SUMMARIZE
Applies to: Calculated column Calculated table Measure Visual calculation
Returns a summary table for the requested totals over a set of groups.
SUMMARIZE (<table>, <groupBy_columnName>[, <groupBy_columnName>]…[, <name>, <expression>]…)
Term | Definition |
---|---|
table | Any DAX expression that returns a table of data. |
groupBy_ColumnName | (Optional) The qualified name of an existing column used to create summary groups based on the values found in it. This parameter cannot be an expression. |
name | The name given to a total or summarize column, enclosed in double quotes. |
expression | Any DAX expression that returns a single scalar value, where the expression is to be evaluated multiple times (for each row/context). |
A table with the selected columns for the groupBy_columnName arguments and the summarized columns designed by the name arguments.
Each column for which you define a name must have a corresponding expression; otherwise, an error is returned. The first argument, name, defines the name of the column in the results. The second argument, expression, defines the calculation performed to obtain the value for each row in that column.
groupBy_columnName must be either in table or in a related table to table.
Each name must be enclosed in double quotation marks.
The function groups a selected set of rows into a set of summary rows by the values of one or more groupBy_columnName columns. One row is returned for each group.
This function is not supported for use in DirectQuery mode when used in calculated columns or row-level security (RLS) rules.
The following example returns a summary of the reseller sales grouped around the calendar year and the product category name, this result table allows you to do analysis over the reseller sales by year and product category.
SUMMARIZE(ResellerSales_USD
, DateTime[CalendarYear]
, ProductCategory[ProductCategoryName]
, "Sales Amount (USD)", SUM(ResellerSales_USD[SalesAmount_USD])
, "Discount Amount (USD)", SUM(ResellerSales_USD[DiscountAmount])
)
The following table shows a preview of the data as it would be received by any function expecting to receive a table:
DateTime[CalendarYear] | ProductCategory[ProductCategoryName] | [Sales Amount (USD)] | [Discount Amount (USD)] |
---|---|---|---|
2008 | Bikes | 12968255.42 | 36167.6592 |
2005 | Bikes | 6958251.043 | 4231.1621 |
2006 | Bikes | 18901351.08 | 178175.8399 |
2007 | Bikes | 24256817.5 | 276065.992 |
2008 | Components | 2008052.706 | 39.9266 |
2005 | Components | 574256.9865 | 0 |
2006 | Components | 3428213.05 | 948.7674 |
2007 | Components | 5195315.216 | 4226.0444 |
2008 | Clothing | 366507.844 | 4151.1235 |
2005 | Clothing | 31851.1628 | 90.9593 |
2006 | Clothing | 455730.9729 | 4233.039 |
2007 | Clothing | 815853.2868 | 12489.3835 |
2008 | Accessories | 153299.924 | 865.5945 |
2005 | Accessories | 18594.4782 | 4.293 |
2006 | Accessories | 86612.7463 | 1061.4872 |
2007 | Accessories | 275794.8403 | 4756.6546 |
The addition of the ROLLUP syntax modifies the behavior of the SUMMARIZE function by adding rollup rows to the result on the groupBy_columnName columns. ROLLUP can only be used within a SUMMARIZE expression.
The following example adds rollup rows to the Group-By columns of the SUMMARIZE function call:
SUMMARIZE(ResellerSales_USD
, ROLLUP( DateTime[CalendarYear], ProductCategory[ProductCategoryName])
, "Sales Amount (USD)", SUM(ResellerSales_USD[SalesAmount_USD])
, "Discount Amount (USD)", SUM(ResellerSales_USD[DiscountAmount])
)
Returns the following table,
DateTime[CalendarYear] | ProductCategory[ProductCategoryName] | [Sales Amount (USD)] | [Discount Amount (USD)] |
---|---|---|---|
2008 | Bikes | 12968255.42 | 36167.6592 |
2005 | Bikes | 6958251.043 | 4231.1621 |
2006 | Bikes | 18901351.08 | 178175.8399 |
2007 | Bikes | 24256817.5 | 276065.992 |
2008 | Components | 2008052.706 | 39.9266 |
2005 | Components | 574256.9865 | 0 |
2006 | Components | 3428213.05 | 948.7674 |
2007 | Components | 5195315.216 | 4226.0444 |
2008 | Clothing | 366507.844 | 4151.1235 |
2005 | Clothing | 31851.1628 | 90.9593 |
2006 | Clothing | 455730.9729 | 4233.039 |
2007 | Clothing | 815853.2868 | 12489.3835 |
2008 | Accessories | 153299.924 | 865.5945 |
2005 | Accessories | 18594.4782 | 4.293 |
2006 | Accessories | 86612.7463 | 1061.4872 |
2007 | Accessories | 275794.8403 | 4756.6546 |
2008 | 15496115.89 | 41224.3038 | |
2005 | 7582953.67 | 4326.4144 | |
2006 | 22871907.85 | 184419.1335 | |
2007 | 30543780.84 | 297538.0745 | |
76494758.25 | 527507.9262 |
The addition of ROLLUPGROUP inside a ROLLUP syntax can be used to prevent partial subtotals in rollup rows. ROLLUPGROUP can only be used within a ROLLUP, ROLLUPADDISSUBTOTAL, or ROLLUPISSUBTOTAL expression.
