields aren’t present in all tables. May cause data duplication if tables are at different levels of detail. |
| Unions | Merge two or more tables of data to form a new, fixed table of data. Used to append (add new rows of) data across the same basic column structure. |
| Blends | Data remains separate. Tableau queries the data sources independently and visualises the results together in the view, based on the linking fields established for that sheet. Mimics the behaviour of a left join and may filter data from secondary data sources. |
| Syntax | MODEL_PERCENTILE(
|
| Definition | 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])) |
| Syntax | MODEL_QUANTILE(
|
| Definition | 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])) |
| Before | After |
|---|---|
 |  |
| Tableau Desktop version | Web version |
|
|
| Tableau Desktop version | Web version |
|
|
| Augmentation | Lambda | |
| Ridge regression | Yes | Yes |
| Linear regression | Yes | Not applicable |
| Relate | Use when combining data from different levels of detail.
|
| Join | Use when you want to add more columns of data across the same row structure.
|
| Union | Use when you want to add more rows of data with the same column structure.
|
| Blend | Use when combining data from different levels of detail.
|
 | Show Filmstrip – shows the sheets as thumbnails at the bottom of the workspace. |
 | Show Tabs – shows the sheet tabs at the bottom of the workspace. |
 | Previous/Next Sheet – advances forward or backward through the sheets in a workbook. |
 | Enter/Exit Full Screen – switches between expanding the workbook to fill the entire screen and showing it in a window. |
 | Exit Presentation Mode – returns the workbook to showing the entire workspace including the menus, toolbar and the Data pane. |
| Explain Data can't be run in views that use: |
|
Explain Data can't be run if you select: |
|
| Explain Data can't be run when the measure to be used for an explanation: |
|
Explain Data can't offer explanations for a dimension when it is: |
|
| Square Cell | Text Cell |
 |  |
| Error message | Suggestion for Resolution |
| A continuous date cannot be derived from the date fields in the view. | Forecasting requires a date field that can be interpreted continuously. If the date field is not explicitly continuous, then one of the included date levels must be Year. This error is returned if there are no dates in the view, or if the dates in the view don’t constitute a full hierarchy (for example, the date includes Year and Day, but not Month), or if they constitute a hierarchy that is not supported (for example, Year, Week, Day). |
| The time series is too short to forecast. | Expand the time series in your view to include more date values. This error is returned if there are fewer than four data points after trimming off unreliable or partial trailing periods which could mislead the forecast. |
| A forecast cannot be computed for a time series with Null date values. | Eliminate any Null values from the date field or fields in the view, either by filtering the date field or by using a less detailed date granularity (for example, by switching from months to quarters). |
| A forecast cannot be computed when the view contains multiple distinct date fields. | This error is returned if there are multiple date fields in the view. For example, if both Order Date and Ship Date are in the same view, forecasting is not supported. |
| The selected 'Aggregate by' value in Forecast Options is not compatible with the visualisation. | The date in the view must be compatible with the value of Aggregate by in the Forecast Options dialog box. For example, if Aggregate by is set to Weeks and the date in the view is set to Months, this error occurs. Change one of the dates so that the two are compatible, or set Aggregate by to Automatic. |
| A forecast cannot be computed because there are too many missing values. | This error is returned if more than 40% of the data in a pane is missing. Selecting Fill in missing values with zeros in the Forecast Options dialog box will not resolve this error. Aggregate your data to a higher level of detail by removing dimensions or changing the date level, for example from 'weeks' to 'months'. Otherwise, you must modify the source data or use data from a different source. |
| There is no measure to forecast. | This error is returned if no measure that can be forecast is present in the view. Forecast measures must be on the Rows or Columns shelf, or on the Marks card. |
| The measure to forecast must be a number. | Some measures cannot be interpreted numerically and therefore cannot be forecast. |
| A forecast cannot be computed for a dimension. | The value to be forecast must be a measure, and not a dimension. |
| There is too much data to compute a forecast. | Forecasting is not possible when the result set from the query is too large. The limit is about 10,000 rows. To fix the forecast, aggregate the time series value at a higher level (for example, Month instead of Week) or filter the data. |
| A forecast cannot be computed because the data is divided into too many rows, columns, or colours. | Simplify the view to resolve the error by filtering or removing some of the dimensions. |
| A forecast cannot be computed because the view contains table calculations. | Create a version of the view that does not contain table calculations. |
| A forecast cannot be computed because there is a measure on the Filters shelf. | Remove the measure from the Filters shelf. |
| A forecast cannot be computed because Aggregate Measures is not selected. | Aggregate Measures is an option on the Analysis menu. See Data Aggregation in Tableau and How to Disaggregate Data. |
| A forecast cannot be computed because the view contains percent calculations. | Percentage of is an option on the Analysis menu. See Calculate Percentages in Tableau. |
| A forecast cannot be computed because Grand Totals or Subtotals is enabled. | These options are controlled from the Totals command in the Analysis menu. See Show Totals in a Visualisation. |
| A multiplicative model cannot be computed because the measure to be forecast has one or more values that are less than or equal to zero. | You have created a custom model with Trend or Seasonality set to Multiplicative. Change this value, or set the Forecast Model to Automatic. |
| A model with multiplicative trend and additive season is not allowed because it is numerically unstable. | You have created a custom model configured as described in the error message. Change the settings for the custom model, or set the Forecast Model to Automatic. |
| A seasonal model cannot be computed because the time series is too short. | Expand the time series in your view to include more date values. |
| The selected multiplicative model cannot be computed because some of the data is too close to zero relative to the rest of the data. | You have created a custom model configured as described in the error message. Change the settings for the custom model, or set the Forecast Model to Automatic. |
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|
| DATE('01/01/'+STR([Member since])) |
| Date | Reservation type | Requester ID | ID | First name | Last name | Branch | Member since | Units borrowed | Fees | Suggested limit |
|---|---|---|---|---|---|---|---|---|---|---|
01/01/2000 | Individual | 233445589 | 232502870 | Alan | Wang | North | 2000 | 1 | 0.00 | 15 |
| 01/01/2000 | Individual | 233445589 | 233445589 | Fred | Suzuki | North | 2000 | 52 | 0.90 | 15 |
| 01/01/2000 | Individual | 233445589 | 233445566 | Ashley | Garcia | South | 2000 | 243 | 11.30 | 15 |
| 01/01/2000 | Individual | 233445589 | 233448978 | John | Smith | North | 2000 | 36 | 3.50 | 15 |
| Parameter | Description | Example of returned value |
| TableauServerUser | The username of the current server user. Use when setting up impersonation on the server. Returns an empty string if the user isn’t signed in to Tableau Server. | jsmith |
| TableauServerUserFull | The username and domain of the current server user. Use when setting up impersonation on the server. Returns an empty string if the user isn’t signed in to Tableau Server. | domain.lan\jsmith |
| TableauApp | The name of the Tableau application. | Tableau Desktop Professional Tableau Server |
| TableauVersion | The version of the Tableau application. | 9.3 |
| WorkbookName | The name of the Tableau workbook. Use only in workbooks with an embedded data source. | Financial-Analysis |
| Hover | Select | Menu |
 |  |  |
| Live connection | Extract connection |
 |  |
| Aliases hidden | Aliases showing |
 |  |
| Number of records | Time to retrieve |
|---|---|
1,000 | 11 seconds |
10,000 | 2 minutes |
100,000 | 18 minutes |
| F4 | Starts and stops forward playback |
| SHIFT + F4 | Starts and stops backward playback |
| CTRL + . | Skip forward one page |
| CTRL + , | Skip backward one page |
| F4 | Starts and stops forward playback |
| Shift-F4 | Starts and stops backward playback |
| Command-full stop | Skip forward one page |
| Command-comma | Skip backward one page |
Empty Rows Hidden (default) Jay isn't in any clubs, so there's no row for the student Jay. Every row has a placeholder mark (Abc). | Empty Rows Shown Jay isn't in any clubs, but empty rows are shown, so there is a row for Jay with no placeholder mark (Abc). |
 |  |
| Label options in Tableau Desktop: All | Label option in Web Editing: Min/Max |
 |  |
 | Fixed size (default): The dashboard remains the same size, regardless of the size of the window used to display it. If the dashboard is larger than the window, it becomes scrollable. You can pick from a preset size or specify a custom size. Fixed size dashboards let you specify the exact location and position of the content on the dashboard, which can be useful if there are floating objects. Published dashboards that use a fixed size can load faster because they're more likely to use a cached version on the server. For other performance tips, see Optimise Workbook Performance. |
 | Range: The dashboard scales between the minimum and maximum sizes that you specify. If the window used to display the dashboard is smaller than the minimum size, scroll bars are displayed. If it's larger than the maximum size, white space is displayed. Use this setting when you're designing for two different display sizes that need the same content and have similar shapes – such as small- and medium-sized browser windows. Range also works well for mobile dashboards with vertical layouts. (The width is allowed to change for different mobile device widths, but the height is fixed for vertical scrolling.) |
 | Automatic: The dashboard automatically resizes to fill the window used to display it. Use this setting if you want Tableau to take care of any resizing. For best results, use a tiled (rather than floating) dashboard layout. Automatic sizing can lead to unpredictable results on different screens, so use this setting with caution if you don't know where the dashboard will be consumed. Dashboards with variable sizes must be freshly rendered for every browser request, which can have a performance impact. |
Horizontal layout container The two views are arranged in a horizontal layout container. | Vertical layout container The three views are stacked in a vertical layout container. |
| With mark selected | Without a selection |
 |  |
| Tiled layout | Floating layout |
| Tiled items don't overlap; they become part of a single-layer grid that resizes based on the overall dashboard size. | Floating items can be layered over other objects. In the example below, a map floats over tiled views. |
 |  |
| For best results, give floating objects and views a fixed size and position on a fixed size dashboard. |
| Nested | Non-nested |
 |  |
A nested sort considers each pane independently and sorts the rows per pane. Purple is sorted above Green for Fabric and Paper, but below Green for Paint. | A non-nested sort considers the value across panes and has the same order of values per pane. Purple is above Green for all materials because in aggregate, Purple is higher than Green. |
| Nested sorts look correct within the context of the pane, but don’t convey the aggregated information about how the values compare overall. | Non-nested sorts may look incorrect in a single pane, but consistently convey how the aggregated values compare overall. |
| Sorting from an axis gives a nested sort by default. | Sorting from a field label gives a non-nested sort by default. |
| Syntax | AREA(Spatial Polygon, 'units') |
| Output | Number |
| Definition | Returns the total surface area of a <spatial polygon>. |
| Example | AREA([Geometry], 'feet') |
| Notes | Supported unit names (must be in quotation marks in the calculation, such as
|
| Syntax | BUFFER(Spatial point, distance, 'units')
|
| Output | Geometry |
| Definition | For spatial points, returns a polygon shape centred over a For linestrings, computes the polygons formed by including all points within the radius distance from the linestring. For polygons, it calculates a polygon that is either an inset (negative distance) or outset (positive distance) of each given polygon. |
| Example | BUFFER([Spatial Point Geometry], 25, 'mi') BUFFER(MAKEPOINT(47.59, -122.32), 3, 'km') BUFFER(MAKELINE(MAKEPOINT(0, 20),MAKEPOINT (30, 30)),20,'km')) |
| Notes | Supported unit names (must be in quotation marks in the calculation, such as
|
| Syntax | DIFFERENCE(Spatial, Spatial) |
| Output | Spatial Polygon |
| Definition | Computes the portions of regions remaining when all regions in the second argument are carved out of the first argument in areas that overlap. Discards regions from the second argument in areas that don't overlap. |
| Example | DIFFERENCE(Spatial Polygon1, Spatial Polygon2) |
| Notes | Supports spatial polygons and multipolygons, not spatial points or lines. |
| Syntax | DISTANCE(SpatialPoint1, SpatialPoint2, 'units') |
| Output | Number |
| Definition | Returns the distance measurement between two points in the specified <unit>. |
| Example | DISTANCE([Origin Point],[Destination Point], 'km') |
| Notes | Supported unit names (must be in quotation marks in the calculation, such as
|
| Database limitations | This function can only be created with a live connection but will continue to work if the data source is converted to an extract. |
| Syntax | INTERSECTION (spatial, spatial) |
| Output | Polygon |
| Definition | Computes and returns the portions of regions in the second argument that overlap regions in the first argument. |
| Example | INTERSECTION (Spatial Polygon1, Spatial Polygon2) |
| Notes | Supports spatial polygons and multipolygons, not spatial points or lines. |
| Syntax | INTERSECTS (geometry1, geometry2) |
| Output | Boolean |
| Definition | Returns true or false indicating whether two geometries overlap in space. |
| Notes | Supported combinations: point/polygon, line/polygon and polygon/polygon. |
| Syntax | LENGTH(geometry, 'units') |
| Output | Number |
| Definition | Returns the geodetic path length of the line string or strings in the <geometry> using the given <units>. |
| Example | LENGTH([Spatial], 'metres') |
| Notes | The result is <NaN> if the geometry argument has no linestrings, though other elements are permitted. |
| Syntax | MAKELINE(SpatialPoint1, SpatialPoint2) |
| Output | Geometry (line) |
| Definition | Generates a line mark between two points |
| Example | MAKELINE(MAKEPOINT(47.59, -122.32), MAKEPOINT(48.5, -123.1)) |
| Notes | Useful for building origin-destination maps. |
| Syntax | MAKEPOINT(latitude, longitude, [SRID]) |
| Output | Geometry (point) |
| Definition | Converts data from If the optional |
| Example | MAKEPOINT(48.5, -123.1) MAKEPOINT([AirportLatitude], [AirportLongitude]) MAKEPOINT([Xcoord],[Ycoord], 3493) |
| Notes |
You can use |
| Syntax | NO_CUTOUTS (spatial) |
| Output | Corrected spatial polygon |
| Definition | Returns a corrected spatial polygon if a flat-earth interpretation requires polygon inversions; otherwise, returns the original. |
| Notes | Spatial file formats like Keyhole Markup Language (.kml) require polygon boundaries to follow a specific coordinate direction. If a data set draws boundaries in reverse, Tableau interprets the exterior space as the shape. |
| Syntax | OUTLINE(spatial polygon) |
| Output | Geometry |
| Definition | Converts a polygon geometry into linestrings. |
| Notes | Useful for creating a separate layer for an outline that can be styled differently than the fill. Supports polygons within multipolygons. |
| Syntax | PARSE_WKT (String) |
| Output | Spatial (Geography) |
| Definition | Converts a text string field containing well-known text (WKT) representations of geographic entities (such as points, linestrings or polygons) into a spatial value. |
| Notes | Coordinates are assumed to use WGS-84 latitude and longitude. For more information about WKT, see Well-Known Text Representation of Geometry. |
| Syntax | SHAPETYPE(geometry) |
| Output | String |
| Definition | Returns a string describing the structure of the spatial <geometry>, such as Empty, Point, MultiPoint, LineString, MultiLinestring, Polygon, MultiPolygon, Mixed and unsupported. |
| Example | SHAPETYPE(MAKEPOINT(48.5, -123.1)) = "Point" |
| Syntax | SYMDIFFERENCE(spatial, spatial) |
| Output | Geometry |
| Definition | Computes any portions of regions from the second argument that overlap regions in the first argument and discards from both. Returns the remaining portions of regions from both arguments. |
| Example |
|
| Syntax | UNION(spatial 1, [spatial 2]) |
| Output | Geometry |
| Definition | Combines spatial geometries by dissolving adjacent or overlapping boundaries into a single spatial geometry. |
| Notes | When used with one argument ( When used with two arguments ( For points and linestrings, |
| Syntax | VALIDATE(spatial geometry) |
| Output | Geometry |
| Definition | Confirms topological correctness of the geometry in your spatial value. If the value cannot be used for analysis due to problems such as a polygon’s perimeter intersecting itself, then the result will be a null. If the geometry is correct, the result will be the original geometry. |
| Example |
|
| Operator | DIFFERENCE |
| Definition | Computes the portions of regions remaining when all regions in the second argument are carved out of the first argument in areas that overlap. Discards regions from the second argument in areas that don't overlap. |
| Example |
|
| Operator | INTERSECTION |
| Definition | Computes and returns the portions of regions in the second argument that overlap regions in the first argument. |
| Example |
|
| Operator | SYMDIFFERENCE |
| Definition | Computes any portions of regions from the second argument that overlap regions in the first argument and discards from both. Returns the remaining portions of regions from both arguments. |
| Example |
|
| Operator | UNION |
| Definition | Monadic union (one parameter) Syntax:
Dyadic union (two parameters) Syntax:
|
| Example |
|
| Calculation | Result |
RIGHT([Value], 4) | 8892 |
LEFT([Value], 4) | IGW8 |
LEFT(RIGHT([Value], 2) , 1) | 9 |
| Original value | Split field values |
| Zip-98102 | 98102 |
| Zip-98109 | 98109 |
| Zip-98119 | 98199 |
| Zip-98195 | 98195 |
| Text Table | Adding a dimension first produces a text table (or cross-tab). All subsequent clicks on fields result in refinement of the text table. |
| Bars | Adding a measure first and then a dimension produces a bar view. All subsequent clicks result in refinement of the bar view, unless a date dimension is added, at which time the view is changed to a line. |
| Line | Adding a measure and then a date dimension produces a line view. All subsequent clicks result in refinement of the line view. |
| Continuous Line | Adding a continuous dimension and then a measure produces a continuous line view. Subsequent dimensions result in refinement of the continuous line view. Subsequent measures add quantitative axes to the view. |
| Scatter | Adding a measure and then another measure produces a scatter view. Subsequent dimensions result in refinement to the scatter view. Subsequent measures will create a scatter matrix. |
| Maps | Adding a geographic field produces a map view with latitude and longitude as axes and the geographic field on the Level of Detail shelf. Subsequent dimensions add rows to the view while subsequent measures further refine the map by adding size and colour encoding. |
| Syntax | ASCII(string) |
| Output | Number |
| Definition | Returns the ASCII code for the first character of a <string>. |
| Example | ASCII('A') = 65 |
| Notes | This is the inverse of the CHAR function. |
| Syntax | CHAR(number) |
| Output | String |
| Definition | Returns the character encoded by the ASCII code <number>. |
| Example | CHAR(65) = 'A' |
| Notes | This is the inverse of the ASCII function. |
| Syntax | CONTAINS(string, substring) |
| Output | Boolean |
| Definition | Returns true if the given string contains the specified substring. |
| Example | CONTAINS("Calculation", "alcu") = true |
| Notes | See also the logical function Depending on the data source, CONTAINS may be case sensitive. That is, for some data sources, |
| Syntax | ENDSWITH(string, substring) |
| Output | Boolean |
| Definition | Returns true if the given string ends with the specified substring. Trailing white spaces are ignored. |
| Example | ENDSWITH("Tableau", "leau") = true |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | FIND(string, substring, [start]) |
| Output | Number |
| Definition | Returns the index position of substring in string, or 0 if the substring isn't found. The first character in the string is position 1. If the optional numeric argument |
| Example | FIND("Calculation", "alcu") = 2FIND("Calculation", "Computer") = 0FIND("Calculation", "a", 3) = 7FIND("Calculation", "a", 2) = 2FIND("Calculation", "a", 8) = 0 |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | FINDNTH(string, substring, occurrence) |
| Output | Number |
| Definition | Returns the position of the nth occurrence of substring within the specified string, where n is defined by the occurrence argument. |
| Example | FINDNTH("Calculation", "a", 2) = 7 |
| Notes |
See also the supported RegEx in the additional functions documentation. |
| Syntax | LEFT(string, number) |
| Output | String |
| Definition | Returns the left-most <number> of characters in the string. |
| Example | LEFT("Matador", 4) = "Mata" |
| Notes | See also MID and RIGHT. |
| Syntax | LEN(string) |
| Output | Number |
| Definition | Returns the length of the string. |
| Example | LEN("Matador") = 7 |
| Notes | Not to be confused with the spatial function LENGTH. |
| Syntax | LOWER(string) |
| Output | String |
| Definition | Returns the provided <string> in all lowercase characters. |
| Example | LOWER("ProductVersion") = "productversion" |
| Notes | See also UPPER and PROPER. |
| Syntax | LTRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with any leading spaces removed. |
| Example | LTRIM(" Matador ") = "Matador " |
| Notes | See also RTRIM. |
| Syntax | MAX(expression) or MAX(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the maximum of the two arguments, which must be of the same data type.
