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Returns all the rows in a table, or all the values in a column, ignoring any filters that might have been applied. This function is useful for clearing filters and creating calculations on all the rows in a table.

## Syntax

`ALL( [<table> | <column>[, <column>[, <column>[,…]]]] ) `

### Parameters

Term | Definition |
---|---|

table | The table that you want to clear filters on. |

column | The column that you want to clear filters on. |

The argument to the ALL function must be either a reference to a base table or a reference to a base column. You cannot use table expressions or column expressions with the ALL function.

## Return value

The table or column with filters removed.

## Remarks

This function is not used by itself, but serves as an intermediate function that can be used to change the set of results over which some other calculation is performed.

(Video) Understanding ALL function in DAXThe normal behavior for DAX expressions containing the ALL() function is that any filters applied will be ignored. However, there are some scenarios where this is not the case because of

*auto-exist*, a DAX technology that optimizes filtering in order to reduce the amount of processing required for certain DAX queries. An example where auto-exist and ALL() provide unexpected results is when filtering on two or more columns of the same table (like when using slicers), and there is a measure on that same table that uses ALL(). In this case, auto-exist will*merge*the multiple filters into one and will only filter on existing combinations of values. Because of this merge, the measure will be calculated on the existing combinations of values and the result will be based on filtered values instead of all values as expected. To learn more about auto-exist and its effect on calculations, see Microsoft MVP Alberto Ferrari's Understanding DAX Auto-Exist article on sql.bi.com.The following table describes how you can use the ALL and ALLEXCEPT functions in different scenarios.

Function and usage Description ALL() Removes all filters everywhere. ALL() can only be used to clear filters but not to return a table. ALL(Table) Removes all filters from the specified table. In effect, ALL(Table) returns all of the values in the table, removing any filters from the context that otherwise might have been applied. This function is useful when you are working with many levels of grouping, and want to create a calculation that creates a ratio of an aggregated value to the total value. The first example demonstrates this scenario. ALL (Column[, Column[, …]]) Removes all filters from the specified columns in the table; all other filters on other columns in the table still apply. All column arguments must come from the same table. The ALL(Column) variant is useful when you want to remove the context filters for one or more specific columns and to keep all other context filters. The second and third examples demonstrate this scenario. ALLEXCEPT(Table, Column1 [,Column2]...) Removes all context filters in the table except filters that are applied to the specified columns. This is a convenient shortcut for situations in which you want to remove the filters on many, but not all, columns in a table. This function is not supported for use in DirectQuery mode when used in calculated columns or row-level security (RLS) rules.

## Example 1

Calculate ratio of Category Sales to Total Sales

Assume that you want to find the amount of sales for the current cell, in your PivotTable, divided by the total sales for all resellers. To ensure that the denominator is the same regardless of how the PivotTable user might be filtering or grouping the data, you define a formula that uses ALL to create the correct grand total.

The following table shows the results when a new measure, **All Reseller Sales Ratio**, is created using the formula shown in the code section. To see how this works, add the field, CalendarYear, to the **Row Labels** area of the PivotTable, and add the field, ProductCategoryName, to the **Column Labels** area. Then, drag the measure, **All Reseller Sales Ratio**, to the **Values** area of the Pivot Table. To view the results as percentages, use the formatting features of Excel to apply a percentage number formatting to the cells that contains the measure.

Row Labels | Accessories | Bikes | Clothing | Components | Grand Total |
---|---|---|---|---|---|

2005 | 0.02% | 9.10% | 0.04% | 0.75% | 9.91% |

2006 | 0.11% | 24.71% | 0.60% | 4.48% | 29.90% |

2007 | 0.36% | 31.71% | 1.07% | 6.79% | 39.93% |

2008 | 0.20% | 16.95% | 0.48% | 2.63% | 20.26% |

Grand Total | 0.70% | 82.47% | 2.18% | 14.65% | 100.00% |

**Formula**

`= SUMX(ResellerSales_USD, ResellerSales_USD[SalesAmount_USD])/SUMX(ALL(ResellerSales_USD), ResellerSales_USD[SalesAmount_USD]) `

The formula is constructed as follows:

The numerator,

`SUMX(ResellerSales_USD, ResellerSales_USD[SalesAmount_USD])`

, is the sum of the values in ResellerSales_USD[SalesAmount_USD] for the current cell in the PivotTable, with context filters applied on CalendarYear and ProductCategoryName.For the denominator, you start by specifying a table, ResellerSales_USD, and use the ALL function to remove all context filters on the table.

You then use the SUMX function to sum the values in the ResellerSales_USD[SalesAmount_USD] column. In other words, you get the sum of ResellerSales_USD[SalesAmount_USD] for all resellers sales.