The following example shows only the grand total of all years and categories without the subtotal of each year with all categories:
SUMMARIZE(ResellerSales_USD
, ROLLUP(ROLLUPGROUP( DateTime[CalendarYear], ProductCategory[ProductCategoryName]))
, "Sales Amount (USD)", SUM(ResellerSales_USD[SalesAmount_USD])
, "Discount Amount (USD)", SUM(ResellerSales_USD[DiscountAmount])
)
Returns the following table,
DateTime[CalendarYear] | ProductCategory[ProductCategoryName] | [Sales Amount (USD)] | [Discount Amount (USD)] |
---|---|---|---|
2008 | Bikes | 12968255.42 | 36167.6592 |
2005 | Bikes | 6958251.043 | 4231.1621 |
2006 | Bikes | 18901351.08 | 178175.8399 |
2007 | Bikes | 24256817.5 | 276065.992 |
2008 | Components | 2008052.706 | 39.9266 |
2005 | Components | 574256.9865 | 0 |
2006 | Components | 3428213.05 | 948.7674 |
2007 | Components | 5195315.216 | 4226.0444 |
2008 | Clothing | 366507.844 | 4151.1235 |
2005 | Clothing | 31851.1628 | 90.9593 |
2006 | Clothing | 455730.9729 | 4233.039 |
2007 | Clothing | 815853.2868 | 12489.3835 |
2008 | Accessories | 153299.924 | 865.5945 |
2005 | Accessories | 18594.4782 | 4.293 |
2006 | Accessories | 86612.7463 | 1061.4872 |
2007 | Accessories | 275794.8403 | 4756.6546 |
76494758.25 | 527507.9262 |
With ISSUBTOTAL, you can create another column in the SUMMARIZE expression that returns True if the row contains subtotal values for the column given as argument to ISSUBTOTAL, otherwise returns False. ISSUBTOTAL can only be used within a SUMMARIZE expression.
The following sample generates an ISSUBTOTAL column for each of the ROLLUP columns in the given SUMMARIZE function call:
SUMMARIZE(ResellerSales_USD
, ROLLUP( DateTime[CalendarYear], ProductCategory[ProductCategoryName])
, "Sales Amount (USD)", SUM(ResellerSales_USD[SalesAmount_USD])
, "Discount Amount (USD)", SUM(ResellerSales_USD[DiscountAmount])
, "Is Sub Total for DateTimeCalendarYear", ISSUBTOTAL(DateTime[CalendarYear])
, "Is Sub Total for ProductCategoryName", ISSUBTOTAL(ProductCategory[ProductCategoryName])
)
Returns the following table,
[Is Sub Total for DateTimeCalendarYear] | [Is Sub Total for ProductCategoryName] | DateTime[CalendarYear] | ProductCategory[ProductCategoryName] | [Sales Amount (USD)] | [Discount Amount (USD)] |
---|---|---|---|---|---|
FALSE | FALSE | ||||
FALSE | FALSE | 2008 | Bikes | 12968255.42 | 36167.6592 |
FALSE | FALSE | 2005 | Bikes | 6958251.043 | 4231.1621 |
FALSE | FALSE | 2006 | Bikes | 18901351.08 | 178175.8399 |
FALSE | FALSE | 2007 | Bikes | 24256817.5 | 276065.992 |
FALSE | FALSE | 2008 | Components | 2008052.706 | 39.9266 |
FALSE | FALSE | 2005 | Components | 574256.9865 | 0 |
FALSE | FALSE | 2006 | Components | 3428213.05 | 948.7674 |
FALSE | FALSE | 2007 | Components | 5195315.216 | 4226.0444 |
FALSE | FALSE | 2008 | Clothing | 366507.844 | 4151.1235 |
FALSE | FALSE | 2005 | Clothing | 31851.1628 | 90.9593 |
FALSE | FALSE | 2006 | Clothing | 455730.9729 | 4233.039 |
FALSE | FALSE | 2007 | Clothing | 815853.2868 | 12489.3835 |
FALSE | FALSE | 2008 | Accessories | 153299.924 | 865.5945 |
FALSE | FALSE | 2005 | Accessories | 18594.4782 | 4.293 |
FALSE | FALSE | 2006 | Accessories | 86612.7463 | 1061.4872 |
FALSE | FALSE | 2007 | Accessories | 275794.8403 | 4756.6546 |
FALSE | TRUE | ||||
FALSE | TRUE | 2008 | 15496115.89 | 41224.3038 | |
FALSE | TRUE | 2005 | 7582953.67 | 4326.4144 | |
FALSE | TRUE | 2006 | 22871907.85 | 184419.1335 | |
FALSE | TRUE | 2007 | 30543780.84 | 297538.0745 | |
TRUE | TRUE | 76494758.25 | 527507.9262 |