|
| Example | MAX(4,7) = 7 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | (MID(string, start, [length]) |
| Output | String |
| Definition | Returns a string starting at the specified If the optional numeric argument |
| Example | MID("Calculation", 2) = "alculation"MID("Calculation", 2, 5) ="alcul" |
| Notes | See also the supported RegEx in the additional functions documentation. |
| Syntax | MIN(expression) or MIN(expr1, expr2) |
| Output | Same data type as the argument, or NULL if any part of the argument is null. |
| Definition | Returns the minimum of the two arguments, which must be of the same data type.
|
| Example | MIN(4,7) = 4 |
| Notes | For strings
For database data sources, the For dates For dates, the As an aggregation
As a comparison
See also |
| Syntax | PROPER(string) |
| Output | String |
| Definition | Returns the provided |
| Example | PROPER("PRODUCT name") = "Product Name"PROPER("darcy-mae") = "Darcy-Mae" |
| Notes | Spaces and non-alphanumeric characters such as punctuation are treated as separators. |
| Database limitations | PROPER is only available for some flat files and in extracts. If you need to use PROPER in a data source that doesn't otherwise support it, consider using an extract. |
| Syntax | REPLACE(string, substring, replacement |
| Output | String |
| Definition | Searches <string> for <substring> and replaces it with <replacement>. If <substring> is not found, the string is not changed. |
| Example | REPLACE("Version 3.8", "3.8", "4x") = "Version 4x" |
| Notes | See also REGEXP_REPLACE in the additional functions documentation. |
| Syntax | RIGHT(string, number) |
| Output | String |
| Definition | Returns the right-most <number> of characters in the string. |
| Example | RIGHT("Calculation", 4) = "tion" |
| Notes | See also LEFT and MID. |
| Syntax | RTRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with any trailing spaces removed. |
| Example | RTRIM(" Calculation ") = " Calculation" |
| Notes | See also LTRIM and TRIM. |
| Syntax | SPACE(number) |
| Output | String (specifically, just spaces) |
| Definition | Returns a string that is composed of the specified number of repeated spaces. |
| Example | SPACE(2) = " " |
| Syntax | SPLIT(string, delimiter, token number) |
| Output | String |
| Definition | Returns a substring from a string, using a delimiter character to divide the string into a sequence of tokens. |
| Example | SPLIT ("a-b-c-d", "-", 2) = "b"SPLIT ("a|b|c|d", "|", -2) = "c" |
| Notes | The string is interpreted as an alternating sequence of delimiters and tokens. So for the string
See also supported RegEX in the additional functions documentation. |
| Database limitations | 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 strings. See SPLIT function limitations later in this topic. |
| Syntax | STARTSWITH(string, substring) |
| Output | Boolean |
| Definition | Returns true if string starts with substring. Leading white spaces are ignored. |
| Example | STARTSWITH("Matador, "Ma") = TRUE |
| Notes | See also CONTAINS, as well as supported RegEX in the additional functions documentation. |
| Syntax | TRIM(string) |
| Output | String |
| Definition | Returns the provided <string> with leading and trailing spaces removed. |
| Example | TRIM(" Calculation ") = "Calculation" |
| Notes | See also LTRIM and RTRIM. |
| Syntax | UPPER(string) |
| Output | String |
| Definition | Returns the provided <string> in all uppercase characters. |
| Example | UPPER("Calculation") = "CALCULATION" |
| Notes | See also PROPER and LOWER. |
| 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 |
| Here, each record is a day | Here, each record is a month |
|
|
| Summary view | Detail view |
 |  |
| Icon | Data type |
|---|---|
| Text (string) values |
| Date values |
| Date & Time values |
| Numerical values |
| Boolean operators (relational only) |
| Geographic values (used with maps) |
| Group table | Individual table |
 |  |
| Previous | Calculates the difference between the current value and the previous value in the partition. This is the default value. |
| Next | Calculates the difference between the current value and the next value in the partition. |
| First | Calculates the difference between the current value and the first value in the partition. |
| Last | Calculates the difference between the current value and the last value in the partition. |
| Previous | Calculates the difference between the current value and the previous value in the partition. This is the default value. |
| Next | Calculates the difference between the current value and the next value in the partition. |
| First | Calculates the difference between the current value and the first value in the partition. |
| Last | Calculates the difference between the current value and the last value in the partition. |
| Previous | Calculates the difference between the current value and the previous value in the partition. This is the default value. |
| Next | Calculates the difference between the current value and the next value in the partition. |
| First | Calculates the difference between the current value and the first value in the partition. |
| Last | Calculates the difference between the current value and the last value in the partition. |
| Option | Result |
| Competition (1, 2, 2, 4) | Identical values are assigned an identical rank. The highest value is ranked 1 and then the next two identical values are both are ranked 2. The last value is then ranked 4. |
| Modified Competition (1, 3, 3, 4) | Identical values are assigned an identical rank. The highest value is ranked 1 and then the next two identical values are both are ranked 3. The last value is then ranked 4. |
| Dense (1, 2, 2, 3) | Identical values are assigned an identical rank. The next value after the duplicate values is computed as though the duplicate values were a single value. |
| Unique (1, 2, 3, 4) | Duplicate values are given unique rankings, according to the direction in which the ranking is being computed. |
| Aggregation | Meaning |
| Sum | Each value is added to the previous value. |
| Average | The running total averages the current and all previous values. |
| Minimum | All values are replaced with the lowest value in the original partition. |
| Maximum | All values are replaced with the highest value in the original partition. |
| None | Specifies that the calculation should be performed at the level of greatest granularity. This is the default option. This option doesn’t change the view. |
| Quarter of Order Date | Specifies that the calculation should be performed at the quarter level. |
| Insight type | Definition |
| Concentrated Contribution | Shows when a small number of dimension members make up a majority (50% or more) of the contribution to a metric. |
| Top Drivers | Shows values for dimension members that changed the most in the same direction as the observed change in the metric. |
| Current Trend | Shows current trends to communicate the rate of change, direction and fluctuations for the metric value. |
| Trend Change | Shows new trends that vary significantly from the current trend. This insight communicates the rate of change, direction and fluctuations for the metric value. |
| Bottom Contributors | Shows the lowest values in a dimension for a metric within a given time range. |
| Top Detractors | Shows values for dimension members that changed the most in the opposite direction to the observed change in the metric. |
| Unexpected Values (outliers) | Shows when the value of a metric for a given time range is higher or lower than the expected range based on historic observations of the metric. |
| CAP_CREATE_TEMP_TABLES | Set to 'yes' if Tableau can create temporary tables needed for certain complex or optimised queries. See also: CAP_SELECT_INTO. |
| CAP_CONNECT_STORED_PROCEDURE | Set to 'yes' to allow support for connecting to a stored procedure. |
| CAP_FAST_METADATA | Set to 'yes' if you have small to moderate size schemas. This capability controls whether Tableau should enumerate all of the objects immediately when you connect. Set the value to ‘yes’ to enable this capability for better performance when creating new connections. Disable this capability to allow search for specific schemas or tables instead of retrieving all objects. You can search for all objects by using an empty string. This capability is available in 9.0 and later. |
| CAP_ISOLATION_LEVEL_READ_COMMITTED | Set to 'yes' to force the transaction isolation level to Read Committed if the data source supports it. Only one of the four transaction isolation levels should be set to 'yes'. See also: CAP_SET_ISOLATION_LEVEL_VIA_SQL, CAP_SET_ISOLATION_LEVEL_VIA_ODBC_API. |
| CAP_ISOLATION_LEVEL_READ_UNCOMMITTED | Set to 'yes' to force the transaction isolation level to Read Uncommitted if the data source supports it. Only one of the four transaction isolation levels should be set to 'yes'. This capability can improve speed by reducing lock contention, but may result in partial or inconsistent data in query results. See also: CAP_SET_ISOLATION_LEVEL_VIA_SQL, CAP_SET_ISOLATION_LEVEL_VIA_ODBC_API. |
| CAP_ISOLATION_LEVEL_REPEATABLE_READS | Set to 'yes' to force the transaction isolation level to Repeatable Reads if the data source supports it. Only one of the four transaction isolation levels should be set to 'yes'. See also: CAP_SET_ISOLATION_LEVEL_VIA_SQL, CAP_SET_ISOLATION_LEVEL_VIA_ODBC_API. |
| CAP_ISOLATION_LEVEL_SERIALIZABLE | Set to 'yes' to force the transaction isolation level to Serializable if the data source supports it. Only one of the four transaction isolation levels should be set to 'yes'. This is a very conservative setting that may improve stability at the expense of performance. See also: CAP_SET_ISOLATION_LEVEL_VIA_SQL, CAP_SET_ISOLATION_LEVEL_VIA_ODBC_API. |
| CAP_SET_ISOLATION_LEVEL_VIA_ODBC_API | Set to 'yes' to force Tableau to set the transaction isolation level for the data source using the ODBC API. CAP_SET_ISOLATION_LEVEL_VIA_ODBC_API must be set to 'yes' when any one of the four CAP_ISOLATION_LEVEL capabilities has been set to 'yes'. |
| CAP_SET_ISOLATION_LEVEL_VIA_SQL | Set to 'yes' to force Tableau to set the transaction isolation level for the data source using a SQL query. CAP_SET_ISOLATION_LEVEL_VIA_SQL must be set to 'yes' when any one of the four CAP_ISOLATION_LEVEL capabilities has been set to 'yes'. |
| CAP_MULTIPLE_CONNECTIONS_FROM_SAME_IP | Set to 'no' to prevent Tableau from creating more than one active connection to the database. This is a conservative setting that may increase stability at the expense of performance. |
| CAP_ODBC_BIND_DETECT_ALIAS_CASE_FOLDING | Set to 'yes' to allow Tableau to detect and recover from an ODBC data source that reports the field names in a result set using only upper-case or lower-case characters, instead of the expected field names. |
| CAP_ODBC_BIND_BOOL_AS_WCHAR_01LITERAL | Set to 'yes' to bind a Boolean data type as a WCHAR containing values '0' or '1'. |
| CAP_ODBC_BIND_BOOL_AS_WCHAR_TFLITERAL | Set to 'yes' to bind a Boolean data type as WCHAR containing values 't' or 'f'. |
| CAP_ODBC_BIND_FORCE_DATE_AS_CHAR | Set to 'yes' to force the Tableau native ODBC protocol to bind date values as CHAR. |
| CAP_ODBC_BIND_FORCE_DATETIME_AS_CHAR | Set to 'yes' to force the Tableau native ODBC protocol to bind datetime values as CHAR. |
| CAP_ODBC_BIND_FORCE_MAX_STRING_BUFFERS | Set to 'yes' to force the Tableau native ODBC protocol to use maximum-sized buffers (1MB) for strings instead of the size described by metadata. |
| CAP_ODBC_BIND_FORCE_MEDIUM_STRING_BUFFERS | Set to 'yes' to force the Tableau native ODBC protocol to use medium-sized buffers (1K) for strings instead of the size described by metadata. |
| CAP_ODBC_BIND_FORCE_SMALL_STRING_BUFFERS | Set to 'yes' to force the Tableau native ODBC protocol to use small buffers for strings instead of the size described by metadata. |
| CAP_ODBC_BIND_FORCE_SIGNED | Set to 'yes' to force binding integers as signed. |
| CAP_ODBC_BIND_PRESERVE_BOM | Set to 'yes' to preserve BOM when present in strings. Hive will return BOM and treat strings containing it as distinct entities. |
| CAP_ODBC_BIND_SKIP_LOCAL_DATATYPE_UNKNOWN | Set to ‘yes’ to prevent the native ODBC Protocol from binding to columns having local data type DataType::Unknown in the expected metadata. |
| CAP_ODBC_BIND_SPATIAL_AS_WKT | Set to ‘yes’ to force binding Spatial data as WKT (Well Known Text) |
| CAP_ODBC_BIND_SUPPRESS_COERCE_TO_STRING | Set to 'yes' to prevent the Tableau native ODBC protocol from binding non-string data as strings (i.e. requesting driver conversion). |
| CAP_ODBC_BIND_SUPPRESS_INT64 | Set to 'yes' to prevent the Tableau native ODBC protocol from using 64-bit integers for large numeric data. |
| CAP_ODBC_BIND_SUPPRESS_PREFERRED_CHAR | Set to 'yes' to prevent the Tableau native ODBC protocol from preferring a character type that differs from the driver default. |
| CAP_ODBC_BIND_SUPPRESS_PREFERRED_TYPES | Set to 'yes' to prevent the Tableau native ODBC protocol from binding any data according to its preferred wire types. With this capability set, Tableau will only bind according to the data types described by the ODBC driver via metadata. |
| CAP_ODBC_BIND_SUPPRESS_WIDE_CHAR | Set to 'yes' to prevent the Tableau native ODBC protocol from binding strings a WCHAR. Instead they will be bound as single-byte CHAR arrays, and processed locally for any UTF-8 characters contained within. |
| CAP_ODBC_CONNECTION_STATE_VERIFY_FAST | Set to ‘yes’ to check if a connection is broken with a fast ODBC API call. |
| CAP_ODBC_CONNECTION_STATE_VERIFY_PROBE | Set to ‘yes’ to check if a connection is broken with a forced probe. |
| CAP_ODBC_CONNECTION_STATE_VERIFY_PROBE_IF_STALE | Set to ‘yes’ to check if a connection is broken with a forced probe only if it is ‘stale’ (i.e., unused for about 30 minutes). |
| CAP_ODBC_CONNECTION_STATE_VERIFY_PROBE_PREPARED_QUERY | Set to ‘yes’ to check if a connection is broken using a prepared query. |
| CAP_ODBC_CURSOR_DYNAMIC | Set to 'yes' to force the Tableau native ODBC protocol to set the cursor type for all statements to Dynamic (scrollable, detects added/removed/modified rows). |
| CAP_ODBC_CURSOR_FORWARD_ONLY | Set to 'yes' to force the Tableau native ODBC protocol to set the cursor type for all statements to Forward-only (non-scrollable). |
| CAP_ODBC_CURSOR_KEYSET_DRIVEN | Set to 'yes' to force the Tableau native ODBC protocol to set the cursor type for all statements to Keyset-driven (scrollable, detects changes to values within a row). |
| CAP_ODBC_CURSOR_STATIC | Set to 'yes' to force Tableau to set the cursor type for all statements to Static (scrollable, does not detect changes). |
| CAP_ODBC_ERROR_IGNORE_FALSE_ALARM | Set to 'yes' to allow the Tableau native ODBC protocol to ignore SQL_ERROR conditions where SQLSTATE is '00000' (meaning "no error"). |