## Example 2

Calculate Ratio of Product Sales to Total Sales Through Current Year

Assume that you want to create a table showing the percentage of sales compared over the years for each product category (ProductCategoryName). To obtain the percentage for each year over each value of ProductCategoryName, you need to divide the sum of sales for that particular year and product category by the sum of sales for the same product category over all years. In other words, you want to keep the filter on ProductCategoryName but remove the filter on the year when calculating the denominator of the percentage.

The following table shows the results when a new measure, **Reseller Sales Year**, is created using the formula shown in the code section. To see how this works, add the field, CalendarYear, to the **Row Labels** area of a PivotTable, and add the field, ProductCategoryName, to the **Column Labels** area. To view the results as percentages, use Excel's formatting features to apply a percentage number format to the cells containing the measure, **Reseller Sales Year**.

Row labels | Accessories | Bikes | Clothing | Components | Grand Total |
---|---|---|---|---|---|

2005 | 3.48% | 11.03% | 1.91% | 5.12% | 9.91% |

2006 | 16.21% | 29.96% | 27.29% | 30.59% | 29.90% |

2007 | 51.62% | 38.45% | 48.86% | 46.36% | 39.93% |

2008 | 28.69% | 20.56% | 21.95% | 17.92% | 20.26% |

Grand Total | 100.00% | 100.00% | 100.00% | 100.00% | 100.00% |

**Formula**

`= SUMX(ResellerSales_USD, ResellerSales_USD[SalesAmount_USD])/CALCULATE( SUM( ResellerSales_USD[SalesAmount_USD]), ALL(DateTime[CalendarYear])) `

The formula is constructed as follows:

The numerator,

`SUMX(ResellerSales_USD, ResellerSales_USD[SalesAmount_USD])`

, is the sum of the values in ResellerSales_USD[SalesAmount_USD] for the current cell in the pivot table, with context filters applied on the columns CalendarYear and ProductCategoryName.For the denominator, you remove the existing filter on CalendarYear by using the ALL(Column) function. This calculates the sum over the remaining rows on the ResellerSales_USD table, after applying the existing context filters from the column labels. The net effect is that for the denominator the sum is calculated over the selected ProductCategoryName (the implied context filter) and for all values in Year.

(Video) All Function in Power BI DAX

## Example 3

Calculate Contribution of Product Categories to Total Sales Per Year

Assume that you want to create a table that shows the percentage of sales for each product category, on a year-by-year basis. To obtain the percentage for each product category in a particular year, you need to calculate the sum of sales for that particular product category (ProductCategoryName) in year n, and then divide the resulting value by the sum of sales for the year n over all product categories. In other words, you want to keep the filter on year but remove the filter on ProductCategoryName when calculating the denominator of the percentage.

The following table shows the results when a new measure, **Reseller Sales CategoryName**, is created using the formula shown in the code section. To see how this works, add the field, CalendarYear to the **Row Labels** area of the PivotTable, and add the field, ProductCategoryName, to the **Column Labels** area. Then add the new measure to the **Values** area of the PivotTable. To view the results as percentages, use Excel's formatting features to apply a percentage number format to the cells that contain the new measure, **Reseller Sales CategoryName**.

Row Labels | Accessories | Bikes | Clothing | Components | Grand Total |
---|---|---|---|---|---|

2005 | 0.25% | 91.76% | 0.42% | 7.57% | 100.00% |

2006 | 0.38% | 82.64% | 1.99% | 14.99% | 100.00% |

2007 | 0.90% | 79.42% | 2.67% | 17.01% | 100.00% |

2008 | 0.99% | 83.69% | 2.37% | 12.96% | 100.00% |

Grand Total | 0.70% | 82.47% | 2.18% | 14.65% | 100.00% |

**Formula**

`= SUMX(ResellerSales_USD, ResellerSales_USD[SalesAmount_USD])/CALCULATE( SUM( ResellerSales_USD[SalesAmount_USD]), ALL(ProductCategory[ProductCategoryName])) `

The formula is constructed as follows:

The numerator,

`SUMX(ResellerSales_USD, ResellerSales_USD[SalesAmount_USD])`

, is the sum of the values in ResellerSales_USD[SalesAmount_USD] for the current cell in the PivotTable, with context filters applied on the fields, CalendarYear and ProductCategoryName.(Video) ALL Vs ALLSELECTED Vs ALLEXCEPT DAX Filter Functions | DAX Sundays | DAX Tutorial |BI Consulting ProFor the denominator, you use the function, ALL(Column), to remove the filter on ProductCategoryName and calculate the sum over the remaining rows on the ResellerSales_USD table, after applying the existing context filters from the row labels. The net effect is that, for the denominator, the sum is calculated over the selected Year (the implied context filter) and for all values of ProductCategoryName.