| CAP_ODBC_ERROR_IGNORE_SQLNODATA_FOR_COMMAND_QUERIES | Set to ‘yes’ to ignore when SQLExecDirect returns SQL_NO_DATA even when data is not expected back. |
| CAP_ODBC_EXPORT_ALLOW_CHAR_UTF8 | Set to 'yes' to allow the use of single-byte char data type for binding Unicode strings as UTF-8. |
| CAP_ODBC_EXPORT_BIND_FORCE_TARGET_METADATA | Set to 'yes' to force binding for export based on all of the metadata from the target table instead of the ODBC metadata for the parameterised insert statement. |
| CAP_ODBC_EXPORT_BIND_PREFER_TARGET_METADATA | Set to 'yes' to prefer binding for export based on specific types of metadata from the target table instead of the ODBC metadata for the parameterised insert statement. |
| CAP_ODBC_EXPORT_BUFFERS_RESIZABLE | Set to 'yes' to allow export buffers to be reallocated after the first batch to improve performance. |
| CAP_ODBC_EXPORT_BUFFERS_SIZE_FIXED | Set to 'yes' to ignore the width of a single row when computing the total rows to insert at a time. |
| CAP_ODBC_EXPORT_BUFFERS_SIZE_LIMIT_512KB | Set to 'yes' to limit export buffers to 512 KB. This is an uncommon setting. |
| CAP_ODBC_EXPORT_BUFFERS_SIZE_MASSIVE | Set to 'yes' to force the use of large buffers for insert. If CAP_ODBC_EXPORT_BUFFERS_RESIZABLE is not set or disabled, a fixed row count is used. |
| CAP_ODBC_EXPORT_BUFFERS_SIZE_MEDIUM | Set to 'yes' to force the use of medium-sized buffers for insert. If CAP_ODBC_EXPORT_BUFFERS_RESIZABLE is not set or disabled, a fixed row count is used. |
| CAP_ODBC_EXPORT_BUFFERS_SIZE_SMALL | Set to 'yes' to force the use of small buffers for insert. If CAP_ODBC_EXPORT_BUFFERS_RESIZABLE is not set or disabled, a fixed row count is used. |
| CAP_ODBC_EXPORT_CONTINUE_ON_ERROR | Set to 'yes' to continue data insert despite errors. Some data sources report warnings as errors. |
| CAP_ODBC_EXPORT_DATA_BULK | Set to 'yes' to allow the use of ODBC bulk operations for data insert. |
| CAP_ODBC_EXPORT_DATA_BULK_VIA_INSERT | Set to 'yes' to allow the use of ODBC bulk operations based on 'INSERT INTO' parameterised queries. |
| CAP_ODBC_EXPORT_DATA_BULK_VIA_ROWSET | Set to 'yes' to allow the use of ODBC bulk operations based on a rowset cursor. |
| CAP_ODBC_EXPORT_FORCE_INDICATE_NTS | Set to 'yes' to force the use of indicator buffers for identifying null-terminated strings (NTS). |
| CAP_ODBC_EXPORT_FORCE_SINGLE_ROW_BINDING | Set to 'yes' to force the use of a single row for binding export buffers to insert data. |
| CAP_ODBC_EXPORT_FORCE_SINGLE_ROW_BINDING_WITH_TIMESTAMPS | Set to 'yes' to force the use of a single row for binding export buffers when dealing with timestamp data. This is required for some versions of Teradata. |
| CAP_ODBC_EXPORT_FORCE_STRING_WIDTH_FROM_SOURCE | Set to 'yes' to force the use of the source string width (from Tableau metadata), overriding the destination string width (from insert parameter metadata). |
| CAP_ODBC_EXPORT_FORCE_STRING_WIDTH_USING_OCTET_LENGTH | Set to 'yes' to force the use of the source string width from the octet length. |
| CAP_ODBC_EXPORT_SUPPRESS_STRING_WIDTH_VALIDATION | Set to 'yes' to suppress validating that the target string width can accommodate the widest source strings. |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_BATCH_MASSIVE | Set to ‘yes’ to commit in massive batches of INSERT statements (~100,000). This may be useful with single-row export binding. |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_BATCH_MEDIUM | Set to 'yes' to commit in medium-sized batches of INSERT statements (~50). A single statement may be bound to multiple records. |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_BATCH_SMALL | Set to 'yes' to commit in small batches of INSERT statements (~5). A single statement may be bound to multiple records. |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_BYTES_MASSIVE | Set to 'yes' to commit in massive batches of data (~100 MB). |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_BYTES_MEDIUM | Set to 'yes' to commit in medium batches of data (~10 MB). |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_BYTES_SMALL | Set to 'yes' to commit in small batches of data (~1 MB). |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_EACH_STATEMENT | Set to 'yes' to commit after executing each INSERT statement. A single statement may be bound to multiple records. |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_INTERVAL_LONG | Set to 'yes' to commit in long intervals of elapsed time (~100 seconds). |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_INTERVAL_MEDIUM | Set to 'yes' to commit in medium intervals of elapsed time (~10 seconds). |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_INTERVAL_SHORT | Set to 'yes' to commit in short intervals of elapsed time (~1 seconds). |
| CAP_ODBC_EXPORT_TRANSACTIONS_COMMIT_ONCE_WHEN_COMPLETE | Set to 'yes' to commit only once at the end after the export is complete. |
| CAP_ODBC_EXPORT_TRANSLATE_DATA_PARALLEL | Set to 'yes' to use parallel loops to translate Tableau DataValues to wire buffers on export. |
| CAP_ODBC_FETCH_ABORT_FORCE_CANCEL_STATEMENT | Set to 'yes' to cancel the statement handle upon interrupting SQLFetch with a cancel exception. |
| CAP_ODBC_FETCH_BUFFERS_RESIZABLE | Set to 'yes' to allow buffers to be reallocated after fetch to improve performance or handle data truncation. |
| CAP_ODBC_FETCH_BUFFERS_SIZE_FIXED | Set to 'yes' to ignore the width of a single row when computing the total rows to fetch. |
| CAP_ODBC_FETCH_BUFFERS_SIZE_MASSIVE | Set to 'yes' to force the use of large buffers. If CAP_ODBC_FETCH_BUFFERS_SIZE_FIXED is enabled, a fixed row count is used. |
| CAP_ODBC_FETCH_BUFFERS_SIZE_MEDIUM | Set to 'yes' to force the use of medium-sized buffers. If CAP_ODBC_FETCH_BUFFERS_SIZE_FIXED is enabled, a fixed row count is used. |
| CAP_ODBC_FETCH_BUFFERS_SIZE_SMALL | Set to 'yes' to force the use of small buffers. If CAP_ODBC_FETCH_BUFFERS_SIZE_FIXED is enabled, a fixed row count is used. |
| CAP_ODBC_FETCH_CONTINUE_ON_ERROR | Set to 'yes' to allow the Tableau native ODBC protocol to continue resultset fetch despite errors (some data sources report warnings as errors). |
| CAP_ODBC_FETCH_IGNORE_FRACTIONAL_SECONDS | Set to 'yes' to allow the Tableau native ODBC protocol to ignore the fractional seconds component of a time value when fetching query result set data. This is useful when working with data sources that do not follow the ODBC specification for fractional seconds, which must be represented as billionths of a second. |
| CAP_ODBC_FETCH_RESIZE_BUFFERS | Set to 'yes' to allow the Tableau native ODBC protocol to automatically resize buffers and fetch again if data truncation occurred. |
| CAP_ODBC_FORCE_SINGLE_ROW_BINDING | Set to 'yes' to force the Tableau native ODBC protocol to use a single row for result set transfers instead of the more efficient bulk-fetch. |
| CAP_ODBC_IMPORT_ERASE_BUFFERS | Set to 'yes' to reset the contents of data buffers before fetching each block. |
| CAP_ODBC_IMPORT_TRANSLATE_DATA_PARALLEL | Set to ‘no’ to disable decoding data locally in parallel. |
| CAP_ODBC_METADATA_FORCE_LENGTH_AS_PRECISION | Set to 'yes' to force the Tableau native ODBC protocol to use the column ‘length’ as the numeric precision. This is an uncommon setting. |
| CAP_ODBC_METADATA_FORCE_NUM_PREC_RADIX_10 | Set to 'yes' to force the Tableau native ODBC protocol to assume the numeric precision is reported in base-10 digits. This is an uncommon setting. |
| CAP_ODBC_METADATA_FORCE_UNKNOWN_AS_STRING | Set to 'yes' to force the Native ODBC Protocol to treat unknown data types as string instead of ignoring the associated column. |
| CAP_ODBC_METADATA_FORCE_UTF8_IDENTIFIERS | Set to 'yes' to force the protocol to treat identifiers as UTF-8 when communicating with the driver. |
| CAP_ODBC_METADATA_SKIP_DESC_TYPE_NAME | Set to 'yes' to remove the check for the SQL_DESC_TYPE_NAME attribute with the SQLColAttribute API. |
| CAP_ODBC_METADATA_STRING_LENGTH_UNKNOWN | Set to 'yes' to prevent Tableau from allocating memory based on the driver-reported string length, which may not be known or reported properly. Instead, Tableau will use a fixed-sized string length, and will reallocate as needed to handle string data that is too large for the fixed-size buffer. |
| CAP_ODBC_METADATA_STRING_TRUST_OCTET_LENGTH | Set to 'yes' to use the octet length reported by the driver for strings instead of computing it from the number of characters. |
| CAP_ODBC_METADATA_SUPPRESS_EXECUTED_QUERY | Set to 'yes' to prevent Tableau from executing a query as a means of reading metadata. While Tableau typically includes a row-limiting clause in such metadata queries (e.g., 'LIMIT', or 'WHERE 1=0'), this may not help when used with a Custom SQL connection for database systems with poor query optimisers. Note that this capability may prevent Tableau from determining the connection metadata properly. |
| CAP_ODBC_METADATA_SUPPRESS_PREPARED_QUERY | Set to 'yes' to prevent Tableau from using a prepared query as a means of reading metadata. A prepared query is often the fastest way to accurately read metadata. However, not all database systems are capable of reporting metadata for a prepared query without actually executing the query. Note that certain metadata – for example from connections using Custom SQL– cannot be retrieved if this capability and CAP_ODBC_METADATA_SUPPRESS_EXECUTED_QUERY are both set. |
| CAP_ODBC_METADATA_SUPPRESS_READ_IDENTITY_COLUMNS | Set to ‘no’ to prevent reading identity column metadata. |
| CAP_ODBC_METADATA_SUPPRESS_SELECT_STAR | Set to 'yes' to prevent reading metadata using a 'select *' query. |
| CAP_ODBC_METADATA_SUPPRESS_SQLCOLUMNS_API | Set to 'yes' to prevent Tableau from using older, less accurate API for reading metadata from ODBC data sources. Setting this capability allows Tableau to read metadata by issuing a full 'select *' query, which is expensive but may enable connectivity for extremely limited or unstable data sources. |
| CAP_ODBC_METADATA_SUPPRESS_SQLFOREIGNKEYS_API | Set to 'yes' to prevent Tableau from attempting to read metadata describing foreign key constraints. Despite the simple nature of this ODBC API, some drivers may have unstable behaviour or produce inaccurate results. Setting this capability may force Tableau to generate less efficient queries involving multi-table joins. |
| CAP_ODBC_METADATA_SUPPRESS_SQLPRIMARYKEYS_API | Set to 'yes' to prevent Tableau from reading primary key metadata using the SQLPrimaryKeys API or an equivalent query. This capability is available in Tableau 9.1 and later. |
| CAP_ODBC_METADATA_SUPPRESS_SQLSTATISTICS_API | Set to 'yes' to prevent reading unique constraints and table cardinality estimates using the SQLStatistics API or an equivalent query. This capability is available in Tableau 9.0 and later. |
| CAP_ODBC_QUERY_USE_PREPARE_PARAMETER_MARKER | Enable to use prepared statements with parameter markers instead of literal values. Applies only for floating point, integer, and string values. |
| CAP_ODBC_REBIND_SKIP_UNBIND | Set to 'yes' to force the Tableau native ODBC protocol to rebind a column directly and skip unbinding, which reduces ODBC API calls when resizing buffers to refetch truncated data. |
| CAP_ODBC_SUPPORTS_LONG_DATA_BULK | Set to ‘yes’ if driver can fetch multiple long-data rows at a time. |
| CAP_ODBC_SUPPORTS_LONG_DATA_ORDERED | Set to ‘yes’ if driver requires long-data columns to come after non-long-data ones. |
| CAP_ODBC_SUPPRESS_INFO_SCHEMA_STORED_PROCS | Set to 'yes' to prevent the INFORMATION.SCHEMA schema from being queried when enumerating stored procedures. |
| CAP_ODBC_SUPPRESS_INFO_SCHEMA_TABLES | Set to ‘yes’ to prevent tables from “information_schema” schema from being returned by EnumerateTables. |
| CAP_ODBC_SUPPRESS_PG_TEMP_SCHEMA_TABLES | Set to ‘yes’ to prevent tables from “pg_temp” schema from being returned by EnumerateTables. |
| CAP_ODBC_SUPPRESS_PREPARED_QUERY_FOR_ALL_COMMAND_QUERIES | Set to 'yes' to execute all commands directly (i.e., no prepared statement). |
| CAP_ODBC_SUPPRESS_PREPARED_QUERY_FOR_DDL_COMMAND_QUERIES | Set to 'yes' to execute DDL commands (e.g. CREATE TABLE) directly (i.e., no prepared statement). |
| CAP_ODBC_SUPPRESS_PREPARED_QUERY_FOR_DML_COMMAND_QUERIES | Set to 'yes' to execute DML commands (e.g. INSERT INTO) directly (i.e, no prepared statement). |
| CAP_ODBC_SUPPRESS_PREPARED_QUERY_FOR_NON_COMMAND_QUERIES | Set to ‘yes’ to execute all non-command queries directly (no prepared statement). |
| CAP_ODBC_SUPPRESS_SYS_SCHEMA_STORED_PROCS | Set to 'yes' to explicitly add the ‘SYS’ schema to the schema exclusions when enumerating stored procedures. |
| CAP_ODBC_TRANSACTIONS_COMMIT_INVALIDATES_PREPARED_QUERY | Set to ‘yes’ to indicate that a transaction will invalidate all prepared statements and close any open cursors. |
| CAP_ODBC_TRANSACTIONS_SUPPRESS_AUTO_COMMIT | Set to 'yes' to prevent the Native ODBC Protocol from using default auto-committing transaction behaviour in ODBC. This capability cannot be used with CAP_ODBC_TRANSACTIONS_SUPPRESS_EXPLICIT_COMMIT. |
| CAP_ODBC_TRANSACTIONS_SUPPRESS_EXPLICIT_COMMIT | Set to 'yes' to prevent the Native ODBC Protocol from explicitly managing transactions. This capability cannot be used with CAP_ODBC_TRANSACTIONS_SUPPRESS_AUTO_COMMIT. |
| CAP_ODBC_TRIM_CHAR_LEAVE_PADDING | Set to 'yes' to leave whitespace padding at the end of a character or text data type. Most data sources will trim this whitespace automatically, but the behaviour depends on the driver. |
| CAP_ODBC_TRIM_VARCHAR_PADDING | Set to 'yes' to force the Tableau native ODBC protocol to trim trailing whitespace from VARCHAR columns which the driver has erroneously padded. |
| CAP_ODBC_UNBIND_AUTO | Set to 'yes' to force the Tableau native ODBC protocol to unbind and deallocate columns automatically, which can reduce ODBC API calls. |
| CAP_ODBC_UNBIND_BATCH | Set to 'yes' to force the Tableau native ODBC protocol to unbind and deallocate columns in a single batch operation, which can reduce ODBC API calls. |
| CAP_ODBC_UNBIND_EACH | Set to 'yes' to force the Tableau native ODBC protocol to unbind and deallocate columns individually, which may improve stability. |
| CAP_ODBC_UNBIND_PARAMETERS_BATCH | Set to ‘yes’ to unbind all parameters in a single batch operation. |
| CAP_ORACLE_SHOW_ALL_SYNONYM_OWNERS | Set to 'yes' to list all the owners in the all_synonyms view for Oracle. This capability is available in 9.0 and later. |
| CAP_QUERY_BOOLEXPR_TO_INTEXPR | Set to 'yes' if Tableau must coerce any Boolean expressions to an integer value in order include in a result set. |
| CAP_QUERY_FROM_REQUIRES_ALIAS | Set to 'yes' if the FROM clause must provide an alias for the given table. |
| CAP_QUERY_GROUP_ALLOW_DUPLICATES | Set to 'no' if SQL queries cannot contain duplicate expressions in the GROUP BY clause (this is uncommon). |
| CAP_QUERY_GROUP_BY_ALIAS | Set to 'yes' if SQL queries with aggregations can reference the grouping columns by their corresponding alias in the SELECT list, e.g. GROUP BY ‘none_ShipCountry_nk. |
| CAP_QUERY_GROUP_BY_DEGREE | Set to 'yes' if SQL queries with aggregations can reference the grouping columns by the ordinal position of each column, e.g. GROUP BY 2, 5. See also: CAP_QUERY_SORT_BY_DEGREE |
| CAP_QUERY_HAVING_REQUIRES_GROUP_BY | Set to 'yes' if Tableau must use an artificial grouping field for any query which has a HAVING clause but no grouping columns. |
| CAP_QUERY_HAVING_UNSUPPORTED | Set to 'yes' if the SQL syntax for HAVING is unsupported. Tableau may be able to work around this using subqueries. See also: CAP_QUERY_SUBQUERIES. |
| CAP_QUERY_INCLUDE_GROUP_BY_COLUMNS_IN_SELECT | Set to 'yes' to require all GROUP BY expressions to also appear in the SELECT expression list. |
| CAP_QUERY_JOIN_ACROSS_SCHEMAS | Set to 'yes' if SQL queries can express joins between tables located in different schemas. |
| CAP_QUERY_JOIN_ASSUME_CONSTRAINED | Set to ‘yes’ to cull inner joins even if the database tables does do not have FK-PK relationships. |
| CAP_QUERY_JOIN_PUSH_DOWN_CONDITION_EXPRESSIONS | Set to 'yes' to rewrite joins to simplify the ON clause conditions to simple identifier comparisons. |
| CAP_QUERY_JOIN_REQUIRES_SCOPE | Set to 'yes' if SQL queries must scope each join clause within parentheses to ensure a proper order of evaluation. |
| CAP_QUERY_JOIN_REQUIRES_SUBQUERY | Set to ‘yes’ to force join expressions involving more than two tables to be composed with subqueries. |
| CAP_QUERY_NULL_REQUIRES_CAST | Set to 'yes' if the data source requires that all NULL literals are cast to an explicit data type. |
| CAP_QUERY_SELECT_ALIASES_SORTED | Set to 'yes' if Tableau must impose a deterministic order on the SELECT expressions (sorted by alias) to ensure that query results can be properly matched with each field in the Tableau visualisation. This is only required for data sources which do not preserve the aliases of the SELECT expressions when returning metadata with the query results. |
| CAP_QUERY_SORT_BY_DEGREE | Set to 'yes' if SQL queries can reference the sorting columns by the ordinal position of each column, e.g. ORDER BY 2, 5. See also: CAP_QUERY_GROUP_BY_DEGREE. |
| CAP_QUERY_SUBQUERIES | Set to 'yes' if the data source supports subqueries. |
| CAP_QUERY_SUBQUERIES_WITH_TOP | Set to 'yes' if the data source supports a TOP or LIMIT row-limiting clause within a subquery. |
| CAP_QUERY_SUBQUERY_DATASOURCE_CONTEXT | Set to 'yes' to use subquery filtered query context to implement data source filters. This capability is available in Tableau 8.0 through Tableau 9.3 only. |
| CAP_QUERY_SUBQUERY_QUERY_CONTEXT | Set to 'yes' to force Tableau to use a subquery for context filters instead of a temporary table or locally cached results. |
| CAP_QUERY_TOP_0_METADATA | Set to ‘yes’ if the data source can handle a “TOP 0” request for retrieving metadata. |
| CAP_QUERY_TOP_N | Set to 'yes' if the data source supports any form of row-limiting clause. The exact forms supported are described below. |
| CAP_QUERY_TOPSTYLE_LIMIT | Set to 'yes' if the data source uses LIMIT as the row-limiting clause. |
| CAP_QUERY_TOPSTYLE_ROWNUM | Set to 'yes' if the data source supports an Oracle-style filter on ROWNUM as the row-limiting clause. |
| CAP_QUERY_TOPSTYLE_TOP | Set to 'yes' if the data source uses TOP as the row-limiting clause. |
| CAP_QUERY_USE_QUERY_FUSION | Set to ‘no’ to prevent Tableau from combining multiple individual queries into a single combined query. Turn off this capability for performance tuning or if the database is unable to process large queries. This capability is enabled by default and is available in Tableau 9.0 and later for all data sources except Tableau data extracts. Support for this capability in Tableau data extracts is available in Tableau 9.0.6. |
| CAP_QUERY_WHERE_FALSE_METADATA | Set to ‘yes’ if the data source can handle a “WHERE <false>” predicate for retrieving metadata. |
| CAP_SELECT_INTO | Set to 'yes' if Tableau can create a table on the fly from the resultset of another query. See also: CAP_CREATE_TEMP_TABLES. |
| CAP_SELECT_TOP_INTO | Set to 'yes' if Tableau can use a TOP or LIMIT row-limiting clause when creating a table from a query resultset. |
| CAP_STORED_PROCEDURE_PREFER_TEMP_TABLE | Set to 'yes' to use a temporary table to support remote queries over the stored procedure result set. |
| CAP_STORED_PROCEDURE_REPAIR_TEMP_TABLE_STRINGS | Set to 'yes' to attempt to compute actual string widths if metadata indicates no width or non-positive width. |
| CAP_STORED_PROCEDURE_TEMP_TABLE_FROM_BUFFER | Set to 'yes' to populate the temporary table from a result set buffered in entirety. |
| CAP_STORED_PROCEDURE_TEMP_TABLE_FROM_NEW_PROTOCOL | Set to ‘yes’ to populate the temporary table from a separate protocol created for just this operation. |
| CAP_SUPPRESS_DISCOVERY_QUERIES | Set to 'yes' to prevent Tableau from detecting the supported SQL syntax for a variety of clauses. |
| CAP_SUPPRESS_DISPLAY_LIMITATIONS | Set to 'yes' to suppress displaying any warnings about limitations for this data source. |
| Short Form | Full Form | Description |
--source-username <user name> | A valid user name for the data source connection. Use this option with
Note: You must provide the user name and password when refreshing a published extract, even if the data source was originally published with embedded credentials. | |
--source-password "<password>" | The password for the data source user. | |
or
| Path and file name for the data source to be refreshed on the server. For example: To refresh a multi-file data source, pass the path to a folder that contains the data files. For example: If the file is on a network share, use the UNC format for the path: | |
--force-full-refresh | If the data source is set up for incremental refreshes, use this option to force a full extract refresh. If this option is not included, an incremental refresh is performed. Not all data sources support incremental refresh. | |
-s <server http address> | --server <URL> | The URL for the Tableau server on which the data is published. For Tableau Cloud, specify |
-t <site id> | --site <siteid> | In a multiple-site environment, specifies the site to which the command applies. For Tableau Cloud, use this argument if your username is associated with more than one site. For Tableau Server, if you do not specify a site, the default site is assumed. The site id is independent of the site name, and it is indicated in the URL when you view the site in a browser. For example, if the URL for the page you see after signing in to Tableau Cloud is https://online.tableau.com/t/vernazza/views the site id is vernazza. |
--datasource <datasource> | The name of the data source, as published to Tableau Server or Tableau Cloud. | |
--project <projectname> | The project to which the data source belongs. If this option is not included, the default project is assumed. If the project you want to specify is a child project nested within a project hierarchy, you must use this parameter along with the | |
--parent-project-path path/to/project | If a project to which the data source is published is not at the top level of a project hierarchy, use this parameter along with the Use the forward slash character ( For example, for a project named Sandbox, in project Social, under top-level Marketing:
| |
-u <user name> | --username <username> | Valid Tableau Server or Tableau Cloud user. |
-p "<password>" | --password "<password>" | The password for the specified Tableau Server or Tableau Cloud user. |
--proxy-username <username> | The user name for a proxy server. | |
--proxy-password "<password>" | The password for a proxy server. | |
-c "<path and file name>" | --config-file "<path and file name>" | Path and file name information for a file containing configuration options for the command. Always enclose the path in double quotation marks. For more information, see Using a config file below. |
| Short Form | Full Form | Description |
--file <path and file name> | Path and file name information for the data file containing data to append. The file can be from Excel, Access, a Tableau data extract, or a delimited text file. It cannot be password protected. Use UNC format if the file is on a network share. For example, | |
-s <server http address> | --server <URL> | The URL for the Tableau server on which the data is published. For Tableau Cloud, specify |
-t <site id> | --site <site id> | In a multiple-site environment, specifies the site to which the command applies. For Tableau Cloud, you must include this argument if your username is associated with more than one site. For Tableau Server, if you do not specify a site, the default site is assumed. |
--datasource <datasource> | The name of the data source, as published to Tableau Server or Tableau Cloud. | |
--project <projectname> | The project to which the data source belongs. If this option is not included, the default project is assumed. If the project you want to specify is a child project nested within a project hierarchy, you must use this parameter along with the | |
--parent-project-path path/to/project | If a project to which the data source is published is not at the top level of a project hierarchy, use this parameter along with the Use the forward slash character ( For example, for a project named Sandbox, in project Social, under top-level Marketing:
| |
-u <username> | --username <username> | Valid Tableau Server or Tableau Cloud user. |
-p "<password>" | --password "<password>" | The password for the specified Tableau Server or Tableau Cloud user. |
--proxy-username <username> | The user name for a proxy server. | |
--proxy-password "<password>" | The password for a proxy server. | |
-c "<path and filename>" | --config-file "<path and filename>" | Path and file name information for a file containing configuration options for the command. Always enclose the path in double quotation marks. For more information, see Using a config file below. |
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| Publish visualisations to Tableau Cloud or Tableau Server | | | |
| Share packaged workbooks with other users | | | |
| Live data refresh | Limited data refresh (Google Drive only. Data is refreshed automatically once every 24 hours) | | |
| Data sources | Limited data source options (Google Drive, JSON files, Microsoft Excel 2007 or later, OData, PDF, Spatial files, Statistical files, Text files) | * Published data sources on Tableau Cloud or Tableau Server are not supported | |
| Data source rows | 15M rows | Unlimited | Unlimited |
| Cloud Storage | 10 GB on Tableau Public | | Tableau Cloud and Tableau Server if applicable |
| Local Storage | | | |
| CAP_CREATE_TEMP_TABLES | Set to 'yes' if Tableau can create temporary tables needed for certain complex or optimised queries. See also: CAP_SELECT_INTO. |
| CAP_CONNECT_STORED_PROCEDURE | Set to 'yes' to allow support for connecting to a stored procedure. |
| CAP_FAST_METADATA | Set to 'yes' if you have small to moderate size schemas. This capability controls whether Tableau should enumerate all of the objects immediately when you connect. Set the value to ‘yes’ to enable this capability for better performance when creating new connections. Disable this capability to allow search for specific schemas or tables instead of retrieving all objects. You can search for all objects by using an empty string. This capability is available in 9.0 and later. |
| CAP_ISOLATION_LEVEL_READ_COMMITTED | Set to 'yes' to force the transaction isolation level to Read Committed if the data source supports it. Only one of the four transaction isolation levels should be set to 'yes'. See also: CAP_SET_ISOLATION_LEVEL_VIA_SQL. |
| CAP_ISOLATION_LEVEL_READ_UNCOMMITTED | Set to 'yes' to force the transaction isolation level to Read Uncommitted if the data source supports it. Only one of the four transaction isolation levels should be set to 'yes'. This capability can improve speed by reducing lock contention, but may result in partial or inconsistent data in query results. See also: CAP_SET_ISOLATION_LEVEL_VIA_SQL. |
| CAP_ISOLATION_LEVEL_REPEATABLE_READS | Set to 'yes' to force the transaction isolation level to Repeatable Reads if the data source supports it. Only one of the four transaction isolation levels should be set to 'yes'. See also: CAP_SET_ISOLATION_LEVEL_VIA_SQL. |
| CAP_ISOLATION_LEVEL_SERIALIZABLE | Set to 'yes' to force the transaction isolation level to Serializable if the data source supports it. Only one of the four transaction isolation levels should be set to 'yes'. This is a very conservative setting that may improve stability at the expense of performance. See also: CAP_SET_ISOLATION_LEVEL_VIA_SQL. |
| CAP_JDBC_BIND_DETECT_ALIAS_CASE_FOLDING | Set to ‘yes’ to allow Tableau to detect and recover from a JDBC data source that reports the field names in a result set using only uppercase or lowercase characters, instead of the expected field names. |
| CAP_JDBC_EXPORT_DATA_BATCH | Set to 'no' to disable the use of JDBC batch operations for data insert. |
| CAP_JDBC_METADATA_GET_INDEX_INFO | Set to ‘no’ to disable reading index information. |
| CAP_JDBC_METADATA_READ_FOREIGNKEYS | Set to ‘no’ to disable reading foreign key metadata. |
| CAP_JDBC_METADATA_READ_PRIMARYKEYS | Set to ‘no’ to disable reading primary key metadata. |
| CAP_JDBC_METADATA_USE_RESULTSET_FOR_TABLE | Set to 'yes' to get column metadata from the result set of a select * query. Available in Tableau 2020.4 and newer. |
| CAP_JDBC_QUERY_ASYNC | Set to ‘yes’ to run queries on another thread. |
| CAP_JDBC_QUERY_CANCEL | Set to ‘yes’ if driver can cancel queries. |
| CAP_JDBC_QUERY_DISABLE_AUTO_COMMIT | Set to 'yes' to disable the default auto-commit mode when running query. Available in Tableau 2020.4 and newer. |
| CAP_JDBC_QUERY_FORCE_PREPARE | Set to 'yes' to always prepare the query before execution. Available in Tableau 2020.4 and newer. |
| CAP_JDBC_SUPPRESS_EMPTY_CATALOG_NAME | Set to 'yes' to ignore missing catalogue. |
| CAP_JDBC_SUPPRESS_ENUMERATE_DATABASES | Set to ‘yes’ to disable database enumeration. |
| CAP_JDBC_SUPPRESS_ENUMERATE_SCHEMAS | Set to ‘yes’ to disable schema enumeration. |
| CAP_JDBC_METADATA_SUPPRESS_PREPARED_QUERY | If CAP_JDBC_METADATA_USE_RESULTSET_FOR_TABLE is enabled, set this capability to 'yes' to disable preparing the query used for reading the table metadata. We will execute the query wrapped with a where-false clause. |
| CAP_JDBC_USE_ADAPTIVE_FETCH_SIZE | Set to 'yes' to use ResultSet metadata to determine optimal fetch size. May require CAP_JDBC_QUERY_FORCE_PREPARE to be enabled to work properly. Available in Tableau 2020.4 and newer. |
| CAP_MULTIPLE_CONNECTIONS_FROM_SAME_IP | Set to 'no' to prevent Tableau from creating more than one active connection to the database. This is a conservative setting that may increase stability at the expense of performance. |