## See also

Filter functions

ALL function

ALLEXCEPT function

FILTER function

## FAQs

### How many DAX functions are there? ›

The DAX function reference provides detailed information including syntax, parameters, return values, and examples for each of the **over 250** functions used in Data Analysis Expression (DAX) formulas.

**What is the difference between all and ALLEXCEPT in DAX? ›**

All function is used when you want to fetch data from the entire table or a few columns without filter action. All except is used similarly to all but would fetch data that is affected after applying filters from the entire table or few columns. syn = ALLEXCEPT/ALL(table name,column name).

**What is difference between all and Allselected in DAX? ›**

It is different from the ALL function in that **the ALL function ignores all filters regardless of where they come from, while the ALLSELECTED function ignores filters that come from the inner query**.

**What does calculate all do? ›**

CALCULATE Using ALL, ALLEXCEPT

We can achieve this by using the function ALL and ALLEXCEPT. The ALL function will **compute the expression part of your CALCULATE function on all of the data in the data set regardless of the filters applied to it**.

**What are DAX function types? ›**

The DAX language uses four different types of calculation operators in formulas: Comparison operators to compare values and return a logical TRUE\FALSE value. Arithmetic operators to perform arithmetic calculations that return numeric values. Text concatenation operators to join two or more text strings.

**How to use SUMX in DAX? ›**

The SUMX function takes as its first argument a table, or an expression that returns a table. The second argument is a column that contains the numbers you want to sum, or an expression that evaluates to a column. Only the numbers in the column are counted. Blanks, logical values, and text are ignored.

**What is the difference between all and Removefilters in DAX? ›**

REMOVEFILTERS is like ALL, but it can only be used as a filter argument in CALCULATE. **While REMOVEFILTERS can replace ALL, there is not replacement for ALLEXCEPT and ALLSELECTED used as CALCULATE modifiers**. In this case, ALL is a filter parameter of CALCULATE. As such, it acts as a REMOVEFILTERS, not as an ALL.

**What is the difference between sum and SUMX? ›**

Unlike SUM, **SUMX is capable of performing row-by-row calculations and iterates through every row of a specified table to complete the calculation**. SUMX then adds all the row-wise results of the iterations of the given expression.

**What is the difference between summarize and Summarizecolumns in DAX? ›**

Another difference between SUMMARIZE and SUMMARIZECOLUMNS is that SUMMARIZE keeps both a row context and a filter context active in the expression where you specify the aggregation (more details in All the secrets of SUMMARIZE), whereas SUMMARIZECOLUMNS provides a filter context only and no row context.

**What is the difference between distinct () and values () in DAX? ›**

**The DISTINCT function allows a column name or any valid table expression to be its argument but the VALUES function only accepts a column name or a table name as the argument**.

### What is the difference between all and Allselected and Allexcept? ›

ALL – Returns all the rows in a table or all the values in a column, ignoring any filters which might have been applied. ALLSELECTED- Returns all the rows in a table or all the values in a column, ignoring any filters which might have been applied on the columns or the rows but keeping all other explicit filters.

**What are the two types of context in DAX? ›**

There are different types of context: **row context, query context**, and filter context. Row context can be thought of as "the current row.” If you have created a calculated column, the row context consists of the values in each individual row and values in columns that are related to the current row.

**How do I filter data in DAX? ›**

You do this by **specifying a table as an input to the formula, and then defining a filter expression**. The filter expression you provide is used to query the data and return only a subset of the source data.

**What units do all calculations? ›**

**arithmetic-logic unit (ALU)**

**Which are all the calculations? ›**

A calculator is a device that performs arithmetic operations on numbers. Basic calculators can do only addition, subtraction, multiplication and division mathematical calculations.

**What does == mean in DAX? ›**

The “strictly equal to” operator == returns TRUE when the two arguments have the same value or are both BLANK. A comparison between BLANK and any other value returns FALSE.

**What are the most common DAX functions you have used? ›**

DAX Functions for Power BI: **Date and Time Functions**

DAX Date and Time functions follow the similar syntax and rules as the Excel date and time functions but operate on DAX's data type to calculate the values of time and date.

**What is Edate in DAX? ›**

**Returns the date that is the indicated number of months before or after the start date**. Use EDATE to calculate maturity dates or due dates that fall on the same day of the month as the date of issue.

**What does Crossjoin do in DAX? ›**

**Returns a table that contains the Cartesian product of all rows from all tables in the arguments**.

**How do you add multiple conditions in DAX? ›**

For multiple criterias in DAX you can **use the AND or OR functions (that only handle up to 2 conditions), or operators like && or ||**. but it becomes too complex and unclear if there are more IFs. With SWITCH we can simply keep the logic condition - result - condition - result etc.