| CAP_QUERY_BOOLEXPR_TO_INTEXPR | Set to 'yes' if Tableau must coerce any Boolean expressions to an integer value in order include in a result set. |
| CAP_QUERY_FROM_REQUIRES_ALIAS | Set to 'yes' if the FROM clause must provide an alias for the given table. |
| CAP_QUERY_GROUP_ALLOW_DUPLICATES | Set to 'no' if SQL queries cannot contain duplicate expressions in the GROUP BY clause (this is uncommon). |
| CAP_QUERY_GROUP_BY_ALIAS | Set to 'yes' if SQL queries with aggregations can reference the grouping columns by their corresponding alias in the SELECT list, e.g. GROUP BY ‘none_ShipCountry_nk. |
| CAP_QUERY_GROUP_BY_DEGREE | Set to 'yes' if SQL queries with aggregations can reference the grouping columns by the ordinal position of each column, e.g. GROUP BY 2, 5. See also: CAP_QUERY_SORT_BY_DEGREE |
| CAP_QUERY_HAVING_REQUIRES_GROUP_BY | Set to 'yes' if Tableau must use an artificial grouping field for any query which has a HAVING clause but no grouping columns. |
| CAP_QUERY_HAVING_UNSUPPORTED | Set to 'yes' if the SQL syntax for HAVING is unsupported. Tableau may be able to work around this using subqueries. See also: CAP_QUERY_SUBQUERIES. |
| CAP_QUERY_INCLUDE_GROUP_BY_COLUMNS_IN_SELECT | Set to 'yes' to require all GROUP BY expressions to also appear in the SELECT expression list. |
| CAP_QUERY_JOIN_ACROSS_SCHEMAS | Set to 'yes' if SQL queries can express joins between tables located in different schemas. |
| CAP_QUERY_JOIN_ASSUME_CONSTRAINED | Set to ‘yes’ to cull inner joins even if the database tables does do not have FK-PK relationships. |
| CAP_QUERY_JOIN_PUSH_DOWN_CONDITION_EXPRESSIONS | Set to 'yes' to rewrite joins to simplify the ON clause conditions to simple identifier comparisons. |
| CAP_QUERY_JOIN_REQUIRES_SCOPE | Set to 'yes' if SQL queries must scope each join clause within parentheses to ensure a proper order of evaluation. |
| CAP_QUERY_JOIN_REQUIRES_SUBQUERY | Set to ‘yes’ to force join expressions involving more than two tables to be composed with subqueries. |
| CAP_QUERY_NULL_REQUIRES_CAST | Set to 'yes' if the data source requires that all NULL literals are cast to an explicit data type. |
| CAP_QUERY_SELECT_ALIASES_SORTED | Set to 'yes' if Tableau must impose a deterministic order on the SELECT expressions (sorted by alias) to ensure that query results can be properly matched with each field in the Tableau visualisation. This is only required for data sources which do not preserve the aliases of the SELECT expressions when returning metadata with the query results. |
| CAP_QUERY_SORT_BY_DEGREE | Set to 'yes' if SQL queries can reference the sorting columns by the ordinal position of each column, e.g. ORDER BY 2, 5. See also: CAP_QUERY_GROUP_BY_DEGREE. |
| CAP_QUERY_SUBQUERIES | Set to 'yes' if the data source supports subqueries. |
| CAP_QUERY_SUBQUERIES_WITH_TOP | Set to 'yes' if the data source supports a TOP or LIMIT row-limiting clause within a subquery. |
| CAP_QUERY_SUBQUERY_DATASOURCE_CONTEXT | Set to 'yes' to use subquery filtered query context to implement data source filters. This capability is available in Tableau 8.0 through Tableau 9.3 only. |
| CAP_QUERY_SUBQUERY_QUERY_CONTEXT | Set to 'yes' to force Tableau to use a subquery for context filters instead of a temporary table or locally cached results. |
| CAP_QUERY_TOP_N | Set to 'yes' if the data source supports any form of row-limiting clause. The exact forms supported are described below. |
| CAP_QUERY_TOPSTYLE_LIMIT | Set to 'yes' if the data source uses LIMIT as the row-limiting clause. |
| CAP_QUERY_TOPSTYLE_ROWNUM | Set to 'yes' if the data source supports an Oracle-style filter on ROWNUM as the row-limiting clause. |
| CAP_QUERY_TOPSTYLE_TOP | Set to 'yes' if the data source uses TOP as the row-limiting clause. |
| CAP_QUERY_USE_QUERY_FUSION | Set to ‘no’ to prevent Tableau from combining multiple individual queries into a single combined query. Turn off this capability for performance tuning or if the database is unable to process large queries. This capability is enabled by default and is available in Tableau 9.0 and later for all data sources except Tableau data extracts. Support for this capability in Tableau data extracts is available in Tableau 9.0.6. |
| CAP_SELECT_INTO | Set to 'yes' if Tableau can create a table on the fly from the resultset of another query. See also: CAP_CREATE_TEMP_TABLES. |
| CAP_SELECT_TOP_INTO | Set to 'yes' if Tableau can use a TOP or LIMIT row-limiting clause when creating a table from a query result set. |
| CAP_SET_ISOLATION_LEVEL_VIA_SQL | Set to 'yes' to force Tableau to set the transaction isolation level for the data source using a SQL query. CAP_SET_ISOLATION_LEVEL_VIA_SQL must be set to 'yes' when any one of the four CAP_ISOLATION_LEVEL capabilities has been set to 'yes'. |
| CAP_STORED_PROCEDURE_PREFER_TEMP_TABLE | Set to 'yes' to use a temporary table to support remote queries over the stored procedure result set. |
| CAP_STORED_PROCEDURE_REPAIR_TEMP_TABLE_STRINGS | Set to 'yes' to attempt to compute actual string widths if metadata indicates no width or non-positive width. |
| CAP_STORED_PROCEDURE_TEMP_TABLE_FROM_BUFFER | Set to 'yes' to populate the temporary table from a result set buffered in entirety. |
| CAP_STORED_PROCEDURE_TEMP_TABLE_FROM_NEW_PROTOCOL | Set to ‘yes’ to populate the temporary table from a separate protocol created for just this operation. |
| CAP_SUPPRESS_DISCOVERY_QUERIES | Set to 'yes' to prevent Tableau from detecting the supported SQL syntax for a variety of clauses. |
| CAP_SUPPRESS_DISPLAY_LIMITATIONS | Set to 'yes' to suppress displaying any warnings about limitations for this data source. |
| Date Level | When Converted to Fiscal |
|---|---|
| Year | Reflects the fiscal year. For example, if Fiscal year start is set to April, the year for the date 1 June 2004 would be shown as FY 2005. |
| Quarter | The Quarter reflects the fiscal quarter. For example, if Fiscal year start is set to April, the quarter for the date 1 June 2004 would be Q1. |
| Month | No change in behaviour. The calendar month is the same as the fiscal month. |
| Day | No change in behaviour. The calendar day is the same as the fiscal day. |
| Hour | No change in behaviour. The calendar hour is the same as the fiscal hour. |
| Minute | No change in behaviour. The calendar minute is the same as the fiscal minute. |
| Second | No change in behaviour. The calendar second is the same as the fiscal second. |
| Week Number | The Week Number reflects the fiscal week number. For example, if Fiscal year start is set to April, the week number for the date 1 April 2004 would be 1. |
| Weekday | No change in behaviour. The calendar weekday is the same as the fiscal weekday. |
| MM/YYYY | No change in behaviour. This date format always displays calendar dates, even when a fiscal year has been assigned. |
| M/D/Y | This date format always displays Calendar dates, even when a fiscal year has been assigned. |
| Date part or truncation | When using a fiscal calendar |
| Year date part | Fiscal year start is set to April, the year for the date 1 June 2004 would be shown as FY 2005. |
| Quarter date part | Fiscal year start is set to April, the quarter for the date 1 June 2004 would be Q1. |
| Week Number date part | Fiscal year start is set to April, the week number for the date 1 April 2004 would be 1. |
| Year date truncation | Fiscal year start is set to May, the date 1 June 2004 would become 1 May 2004. |
| Quarter date truncation | Fiscal year start is set to July, the date 1 June 2004 would become 1 April 2004. |
| Value | Description | Example |
|---|---|---|
<TableauMode> | The mode Tableau is operating in when generating queries. This value will either be “Connect” when retrieving metadata or “Analytical” when retrieving actual data. | Connect or Analytical |
<LoginUser> | The user name of the person signed in to the database. | jsmith |
<ServerUser> | The signed-in Server user. Does not include domain name. Note: | jsmith |
<ServerUserFull> | The signed-in server user including the domain name (if the server is using Active Directory). Note: | domain.lan\jsmith |
<ProxyUser> | Used when setting up impersonation on the server. Provides the username of the current server user. | jsmith |
<ProxyUserFull> | Used when setting up impersonation on the server. Provides the username and domain name of the current server user. | domain.lan\jsmith |
<TableauApp> | The name of the Tableau application. | Tableau Desktop Professional or Tableau Server |
<TableauVersion> | The version of the Tableau application | 6100.11.0428.0300 |
<WorkbookName> | The name of the workbook. Note that this only works for data sources embedded in the workbook. | Financial-Analysis |
| Library | LibraryID | Consortium Member | Private | Librarians | Library Technicians | Library Assistants |
Idle Hour Library | L-IHL | Yes | No | 53 | 61 | 16 |
The Bibliophile’s Shelves | L-BS | Yes | Yes | 4 | 3 | 0 |
Armchair Athanaeum | L-AA | No | Yes | 6 | 0 | 0 |
| Old Friend Library | L-OFL | Yes | No | 3 | 5 | 17 |
| Bide Awhile | L-BA | Yes | No | 9 | 20 | 6 |
| IndieUnBound | L-IUB | Yes | No | 7 | 2 | 47 |
Page Station Book Exchange | L-PS | No | Yes | 3 | 1 | 4 |
| Logical Layer | Physical Layer | |
|---|---|---|
| Noodles = Relationships | Venn diagram = Joins | |
 |  | |
| The top-level view of a data source with multiple, related tables. This is the logical layer. Logical tables can be combined using relationships (noodles). They don't use join types. They act like containers for physical tables. | Double-click a logical table to open it and see its physical tables. Physical tables can be combined using joins or unions. In this example, the Book logical table is made of three, joined physical tables (Book, Award, Info). |
| Physical Layer Data Source | Logical Layer Data Source | |
|---|---|---|
 |  |
| Toolbar Button | Description |
|---|---|
 | Tableau icon: Navigates to the start page. For more information, see Start Page. Note: Tableau Desktop only. |
 | Undo: Reverses the most recent action in the workbook. You can undo an unlimited number of times, back to the last time you opened the workbook, even after you have saved. For more information, see Undo and Redo. |
 | Redo: Repeats the last action you reversed with the Undo button. You can redo an unlimited number of times. |
 | Save: In Tableau Desktop, saves the changes made to the workbook. For more information, see Save Your Work. In Tableau Server or Tableau Cloud, click File > Save or File > Save As to save your changes. |
 | New Data Source: In Tableau Desktop, opens the Connect pane, where you can create a new connection or open a saved connection. For more information, see Connect to Your Data. In Tableau Server or Tableau Cloud, open the Connect to a Data Source page, where you can connect to a published data source. For more information, see Connect to published data sources while web authoring. |
| Pause Auto Updates: Controls whether Tableau updates the view when changes are made. Use the drop-down menu to automatically update the entire sheet or just use filters. For more information, see Refresh Data or Pause Automatic Updates. |
| Run Update: Runs a manual query of the data to update the view with changes when automatic updates are turned off. Use the drop-down menu to update the entire worksheet or just use filters. Note: Tableau Desktop only. |
| New Worksheet: Creates a new blank worksheet, use the drop-down menu to create a new worksheet, dashboard or story. For more information, see Create new worksheets, dashboards, or stories. |
| Duplicate: Creates a new worksheet containing the same view as the current sheet. For more information, see Duplicate a sheet. |
| Clear: Clears the current worksheet. Use the drop-down menu to clear specific parts of the view such as filters, formatting, sizing and axis ranges. |
 | Swap: Moves the fields on the Rows shelf to the Columns shelf and vice versa. The Hide Empty Rows and Hide Empty Columns settings are always swapped with this button. |
 | Sort Ascending: Applies a sort in ascending order of a selected field based on the measures in the view. For more information, see Sort Data in a Visualisation. |
 | Sort Descending: Applies a sort in descending order of a selected field based on the measures in the view. For more information, see Sort Data in a Visualisation. |
 | Totals: You can compute grand totals and subtotals for the data in a view. Select from the following options:
Note: Tableau Server and Tableau Cloud only. In Tableau Desktop, click Analysis > Totals. For more information, see Show Totals in a Visualisation. |
| Highlight: Turn on highlighting for the selected sheet. Use the options on the drop-down menu to define how values are highlighted. For more information, see Highlight Toolbar Button. |
 | Group Members: Creates a group by combining selected values. When multiple dimensions are selected, use the drop-down menu to specify whether to group on a specific dimension or across all dimensions. For more information, see Correct Data Errors or Combine Dimension Members by Grouping Your Data. Note: Tableau Desktop only. In Tableau Server and Tableau Cloud, create groups using the Group Members button on the tooltip. |
| Show Mark Labels: Switches between showing and hiding mark labels for the current sheet. For more information, see Show, Hide and Format Mark Labels. |
 | Fix Axes: switches between a locked axis that only shows a specific range and a dynamic axis that adjusts the range based on the minimum and maximum values in the view. For more information, see Edit Axes. Note: Tableau Desktop only. |
 | Format Workbook: Open the Format Workbook pane to change how fonts and titles look in every view in a workbook by specifying format settings at the workbook level instead of at the worksheet level. Note: Tableau Server and Tableau Cloud only. In Tableau Desktop, click Format > Workbook. For more information, see Format at the Workbook Level. |
| Fit: Specifies how the view should be sized within the window. Select Standard, Fit Width, Fit Height or Entire View. Note: This menu is not available in geographic map views. The Cell Size commands have different effects depending on the type of visualisation. To access the Cell Size menu in Tableau Desktop click Format > Cell Size. |
 | Show/Hide Cards: Shows and hides specific cards in a worksheet. Select each card that you want to hide or show on the drop-down menu. In Tableau Server and Tableau Cloud, you can show and hide cards for the Title, Caption, Filter and Highlighter only. |
| Presentation Mode: Switches between showing and hiding everything except the view (i.e., shelves, toolbar, Data pane). For more information, see Reorganising the Workspace. Note: Tableau Desktop only. |
 | Download: Use the options under Download to capture parts of your view for use in other applications.
Note: Tableau Server and Tableau Cloud only. |
 | Share Workbook With Others: Publish your workbook to Tableau Server or Tableau Cloud. For more information, see Simple Steps to Publish a Workbook. Note: Tableau Desktop only. |
 | Show Me: Helps you choose a view type by highlighting view types that work best with the field types in your data. An orange outline shows around the recommended chart type that is the best match for your data. For more information, see Use Show Me to Start a View. |
| Warning Icon | Description |
|---|---|
 | Cancel query indicator: When you cancel multiple queries, an indicator appears to show you how many queries are still running on the database and using resources. When you cancel a query in Tableau, the database is told to stop processing the query. However, some databases do not support cancel (MS Excel, MS Access, Essbase, Microsoft Analysis Services 2000). If you cancel a query using one of these types of data sources, the query is abandoned by Tableau but is still running in the background and using resources. When you have abandoned queries, an indicator appears in the bottom right corner of the workbook showing the number of queries still running Note: Text, Microsoft Excel and Microsoft Access data sources may be temporarily unavailable after cancelling a query because of a lock performed internally. You may have to wait until the abandoned query has completed before re-connecting. |
 | Precision warning: Some fields are more precise in the database than Tableau can model. When you add a field to a view that contains values with more precision than Tableau can model, a warning icon For example, a value in the database may have 22 decimal places but Tableau only supports up to 15. When you add that field to the view, you get a precision warning. If you click on the warning, you can read more details including the number of decimal places that have been truncated in the view. Remember that the precision of the data displayed in Tableau will always first be dependent on the data in your database. If the values in your database exceed 15 decimal places, when you add them to the view, the value is truncated and a precision warning appears. Note: Extracts of relational databases always use the Hyper double precision type, and never use the Hyper numeric type. So if you create an extract of a relational database, you only get 15 digits of precision. You can write to the Hyper API and use the numeric type to get up to 18 digits. For related information, see Numeric Types in Hyper API documentation. |
 | Special values indicator: If your data contains null values, unknown geographic locations or negative or zero values on a logarithmic axis; the values are shown with an indicator in the lower right corner of the view. Click the indicator for options for handling these values. See Handling Null and Other Special Values to learn more about this indicator and how to handle these values. |
| Deepest | Specifies that the calculation should be performed at the level of finest granularity. This is the default option. |
| Quarter of Order Date | Specifies that the calculation should be performed at the quarter level. |
| Month of Order Date | Specifies that the calculation should be performed at the month level.
|
Primary data source  | Secondary data source  |
Table 1
| Table 2
|
| Employee ID | Name | Salary | Department | Hire Date | Organisation |
| 20107 | Wilson, Henry | 61,000 | Support | 28/07/2015 | Operations |
| 20107 | Wilson, Henry | 61,000 | Sales | 25/08/2016 | Operations |
| Error Message | Comments |
| Unsupported type passed as an argument to SCRIPT function. | Tableau can only export the following Tableau data types to R:
|
| Unexpected number of results returned by SCRIPT function. Function expected %2 values; %1 values were returned. | The script result must be either a scalar or vector of length one that is replicated for all rows, or a vector of length equal to the number of rows in the Tableau result table. |
| Certificate file is not valid for the specified connection (%1 %2:%3). Check that the same certificate is used for both server and client, the certificate file is not corrupted and has valid dates. | Verify that the certificate you are using to connect to the external service is encoded and formatted correctly. You must connect with a valid PEM-encoded x509 certificate with the extension .crt. |
| The result returned by the SCRIPT function is of an unexpected type. | Occurs when an invalid data type is received. Tableau can only import the following data types from an Rserve server:
For TabPy, Tableau can import the following data types:
This error is also reported if the result is null or if there was a script execution error for which Tableau could not collect an explanation from the external server. |
| An error occurred while communicating with the external service. | Tableau runs all external scripts inside of the "try" external function. This error is displayed along with an external-service-generated error message when the “try” function traps an evaluation error. |
| This external service connection does not support authentication. Try connecting without specifying a password. | |
| Authentication failed. Please provide a valid external service username and password. | |
| An unsupported authentication type is enabled in the external service. | Either disable external service authentication or change to plaintext password authentication. |
| No external service connection configured. Specify a server name and try again. | See Pass Expressions with Analytics Extensions. |
| The calculation '%1' contains a SCRIPT_ function that requires an internal service connection. Configure your external service connection to enable custom scripts. | See Pass Expressions with Analytics Extensions. |
| The workbook you are attempting to publish contains SCRIPT_ functions that require an external service connection. Custom scripts are not allowed in public workbooks. | You cannot publish workbooks containing external service scripts to Tableau Public. |
| Tableau Public does not support running custom scripts that require external services. To take advantage of external services, upgrade to Tableau Desktop Professional Edition. | The "Tableau Public" in this error refers to Tableau Desktop Public. |
| Tableau Reader does not support running custom scripts that require external services. To take advantage of external services, upgrade to Tableau Desktop Professional Edition. | You cannot view workbooks containing external service scripts in Tableau Reader. |
| Error Message | Comments |
| Unrecognised Rserve signature. | The Rserve header signature must be "Rsrv". |
| Unrecognised Rserve version. | The Rserve header version must be "0103". |
| Unrecognised Rserve protocol. | The Rserve header protocol must be "QAP1". |
| Authentication failure when connecting to R. | Tableau attempted and failed to authenticate with Rserve. Verify that you entered a valid password. |
| Incorrect number of bytes in parameter/body. | |
| The length of data which Tableau read does not equal the length promised by the header. | |
| Unrecognised response type. | The transport protocol type when reading a result was not SEXP as expected. |
| Excessively long <type>vector. | Unreasonably large number measuring the length of data sent to or from Rserve possibly indicating a corrupt protocol header. |
| Invalid Rserve command. | Tableau may have improperly implemented the Rserve protocol. |
Response from server was Error << (uint32_t)status << . See Rsrv.h for details. | Various error conditions are documented in the comments in Rsrv.h. |
| Excessively long header offset. | This may be due to a garbled header with an unreasonable offset to response data. |
| Rserve socket failed. | A login, script evaluation, read pending check, result read, or Tableau field to R script argument assignment threw a non-standard exception. |
| The external service uses an unsupported authentication type. | To support running both SSL-enabled and plaintext connections to an Rserve instance, the Rserve Server administrator must add the following entry to the Rserve configuration file on the Rserve Server:
|
| A crypto-system error has occurred on RServe. | An error has occurred with RServe’s encryption system. Check the RServe logs for more details. |
| RServe has initiated closing due to a security violation. | RServe closed the connection due to a security violation. Check the RServe logs for more details. |
| The External Service Configuration is set for a secure connection but missing a certificate. | When establishing a secure connection to an External Service, you are required to upload the certificate with which you expect this External Service to be signed. Connections to servers that are not signed by this certificate will be refused. This ensures that you are only sending your data to trusted servers. |
| Certificate file is not valid for the specified connection (%1 %2:%3). Check that the same certificate is used for both server and client, the certificate file is not corrupted and has valid dates | The certificate provided is not valid for this connection configuration. Check to see that it matches the certificate signing the External Service server, that it is PEM encoded, and that it is valid for today’s date. |
| External service connection certificate is invalid | The certificate provided is invalid. Check to see that the certificate is PEM encoded, and that it is valid for today’s date. |
| External service connection failed to create SSL/TLS context | Tableau failed to initialise a secure environment for this given External Service configuration. Check to see that the host and port are correct, and that the certificate is valid. |
| External service failed to connect with SSL/TLS | Tableau failed to establish a secure connection to the External Service. Verify that the External Service is configured to support secure connection, and that the certificate provided matches the one signing the External Service. |
| External service server protocol is unrecognised | A protocol was prepended to the host that is not recognised or supported by Tableau. If connecting to RServe, no protocol is expected. If connecting to TabPy, the HTTP protocol is expected when establishing a plaintext connection, and the HTTPS protocol is expected when establishing a secure connection. |
| Syntax | DATE(expression) |
| Output | Date |
| Definition | Returns a date, given a number, string or date expression. |
| Example | DATE([Employee Start Date]) DATE("September 22, 2018") DATE("9/22/2018")DATE(#2018-09-22 14:52#) |
| Notes | Unlike DATEPARSE, there is no need to provide a pattern as DATE automatically recognises many standard date formats. If DATE does not recognise the input, however, try using DATEPARSE and specifying the format. MAKEDATE is another similar function, but MAKEDATE requires the input of numeric values for year, month and day. |
| Syntax | DATETIME(expression) |
| Output | Datetime |
| Definition | Returns a datetime given a number, string or date expression. |
| Example | DATETIME("April 15, 2005 07:59:00") = April 15, 2005 07:59:00 |
| Syntax | FLOAT(expression) |
| Output | Floating point number (decimal) |
| Definition | Casts its argument as a floating point number. |
| Example | FLOAT(3) = 3.000 |
| Notes | See also INT, which returns an integer. |
| Syntax | INT(expression) |
| Output | Integer |
| Definition | Casts its argument as an integer. For expressions, this function truncates results to the closest integer toward zero. |
| Example | INT(8/3) = 2 INT(-9.7) = -9 |
| Notes | When a string is converted to an integer it is first converted to a float and then rounded. See also FLOAT, which returns a decimal. |
| Syntax | MAKEDATE(year, month, day) |
| Output | Date |
| Definition | Returns a date value constructed from the specified numerical year, month and date. |
| Example | MAKEDATE(1986,3,25) = #1986-03-25# Note that incorrectly entered values will be adjusted into a date, such as MAKEDATE(2020,4,31) = May 1, 2020 rather than returning an error that there is no 31st day of April. |
| Notes | Available for Tableau Data Extracts. Check for availability in other data sources. MAKEDATE requires numerical inputs for the parts of a date. If your data is a string that should be a date, try the DATE function. DATE automatically recognises many standard date formats. If DATE does not recognise the input try using DATEPARSE. |
| Syntax | MAKEDATETIME(date, time) |
| Output | Datetime |
| Definition | 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. |
| Example | MAKEDATETIME("1899-12-30", #07:59:00#) = #12/30/1899 7:59:00 AM#MAKEDATETIME([Date], [Time]) = #1/1/2001 6:00:00 AM# |
| Notes | This function is available only for MySQL-compatible connections (which for Tableau are MySQL and Amazon Aurora). MAKETIME is a similar function available for Tableau Data Extracts and some other data sources. |
| Syntax | MAKELINE(<Spatial Point1>,<Spatial Point2>) |
| Output | Geometry spatial object (line) |
| Definition | Generates a line mark between two points. |
| Example | MAKELINE(OriginPoint, DestinationPoint) MAKELINE( MAKEPOINT(OriginLat],[OriginLong]) , MAKEPOINT([DestinationLat],[DestinationLong] ) |
| Notes | Useful for building origin-destination maps or, with MAKEPOINT, turning latitude and longitude into spatial objects. |
| Syntax | MAKEPOINT(<latitude>, <longitude>) |
| Output | Geometry spatial object (point) |
| Definition | Converts data from latitude and longitude columns into spatial objects. |
| Example | MAKEPOINT([AirportLatitude],[AirportLongitude]) |
| Notes | You can use MAKEPOINT to spatially-enable a data source so that it can be joined with a spatial file using a spatial join. For more information, see Join Spatial Files in Tableau. To use MAKEPOINT, your data must contain latitude and longitude coordinates. |
| Syntax | MAKETIME(hour, minute, second) |
| Output | Datetime. See Notes. |
| Definition | Returns a date value constructed from the specified hour, minute and second. |
| Example | MAKETIME(14, 52, 40) = #1/1/1899 14:52:40# |
| Notes | Because Tableau does not support a time data type, only datetime, the output is a datetime. The date portion of the field will be 1/1/1899. Similar function to MAKEDATETIME, which is only available for MYSQL-compatible connections. |
| Syntax | STR(expression) |
| Output | String |
| Definition | Casts its argument as a string. |
| Example | STR([ID]) |
| Book ID | Book Name | Series | Year Released | Author |
| 1 | The Lion, the Witch and the Wardrobe | The Chronicles of Narnia | 1950 | C.S. Lewis |
| 2 | Prince Caspian: The Return to Narnia | The Chronicles of Narnia | 1951 | C.S. Lewis |
| 3 | The Voyage of the Dawn Treader | The Chronicles of Narnia | 1952 | C.S. Lewis |
| 4 | The Silver Chair | The Chronicles of Narnia | 1953 | C.S. Lewis |
| 5 | The Horse and His Boy | The Chronicles of Narnia | 1954 | C.S. Lewis |
| 6 | The Magician's Nephew | The Chronicles of Narnia | 1955 | C.S. Lewis |
| 7 | The Last Battle | The Chronicles of Narnia | 1956 | C.S. Lewis |
| 8 | Daughter of the Forest | Sevenwaters | 1999 | Juliet Marillier |
| 9 | Son of the Shadows | Sevenwaters | 2000 | Juliet Marillier |
| 10 | Child of the Prophecy | Sevenwaters | 2001 | Juliet Marillier |
| 11 | Heir of Sevenwaters | Sevenwaters | 2008 | Juliet Marillier |
| 12 | Seer of Sevenwaters | Sevenwaters | 2010 | Juliet Marillier |
| 13 | Flame of Sevenwaters | Sevenwaters | 2012 | Juliet Marillier |
| Book ID | Book Name | Series | Year Released | Author | Author Last Name |
| 1 | The Lion, the Witch and the Wardrobe | The Chronicles of Narnia | 1950 | C.S. Lewis | Lewis |
| 2 | Prince Caspian: The Return to Narnia | The Chronicles of Narnia | 1951 | C.S. Lewis | Lewis |
| 3 | The Voyage of the Dawn Treader | The Chronicles of Narnia | 1952 | C.S. Lewis | Lewis |
| 4 | The Silver Chair | The Chronicles of Narnia | 1953 | C.S. Lewis | Lewis |
| 5 | The Horse and His Boy | The Chronicles of Narnia | 1954 | C.S. Lewis | Lewis |
| 6 | The Magician's Nephew | The Chronicles of Narnia | 1955 | C.S. Lewis | Lewis |
| 7 | The Last Battle | The Chronicles of Narnia | 1956 | C.S. Lewis | Lewis |
| 8 | Daughter of the Forest | Sevenwaters | 1999 | Juliet Marillier | Marillier |
| 9 | Son of the Shadows | Sevenwaters | 2000 | Juliet Marillier | Marillier |
| 10 | Child of the Prophecy | Sevenwaters | 2001 | Juliet Marillier | Marillier |
| 11 | Heir of Sevenwaters | Sevenwaters | 2008 | Juliet Marillier | Marillier |
| 12 | Seer of Sevenwaters | Sevenwaters | 2010 | Juliet Marillier | Marillier |
| 13 | Flame of Sevenwaters | Sevenwaters | 2012 | Juliet Marillier | Marillier |
| Series | Number of Books in Series – at Series level of detail |
| The Chronicles of Narnia | 7 |
| The Chronicles of Narnia | |
| The Chronicles of Narnia | |
| The Chronicles of Narnia | |
| The Chronicles of Narnia | |
| The Chronicles of Narnia | |