### How can I make DAX more efficient? ›

Always remember to **clear your DAX cache** before optimizing DAX as your DAX cache builds up from internal VertiPaq queries. You can clear your cache from DAX Studio. Resetting your cache also enables you to measure performance gains more effectively.

**Which is faster DAX or power query? ›**

PQ calculation slows down data load, where as DAX calculated column will slow down visual update on interaction with slicer etc. Most cases, if you do data load during after hours (or early in the morning) once. **It's more desirable to have better performance during interaction with report**.

**How do I Lookup multiple values in DAX? ›**

**Conclusion**

- RELATED. Returns a related value from another table. ...
- LOOKUPVALUE. Retrieves a value from a table. ...
- GENERATE. The second table expression will be evaluated for each row in the first table. ...
- ROW. Returns a single row table with new columns specified by the DAX expressions. ...
- TREATAS. ...
- VALUES. ...
- GENERATEALL. ...
- SELECTCOLUMNS.

**Are sum () and add () functions the same? ›**

Are sum() and add() functions are same? **No both sum() and add() are different** because add() is used to perform binary operation on two dataframes and sum() is used to add the values of given axis of a dataframe.

**Can we use SUMX in calculated column? ›**

Function 'SUMX' is **not allowed as part of calculated column DAX expressions on DirectQuery model**. Hello, We are creating a measure for Weighted Averages using SUMX function, and then based on the value from this measure we would like to bucket our dimension values (Business Units for example) into different categories.

**How do I sum two columns in DAX? ›**

...

**Power BI sum group by Multiple columns with filter**

- Total Sales = New Table Name.
- Sales = Existing Table Name.
- Product, Country, Sales = Column names.

**What is difference between filter and Keepfilters in DAX? ›**

The net effect over any one column is that both sets of arguments apply: both the filter arguments used in CALCULATE and the filters in the arguments of the KEEPFILTER function. In other words, **whereas CALCULATE filters replace the current context, KEEPFILTERS adds filters to the current context**.

**What is coalesce in DAX? ›**

COALESCE **accepts multiple arguments and returns the first argument that is not blank**. If the first argument is blank, COALESCE returns the value provided by the expression in the second argument, and so on. If all the arguments are blank, COALESCE returns blank as well.

**What does && do in DAX? ›**

&& (double ampersand) **Creates an AND condition between two expressions that each have a Boolean result**. If both expressions return TRUE, the combination of the expressions also returns TRUE; otherwise the combination returns FALSE.

**Should we use distinct or GROUP BY? ›**

The major difference between the DISTINCT and GROUP BY is, **GROUP BY operator is meant for the aggregating or grouping rows whereas DISTINCT is just used to get distinct values**.

### Is distinct faster than GROUP BY? ›

**GROUP BY is slightly faster than SELECT DISTINCT**

The difference is hardly noticeable to users. These tests were done on Access back-end database tables and may not hold for other types of data sources (e.g., SQL Server linked tables)

**How do I remove duplicates in DAX? ›**

There is another version of the DISTINCT function, **DISTINCT (table)**, that returns a table by removing duplicate rows from another table or expression.. The VALUES function is similar to DISTINCT; it can also be used to return a list of unique values, and generally will return exactly the same results as DISTINCT.

**What is all and Allexcept function? ›**

The ALL(Column) variant is useful when you want to remove the context filters for one or more specific columns and to keep all other context filters. ALLEXCEPT(Table, Column1 [,Column2]...) **Removes all context filters in the table except filters that are applied to the specified columns**.

**What does all mean in DAX? ›**

ALL(Table) **Removes all filters from the specified table**. In effect, ALL(Table) returns all of the values in the table, removing any filters from the context that otherwise might have been applied.

**How does Allexcept DAX work? ›**

When used as a table function, ALLEXCEPT **materializes all the unique combinations of the columns in the table specified in the first argument that are not listed in the following arguments**. In this case, the result only has the columns of the table and ignores the expanded table.

**How many datatypes of DAX are there? ›**

DAX offers **three** different numeric data types, which have an internal name that does not always correspond to the name provided in the user interface. DAX is currently used by three different products: Power Pivot, Analysis Services, and Power BI.

**Which DAX functions have you used the most? ›**

The CALCULATE function is one of the most important and multipurpose functions in DAX Power BI. This function can simplify complex and multiple calculations with simple efforts. The DAX CALCULATE function assesses an expression in a context that is changed by specific filters.

**How many functions are there in Calc? ›**

Calc includes **over 350** functions to help you analyze and reference data.