| The Chronicles of Narnia | |
| Sevenwaters | 6 |
| Sevenwaters | |
| Sevenwaters | |
| Sevenwaters | |
| Sevenwaters | |
| Sevenwaters |
| Book ID | Book Name | Series | Year Released | Author | Series Launched |
| 1 | The Lion, the Witch and the Wardrobe | The Chronicles of Narnia | 1950 | C.S. Lewis | 1950 |
| 2 | Prince Caspian: The Return to Narnia | The Chronicles of Narnia | 1951 | C.S. Lewis | 1950 |
| 3 | The Voyage of the Dawn Treader | The Chronicles of Narnia | 1952 | C.S. Lewis | 1950 |
| 4 | The Silver Chair | The Chronicles of Narnia | 1953 | C.S. Lewis | 1950 |
| 5 | The Horse and His Boy | The Chronicles of Narnia | 1954 | C.S. Lewis | 1950 |
| 6 | The Magician's Nephew | The Chronicles of Narnia | 1955 | C.S. Lewis | 1950 |
| 7 | The Last Battle | The Chronicles of Narnia | 1956 | C.S. Lewis | 1950 |
| 8 | Daughter of the Forest | Sevenwaters | 1999 | Juliet Marillier | 1999 |
| 9 | Son of the Shadows | Sevenwaters | 2000 | Juliet Marillier | 1999 |
| 10 | Child of the Prophecy | Sevenwaters | 2001 | Juliet Marillier | 1999 |
| 11 | Heir of Sevenwaters | Sevenwaters | 2008 | Juliet Marillier | 1999 |
| 12 | Seer of Sevenwaters | Sevenwaters | 2010 | Juliet Marillier | 1999 |
| 13 | Flame of Sevenwaters | Sevenwaters | 2012 | Juliet Marillier | 1999 |
| Book ID | Book Name | Series | Year Released | Author | Years Since Previous Book | ||
| 1 | The Lion, the Witch and the Wardrobe | The Chronicles of Narnia | 1950 | C.S. Lewis | NULL | ||
| 2 | Prince Caspian: The Return to Narnia | The Chronicles of Narnia | 1951 | C.S. Lewis | 1951- | 1950 | 1 |
| 3 | The Voyage of the Dawn Treader | The Chronicles of Narnia | 1952 | C.S. Lewis | 1952- | 1951 | 1 |
| 4 | The Silver Chair | The Chronicles of Narnia | 1953 | C.S. Lewis | 1953- | 1952 | 1 |
| 5 | The Horse and His Boy | The Chronicles of Narnia | 1954 | C.S. Lewis | 1954- | 1953 | 1 |
| 6 | The Magician's Nephew | The Chronicles of Narnia | 1955 | C.S. Lewis | 1955- | 1954 | 1 |
| 7 | The Last Battle | The Chronicles of Narnia | 1956 | C.S. Lewis | 1956- | 1955 | 1 |
| 8 | Daughter of the Forest | Sevenwaters | 1999 | Juliet Marillier | NULL | ||
| 9 | Son of the Shadows | Sevenwaters | 2000 | Juliet Marillier | 2000- | 1999 | 1 |
| 10 | Child of the Prophecy | Sevenwaters | 2001 | Juliet Marillier | 2001- | 2000 | 1 |
| 11 | Heir of Sevenwaters | Sevenwaters | 2008 | Juliet Marillier | 2008- | 2001 | 7 |
| 12 | Seer of Sevenwaters | Sevenwaters | 2010 | Juliet Marillier | 2010- | 2008 | 2 |
| 13 | Flame of Sevenwaters | Sevenwaters | 2012 | Juliet Marillier | 2012- | 2010 | 2 |
| Language | Keywords |
| English (UK and US) | Year, Yr, Day, Day of Week, Week, Wk, Month, Quarter, Qtr, FY |
| Chinese (Simplified) | 年, 天, 周中某天, 周, 月, 季度, 会计年度 |
| Chinese (Traditional) | 年, 天, 週中某天, 週, 月, 季, 會計年度 |
| Dutch | Jaar, Jr, Dag, Dag Van De Week, Week, Wk, Maand, Kwartaal, Q, |
| French (Canada and France) | Année, Jour, Jour de la Semaine, Semaine, Mois, Trimestre, AF |
| German | Jahr, Tag, Wochentag, Woche, Monat, Quartal, GJ |
| Italian | Anno, Giorno, Giorno della Settimana, Settimana, Sett, Mese, Trimestre, Trim, AF |
| Japanese | 年, 日, 曜日, 週, 月, 四半期, 年度 |
| Korean | 년, 일, 요일, 주, 월, 분기, 회계 연도 |
| Portuguese | Ano, Dia, Dia da Semana, Semana, Mês, Trimestre, AF |
| Spanish | Año, Día, Día de la Semana, Semana, Mes, Trimestre, AF |
| Swedish | År, Dag, Veckodag, Vecka, Månad, Kvartal, Räkenskapsåret |
| Thai | ปี, วัน, วันของสัปดาห์, สัปดาห์, เดือน, ไตรมาส, FY |
| CIF | FDA | MPI |
| DMA | FOB | MSA |
| DOB | FTE | SKU |
| EIN | KPI | UPC |
| ESP | LOB | URL |
| USD |
| 1st | as | down | of | th (suffix following a number) |
| 2nd | at | for | on | than |
| 3rd | but | in | off | the |
| a | by | inclu. | or | to |
| an | de | into | over | vs |
| and | da | la | per | with |
Classes | Clubs | Students | Rooms |
 |  |  |  |
Fields:
| Fields:
| Fields:
| Fields:
|
Unrelated: Cross join | Stitched: Outer join of intermediate inner joins |
 A viz showing a cross join of Class and Club with rows for every combination of Advanced Songs/Alarm Calls 101/Flying for Fledglings/Nesting Basics with Art/First Aid/Juggling/Photography. |  A viz showing the results of an outer join of the Student-Class inner join and the Student-Club inner join. Not all combinations of classes and clubs are represented, and there are rows for students and clubs without a class. |
May2016
| June2016
| July2016
|
August2016
|
Union (with null values)
|
| Union (with columns that have been merged)
|
| Your Data | Legacy Connection | Default Connection |
|---|---|---|
| File name length | Does not allow connections to a file whose file name is more than 64 characters long. | No length constraints for file names. |
| Multiple period in the file name | Does not allow connections to a file whose file name contains multiple periods. | No period constraints for file names. |
| Number of columns in the file | Uses the number of fields present in the first row to determine the number of columns in the file. | Scans the entire file and uses the most common number of fields in a row to determine the number of columns in the file. |
| Headers rows | Does not automatically detect whether the first row in the file is a header. Note: You can manually specify that the first row in the file is a header. | Automatically detects whether the first row in the file is a header. Note: You can manually override the detection. |
| Empty columns | Empty columns are visible. | Empty columns are hidden because they do not contain any values. |
| Your Data | Legacy Connection | Default Connection |
|---|---|---|
| Number of characters in the field name | Field names are truncated to 64 characters. | No constraint on the number of characters in a field name. |
| Special characters in field names | Special characters are not allowed in field names. For example, special characters like quotation marks and periods are converted to number signs. Brackets are converted to parentheses. | Special characters are allowed in field names. |
| Leading and trailing spaces in field names | Leading and trailing spaces in field names are allowed. | Leading and trailing spaces in field names are automatically removed from column names. |
| Duplicate field names | For duplicate field names, an index number is appended onto the field name. For example, Test Scores1. | For duplicate field names, a space and an index number are appended to the field name. For example, Test Scores 1. |
| Excel cell formatting | Supports cell formatting configured using the Format Cells option in Excel. | Does not support cell formatting configured using the Format Cells option in Excel. |
| Precision with currency values | Fields that contain currency values are represented with a maximum precision of four digits | Full precision of currency values is represented. |
| Your Data | Legacy Connection | Default Connection |
|---|---|---|
| Special characters in file names | Special characters are not allowed in file names. For example, special characters like periods are converted to number signs. | Special characters are allowed. |
| Characters in header field names | Automatically removes leading spaces from header field names. | Automatically removes leading and trailing spaces from header field names. |
| Field separators | Recognises only commas as field separators. Note: You can manually override the detection. | Automatically detects the field separator. Note: You can manually override the detection. |
| Text enclosed with quotation marks | Quotation marks used to enclose text values remain visible. | Quotation marks used to enclose text values are automatically hidden. |
| ANSI and OEM code pages | ANSI and OEM code pages are supported. | ANSI an OEM code pages are automatically converted to be cross-platform compatible. |
| BOM code pages | Inconsistently supports BOM code pages. | Supports BOM code pages. |
| Data Type Detection | Legacy Connection | Default Connection |
|---|---|---|
| Columns | Data type of a column is determined by the first 8 rows.
Note: After the data type of a column in the table has been determined, it cannot be changed. | Data type of a column is determined by the 95% of the first 10000 rows.
Note: You can manually override the detection. |
| Date values without time | Date values are assigned a datetime data type. | Date values without time are assigned a date data type. Date values with time are assigned a datetime data type. |
| Number values | All number values are represented as real numbers. | Number values without decimal points are represented as integers. |
| Null values | If a column contains a null cell, the data type for the column is automatically designated as a string data type. | Null cells do not affect data type detection. |
| Reference errors or empty cells | If a column contains cells with reference errors or empty cells, the entire column is interpreted as a string data type. | Reference errors or cells with no values do not affect the data type detection. |
| Overriding data type detection | After the data type of a column in the table has been determined, it cannot be changed. | Data type of a column can be changed after the automatic detection. |
| Time value precision | The smallest measurement of time values is whole seconds. | The smallest measurement of time values is fractional seconds. |
| DecimalSymbol and CurrencyDecimalSymbol schema.ini values | Both DecimalSymbol and CurrencyDecimalSymbol schema.ini values are recognised. | DecimalSymbol and CurrencyDecimalSymbol scheam.ini values are recognised. However if both values are used, DecimalSymbol takes precedence. |
| Cells formatted as text | The data type of a column is detected as a string data type when cells are formatted as text using the Format Cells option in Excel. | Does not support cell formatting configured using the Format Cells option in Excel. |
| If you choose this option... | The action is run when the user... |
|---|---|
| Hover | Mouses over a mark in the view. This option works best for highlight actions within a dashboard. |
| Select | Clicks a mark in the view. This option works well for all types of actions. |
| Menu | Right-clicks (control-clicks on Mac) a selected mark in the view, then clicks an option in a tooltip (menu). This option works particularly well for URL actions. |
| Publishing a custom font work flow
then
|
If | Then |
A- The workbook is created in Tableau Desktop. | You can use any font installed on your computer in the workbook. |
B- The workbook is created using Web Authoring. | Only fonts installed on the Tableau Server or Tableau Cloud are functional when formatting your text. |
C- The workbook is published to Tableau Server. | Any custom font must be installed on all server nodes. If the font is not installed on Tableau Server, the uninstall font will be replaced with a substitute font upon publishing. |
D- The workbook is published to Tableau Cloud. | Only fonts supported by Tableau Cloud will appear. Any unsupported fonts in the workbook will be replaced with a substitute font upon publishing. For a list of supported fonts, see Knowledge Base: Fonts not displaying as expected. |
Issue | Possible Solution |
|---|---|
Some fonts are accurate in the view, but others are not. | When a view has many marks, the server will render the marks on the server side and display the marks as a static image. This can result in some fonts in the view appearing inconsistent with the rest of the view. To resolve this issue, reduce the number of marks per view. |
The spacing on the font appears different for different viewers. | If the viewer has the custom font installed on their computer, the viewer will see the font displayed accurately. However, each browser uses a slightly different method for rendering fonts, so seeing slight differences in fonts between browsers is expected. |
A different font appears for viewers. | If the viewer does not have the custom font installed on their computer, any uninstalled fonts in the workbook will be replaced with a substitute font selected by the browser. |
| Style Element | Description | Style Attributes | Input Type | Formatting Choice |
|---|---|---|---|---|
| all | Formats all fonts across the entire workbook. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| worksheet | Formats the worksheet default font. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| worksheet-title | Formats the worksheet title font. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| tooltip | Formats the tooltip font. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| dashboard-title | Formats the dashboard title. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| font-weight | String | String specified as normal or bold. | ||
| story-title | Formats the story title font. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| header | Formats the header font. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| legend | Formats the legend body font and background colour. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| background-color | String | String that follows the format of a hex colour code, such as #FF0000. This element also supports two additional digits for transparency, such as #FF000080. | ||
| legend-title | Formats the legend title font on all worksheets. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| filter | Formats the filter body font and background colour on all worksheets. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| background-color | String | String that follows the format of a hex colour code, such as #FF0000. This element also supports two additional digits for transparency, such as #FF000080. | ||
| filter-title | Formats the filter title font on all worksheets. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| parameter-ctrl | Formats the parameter body font and background colour on all worksheets. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| background-color | String | String that follows the format of a hex colour code, such as #FF0000. This element also supports two additional digits for transparency, such as #FF000080. | ||
| parameter-ctrl-title | Formats the parameter control title font on all worksheets. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| highlighter | Formats the highlighter body font and background colour on all worksheets. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| background-color | String | String that follows the format of a hex colour code, such as #FF0000. This element also supports two additional digits for transparency, such as #FF000080. | ||
| Highlighter-title | Formats the highlighter control title font on all worksheets. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| font-size | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| page-ctrl-title | Formats the page card title font on all worksheets. | font-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| font-family | String | String with a maximum length of 50 characters. | ||
| gridline | Formats the gridlines on a view. | line-visibility | String | String specified as on or off. |
| line-pattern | String | String specified as dotted, dashed or solid. | ||
| line-width | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| line-color | String | String that follows the format of a hex colour code, such as #FF0000. This element also supports two additional digits for transparency, such as #FF000080. | ||
| zeroline | Formats the zeroline on a view. | line-visibility | String | String specified as on or off. |
| line-pattern | String | String specified as dotted, dashed or solid. | ||
| line-width | Integer | Integer with a minimum value of 1 and a maximum value of 99. | ||
| line-color | String | String that follows the format of a hex colour code, such as #FF0000. This element also supports two additional digits for transparency, such as #FF000080. | ||
| mark | Formats the mark colour on a view. | mark-color | String | String that follows the format of a hex colour code, such as #FF0000. |
| view | Formats the background colour on a view. | String | String that follows the format of a hex colour code, such as #FF0000. |
Get startedWhat Can I Do with a Tableau Site? | Explore and manage contentExplore and Inspect Data in a View |
Author web viewsWeb Authoring and Tableau Desktop Feature Comparison Creators: Connect to Data on the Web Upload Workbooks to a Tableau Site | Share and collaborateCreate a Subscription to a View or Workbook Send Data-Driven Alerts from Tableau Cloud or Tableau Server |
Supported SRS/EPSG Codes in Tableau: |
3857 - WGS 84 / Pseudo-Mercator [DEFAULT] 4326 - WGS 84 4269 - NAD83 3824 - TWD97 3889 - IGRS 4019 - Unknown datum based on the GRS 80 ellipsoid 4023 - MOLDREF99 4030 - Unknown datum based upon the WGS 84 ellipsoid 4031 - Unknown datum based upon the GEM 10C ellipsoid 4046 - RGRDC 2005 4075 - SREF98 4081 - REGCAN95 4126 - LKS94 (ETRS89) 4130 - Moznet 4140 - NAD83(CSRS98) 4148 - Hartebeesthoek94 4151 - CHTRF95 4152 - NAD83(HARN) 4163 - Yemen NGN96 4166 - Korean 1995 4167 - NZGD2000 4170 - SIRGAS 1995 4171 - RGF93 4172 - POSGAR 4173 - IRENET95 4176 - Australian Antarctic 4180 - EST97 4189 - REGVEN 4190 - POSGAR 98 4258 - ETRS89 4283 - GDA94 4319 - KUDAMS 4612 - JGD2000 4617 - NAD83(CSRS) 4619 - SWEREF99 4627 - RGR92 4640 - RRAF 1991 4645 - RGNC 1991 4659 - ISN93 4661 - LKS92 4667 - IKBD-92 4669 - LKS94 4670 - IGM95 4674 - SIRGAS 2000 4686 - MAGNA-SIRGAS 4687 - RGPF 4693 - Nakhl-e Ghanem 4694 - POSGAR 94 4702 - Mauritania 1999 4737 - Korea 2000 4742 - GDM2000 4747 - GR96 4749 - RGNC91-93 4755 - DGN95 4756 - VN-2000 4757 - SVY21 4758 - JAD2001 4759 - NAD83(NSRS2007) 4761 - HTRS96 4762 - BDA2000 4763 - Pitcairn 2006 4764 - RSRGD2000 4765 - Slovenia 1996 102100 - WGS 84 Web Mercator (Auxiliary Sphere) |
| Syntax | FULLNAME( ) |
| Output | String |
| Definition | Returns the full name for the current user. |
| Example | FULLNAME( ) This returns the full name of the signed-in user, such as "Hamlin Myrer". [Manager] = FULLNAME( ) If manager "Hamlin Myrer" is signed in, this example returns TRUE only if the Manager field in the view contains "Hamlin Myrer". |
| Notes | This function checks:
User filters When used as a filter, a calculated field such as |
| Syntax | ISFULLNAME("User Full Name") |
| Output | Boolean |
| Definition | Returns |
| Example | ISFULLNAME("Hamlin Myrer") |
| Notes | The This function checks:
|
| Syntax | ISMEMBEROF("Group Name") |
| Output | Boolean or null |
| Definition | Returns |
| Example | ISMEMBEROF('Superstars')ISMEMBEROF('domain.lan\Sales') |
| Notes | The If the user is signed in to Tableau Cloud or Tableau Server, group membership is determined by Tableau groups. The function will return TRUE if the given string is "All Users" The If a change is made to a user's group membership, the change in the data that is based on the group membership is reflected in a workbook or view with a new session. The existing session will reflect stale data. |
| Syntax | ISUSERNAME("username") |
| Output | Boolean |
| Definition | Returns TRUE if the current user's username matches the specified username or FALSE if it does not match. |
| Example | ISUSERNAME("hmyrer") |
| Notes | The This function checks:
|
| Syntax | USERDOMAIN( ) |
| Output | String |
| Definition | Returns the domain for the current user. |
| Notes | This function checks:
|
| Syntax | USERNAME( ) |
| Output | String |
| Definition | Returns the username for the current user. |
| Example | USERNAME( ) This returns the username of the signed-in user, such as "hmyrer". [Manager] = USERNAME( ) If manager "hmyrer" is signed in, this example returns TRUE only if the Manager field in the view contains "hmyrer". |
| Notes | This function checks:
User filters When used as a filter, a calculated field such as |
| Syntax | USERATTRIBUTE('attribute_name') |
| Output | String or null |
| Definition | If Returns null if |
| Example | Suppose ‘Region’ is the user attribute included in the JWT or SAML response and passed to Tableau. As the workbook author, you can set up your visualisation to filter data based on a specified region. In that filter, you can reference the following calculation. [Region] = USERATTRIBUTE("Region")When User2 from the West region views the embedded visualisation, Tableau shows the appropriate data for the West region only. |
| Notes | You can use the USERATTRIBUTEINCLUDES function if you expect <'attribute_name'> to return multiple values. |
| Syntax | USERATTRIBUTEINCLUDES('attribute_name', 'expected_value') |
| Output | Boolean |
| Definition | Returns
Returns |
| Example | Suppose ‘Region’ is the user attribute included in the JWT or SAML response and passed to Tableau. As the workbook author, you can set up your visualisation to filter data based on a specified region. In that filter, you can reference the following calculation. USERATTRIBUTEINCLUDES('Region', [Region])If User2 from the West region accesses the embedded visualisation, Tableau checks if the Region user attribute matches one of [Region] field values. When true, the visualisation shows the appropriate data. When User3 from the North region accesses the same visualisation, she’s unable to see any data because there’s no match with [Region] field values. |
| Calendar System | Week Number | Year Number |
| Standard Gregorian | 1 | 2011 |
| ISO-8601 | 52 | 2010 |
| Annotation | Calendar to Use | Example Format String |
| [Y] | ISO-8601 | ww[Y] yyyy[Y] |
| [y] | Standard Gregorian | ww[y] yyyy[y] |
| Format string | Formatted output |
| yyyy | 2013 |
| yyyy[Y] | 2014 |
| yyyy ww | 2014 1 |
| yyyy mm | 2013 12 |
| ww yyyy | 1 2014 |
| mm yyyy | 12 2013 |
| ww yyyy[y] | 1 2013 |
| mm yyyy[Y] | 12 2014 |
| yyyy mm ww | 2013 12 1 |
| mm yyyy ww | 12 2013 1 |
| ww mm yyyy | 1 12 2013 |
| ww mm yyyy[Y] | 1 12 2014 |
| ww yyyy mm | 1 2014 12 (format is ambiguous) |
| ww yyyy[y] mm | 1 2013 12 |
| ww yyyy mm yyyy | 1 2014 12 2013 |
| ww yyyy yyyy mm | 1 2014 2013 12 |
| yyyy mm ww yyyy | 2013 12 1 2014 |
| Context | Scope | How |
|---|---|---|
Worksheet: Selected Mark or Marks Tableau Cloud, Tableau Server, Tableau Desktop | In a worksheet, selecting one or more marks and then selecting View Data from the tooltip menu displays underlying data scoped to the individual mark or a group of marks. Note: The Include command buttons option must be selected for tooltips for the View Data button to be available. This view can be customised and downloaded. | Select one or more marks in the view, then select View Data from the tooltip menu.
|
Data Source page: Per Table Tableau Cloud, Tableau Server, Tableau Desktop | In the Data Source page, you can open View Data for each table listed in the data source (left pane). You can move and sort columns in this view, but you can't download the data. | Select View Data next to a table in the left pane of the Data Source page.
You can also display the View Data window for custom SQL by clicking Preview Results in the Custom SQL dialog box. |
Worksheet: Download button on toolbar Tableau Cloud and Tableau Server | In a worksheet (viewing or editing mode), selecting Data from the Download button menu displays all underlying data used in a viz. In a dashboard, underlying data can be viewed based on the selected worksheet. Select a sheet in the dashboard before you click the Download button to make the Data option available. This view can be customised and downloaded. | From the Download button menu, select Data.
|
Worksheet: Data pane Tableau Desktop only | In a worksheet, selecting View Data at the top of the Data pane displays tabular data for each field in the data source, listed by table. This view can be customised and downloaded. | In the Data pane, click the View Data button next to the Search field.
|
Worksheet: Analysis menu Tableau Desktop only | In a worksheet, selecting View Data from the Analysis menu displays all underlying data used in a viz. The corresponding table or tables for measures used in the viz are listed in the Tabs pane. This view can be customised and downloaded. | From the Analysis menu, select View Data. In vizzes that aren't text tables, you can also right-click on the view, then select View Data.
|
| Dashboard: Analysis menu Tableau Desktop only | On a dashboard, selecting View Data from the Analysis menu displays all underlying data used the currently selected sheet. If no sheet is currently active, the default sheet's data is shown. The corresponding table or tables for measures used in the viz are listed in the Tabs pane. This view can be customised and downloaded. | From the Analysis menu, select View Data.
Note the darker border around the sheet Order details, indicating it was selected in the dashboard, and the view data dialog shows it’s for Order details. |
| Option | How | Where |
|---|---|---|
Show or hide field columns | Click Show Fields and tick or untick a field name. To show all fields, select (All). Fields are added to the right of the currently displayed fields. |
|
Move field columns | Select one or more field columns and then click on the right or left arrows at the top of the window. Or, select the drop-down menu and click Move Right and Move Left. Tip: To group non-adjacent columns together, press Ctrl while selecting the columns, and then move the selected columns to the left or right. |
|
Remove field columns | Select a field column and then select Remove from the drop-down menu. Or, click Show Fields and untick the field to remove its column. |
|
Sort data | Hover near the top of a column to display the Sort button. Click the Sort button to change the sort. Optionally, click the drop-down menu and select Sort Ascending or Sort Descending Note: Customised sort results aren't included in downloaded data. |
|
Edit the maximum number of rows displayed | By default, the View Data window displays up to the first 10,000 rows of data in Tableau Desktop and up to the first 200 rows of data in Tableau Cloud and Tableau Server. You can increase or decrease the maximum number of rows displayed in the View Data window. This setting has no effect on the number of rows exported when you click the Download button. Click in the number of rows field to edit it. Click the arrow button or press Enter on your keyboard to apply the change. |
|
Show aliases | Click the Settings button to show or hide aliases for all field names. |
|
| Visual Cue | Description |
   | The workbook is directly connected to a relational data source or file. |
   | The workbook is connected to an extract that still references the underlying data. |
   | The workbook is connected to a cube (multidimensional) data source. In Tableau, cube data sources are supported only in Windows. |
 | The workbook is connected to an Excel table, sub-table or named range. |
 | The workbook is connected to a data source that has been published to Tableau Server. |
| Visual Cue | Field description |
  | Text or string values. |
 | Numeric values. |
 | Date values. |
| Date and time values. |
 | Boolean values (true or false). |
| Geographical data. This icon also indicates the field has been assigned a geographic role. Use these fields when building map views. See Maps and Geographic Data Analysis in Tableau. |
 | Geographical data from a custom geocoding file. See Geocode Locations Tableau Does Not Recognise and Plot Them on a Map. |
 | A URL set to Image Role. See Add Web Images Dynamically to Worksheets. |
  | A calculation defined by the data source. |
 | A user-defined set. See Create Sets. |
 | A server named set. |
 | A set that was automatically created as a result of an action. See Actions. |
 | A user filter for published content. See Restrict Access at the Data Row Level. |
 | A numeric bin. See Create Bins from a Continuous Measure. |
 | A group. See Correct Data Errors or Combine Dimension Members by Grouping Your Data. |
 | A cluster group. See Find Clusters in Data. |
  | A relational hierarchy. See Create Hierarchies. |
 | A level in a multidimensional hierarchy. Levels greater than five are shown without numbers. |
  | A folder that contains one or more fields. Folders are used to organise fields in the Data pane. See Organise the Data Pane. |
 | An attribute of a cube (multidimensional) data source. In Tableau, cube data sources are supported only in Windows. |
 | A varying attribute of a cube (multidimensional) data source. |
 | The field is an active link for data blending. See Blend Your Data. |
 | The field is a potential link for data blending. See Blend Your Data. |
 | The field is unrelated. See About Multi-fact Relationship Data Models. |
 | The field is a stitching field. See About Multi-fact Relationship Data Models. |
 | The field is hidden. Click to unhide the field. See Hide or Unhide Fields. |
| Visual Cue | Description |
 | A blue field on a shelf indicates a discrete field. In most cases, adding a dimension to a shelf results in a blue field. Blue fields are discrete – they contain a finite number of values. Adding a blue field to a shelf creates headers. For details, see Headers. |
 | A green field on a shelf indicates a continuous field. In most cases, adding a measure to a shelf results in a green field. Green fields are continuous – they contain an infinite number of values. Adding a green field to a shelf creates an axis. For details, see Axes. |
 | The Sort icon indicates a field that has either a computed or manual sort order applied. See Sort Data in a Visualisation. |
 | The sigma icon indicates a slicing filter in a multidimensional (cube) data source. See Create Slicing Filters. |
 | The Venn diagram icon indicates a set. See Create Sets. |
 | The unrelated icon indicates the field is unrelated to at least one other field in the viz. See Field-level relatedness indicators. |
 | The related icon indicates the dimension is stitching otherwise unrelated fields. See Field-level relatedness indicators. |
 | A field name shown in italics indicates the filter was generated and controlled by an action. |
 | A grey field on the Filters shelf indicates a context filter. See Use Context Filters. |
 | The delta icon indicates that the field is a table calculation. See Transform Values with Table Calculations. |
 | The plus and minus controls appear when the field is part of a hierarchy you can drill down or roll up. |
 | The arrow icon indicates that a forecast is being displayed for the field. This icon is also used on the Forecast Indicator field, which is an automatic field used to distinguish between actual and forecast values. See Forecasting. |
 | A data source cylinder with an orange tick indicates the field is from a secondary data source. See Blend Your Data. |
 | The filter is assigned to a specific worksheet. |
 | The filter is assigned to all worksheets with the same data source. |
 | The field is incompatible with one or more other fields in the view. |
| Visual Cue | Description |
 | The field is applied to Colour on the Marks card. |
 | The field is applied to Size on the Marks card. |
 | The field is applied to Label on the Marks card. |
 | The field is applied to Shape on the Marks card. |
 | The field is applied to Detail on the Marks card. |
 | The field is applied to Tooltip on the Marks card. |
 | The field is applied to Path on the Marks card. Path is only available when the Line or Polygon mark type is selected from the Marks drop-down menu. |
| Visual Cue | Description |
  | The sheet is a worksheet. |
  | The sheet is a dashboard. |
| Visual Cue | Description |
| [Field Name] | Orange text. The field is a dimension or measure, or a set. |
| [Parameters].[Parameter Name] | Purple text. The field is a parameter. Tableau adds the prefix [Parameters] to avoid ambiguity when a parameter has the same name as another field |
| [Data source].[Field Name] | Orange text. The field is from a secondary data source. The data source name is added as a prefix. |
| Blue() | Blue text. A calculation function. |
| Previous versions | 2020.2 and later | |
|---|---|---|
| | |
| In Tableau version 2020.1 and earlier, the data model has only the physical layer | In Tableau version 2020.2 and later, the data model has two layers: the logical layer and the physical layer |
Correct: Invoices and Appointments as the base tables | Incorrect: Doctors and Patients as the base tables |
 |  |
Base table | Shared table |
Fact tables in a data warehouse schema | Shared or conformed dimension tables in a data warehouse schema |
Specific to the context or analysis (flight information, energy usage) | Consistent concept across various contexts (date, location) |
Measure heavy | Primarily dimensions |
More frequently updated/transactional (medical appointments, prescriptions, vitals) | More stable/durable (doctor, patient) |
Has foreign key fields | Has primary key fields |
Event based (class schedule, grade on an assignment) | Entity based (student, classroom) |
| Components | Syntax | Example |
Functions | See Tableau Functions (Alphabetical) or Tableau Functions (by Category) for examples of how to format all functions in Tableau. |
|
Fields | A field in a calculation is often surrounded by brackets [ ]. See Field syntax for more information. |
|
Operators |
See Operator syntax for information on the types of operators you can use in Tableau calculation and the order they are performed in a formula. |
|
Literal expressions | Numeric literals are written as numbers. String literals are written with quotation marks. Date literals are written with the # symbol. Boolean literals are written as either true or false. Null literals are written as null. See Literal expression syntax for more information. |
|
Parameters | A parameter in a calculation is surrounded by brackets [ ], like a field. See Create Parameters for more information. |
|
Comments | To enter a comment in a calculation, type two forward slashes //. See Add comments to a calculation for more information. Multi-line comments can be added by typing /* to start the comment and */ to end it. |
|
icon to see a larger version of the visualisation.
