Finding All Selected Items In A Slicer In Excel 2016 Using TextJoin()

When you are using slicers with an Excel PivotTable it’s often useful to be able to get a comma-delimited list of the items selected in that slicer for use in a report title. It’s not easy to do though, and in fact this is one of those topics that lots of people have blogged about over the years: here’s my MDX approach, here’s Erik Svensen’s post on using the new DAX ConcatenateX() function, and there are also posts by Rob Collie like this one. None of these techniques are ideal though: my personal favourite is the ConcatenateX() approach, but that only works with SSAS Tabular 2016 (and then only if you can create a measure on the model) or Power Pivot in Excel 2016, and not at all if you’re using SSAS Multidimensional or earlier versions of SSAS Tabular.

However, after discovering the new TextJoin() function in Excel 2016 the other week I realised that this would provide yet another way to solve this problem. Here’s a simple example using a PivotTable and slicer connected to a Power Pivot model:


The highlighted cell F3 showing a comma-delimited list of all the items selected in the slicer has the following Excel formula:

    ", ",

Important: this needs to be entered as an array formula, so instead of hitting Enter after typing in the formula you need to hit Ctrl+Shift+Enter. You’ll see the formula surrounded by braces {} in the formula bar when you do this:



This formula relies on the fact that the selection in a slicer (in the example above the slicer has the name Slicer_Product) can be treated the same as the output of the Excel CubeSet() function, which means that you can use the CubeSetCount() function to find the number of items selected and the CubeRankedMember() function to get the name of any single item in the selection. It also uses the Row()/Indirect() trick described here to create an array of numbers from 1 to the number of items selected in the slicer, which in turn provides the rank values to pass to the CubeRankedMember() function.

The beauty of this approach is that it works for Power Pivot and all versions of SSAS Tabular and Multidimensional, and doesn’t require any measures to be created on your models/cubes. It even works in Excel Online, so it will work inside Power BI, although it doesn’t seem to be possible to create array formulas in Excel Online yet so you need to create the formula on the desktop before you deploy. Of course you need the latest build of Excel 2016 for all this to work, and at the time of writing most people don’t have Excel 2016 and even if they do they probably won’t have a build (Version 16.0.6568.2025 or higher) with TextJoin() in it yet. But this will be a great solution in the distant future when everyone has Excel 2016, I promise!

You can download the sample Excel 2016 workbook here.

I also have to acknowledge the help of David Hager in writing this formula – we had a conversation about how TextJoin() behaves in array formulas in the comments of my earlier post and in doing so he provided the basic approach for me.

Automatically Generating Date Dimension Tables In Excel 2016 Power Pivot

As you probably know, whenever you are doing any kind of date or time-based calculations in DAX you should always have a separate Date table in your Power Pivot model. There are a number of ways of building these tables (see, for example, my Power Query query here) but they are all a bit of a hassle – which is why it’s so cool that, in Excel 2016, you can get one built automatically inside the Power Pivot window.

Consider the following table of sales data on an Excel worksheet:


With this table loaded into the Data Model (and the Order Date column recognised as containing data of the Date data type), when you go to the Design tab in the Power Pivot window you’ll see the new Date Table button enabled:


Clicking on the New button will add a new date table to the Data Model, called Calendar:


This table is automatically marked as the Date Table in your model.

The table contains a continuous range of dates starting from the beginning of the year of the earliest date found in any column in any table in your Data Model, up to the end of the year containing the latest date found in any column in any table in your Data Model. Obviously, this means that your table could contain a very large date range if, for example, you have a Customer table containing a Date Of Birth column. Luckily, you also have the option of manually configuring the range of dates used by clicking the Update Range button:


One other thing to point out is that the resulting table is a table like any other, so you can add, delete or rename columns as you wish. You should also be able to set the table back to its default state by using the Set Default menu option, but I couldn’t make that work (possibly it hasn’t been implemented yet – this post was written using the Excel 2016 Preview).

If you do make changes like adding calculated columns, such as the Month Year calculated column shown below:


You can then click the Save Configuration button to save the current state of the table as your default. This means that the next time you create a new Date table in the same workbook, the table will include any customisations. However these changes don’t seem to be applied in Date tables created in new workbooks – maybe this will also change before RTM?

All in all, this is a very handy feature that will save Power Pivot modellers a lot of time. I wonder if it uses the new Calendar() or CalendarAuto() DAX functions under the covers?

Using DateDiff() To Calculate Time Intervals In DAX

One of the most useful new additions to DAX in Excel 2016 and the Power BI Designer is the DateDiff() function. It does exactly what you would expect: calculate the amount of time in between two dates, and express that value as either seconds, minutes, hours, days, weeks, months, quarters or years.

Here’s a very simple table of dates:


With this table loaded into the Power BI Designer, you can add new calculated columns to the table by clicking the New Column button on the ribbon. Here are two calculated column definitions that give the number of days and the number of years between the Start Date and the End Date on each row:

DayDurationColumn = 
DATEDIFF(MyTable[Start Date], MyTable[End Date], DAY)

YearDurationColumn = 
DATEDIFF(MyTable[Start Date], MyTable[End Date], YEAR) 

The output is pretty much what you’d expect:


It is of course also possible to create measures that use the DateDiff() function to, for example:

YearDurationMeasure = 
FIRSTDATE(MyTable[Start Date]), 
LASTDATE(MyTable[End Date]), 


All very straightforward, then, and much easier than having to calculate these values yourself.

Using SelectColumns() To Alias Columns In DAX

A few years ago I wrote this post on how to alias columns in a table in DAX, using a combination of AddColumns() and Summarize(). The good news is that in Excel 2016/the Power BI Designer/SSAS Tabular 2016 there’s a new DAX function specifically for this purpose: SelectColumns(). Here’s an example of how it can be used:

Imagine you have the following source table, called Products:


You can write a DAX query to get all the rows and columns from this table like so:


Here’s the output of that query in DAX Studio (and remember, DAX Studio can connect to data loaded into the Power BI Designer, which is what I’m doing here):


You can alias the columns in this table using SelectColumns() very easily, like so:

    "Column One", Products[Product],
    "Column Two", Products[Colour]

Here’s the output:


The syntax for SelectColumns() is straightforward: the first parameter is a table expression, and after that there are pairs of parameters consisting of:

  • A new column name
  • An expression returning a column from the table given in the first parameter

As you can see in the output of the query above, I’ve renamed the Product column “Column One” and the Colour column “Column Two”.

This means I can now crossjoin a table with itself without needing to worry about conflicting column names, like so:

        "Column One", Products[Product],
        "Column Two", Products[Colour]


One other interesting thing to note about SelectColumns() is that it allows you to do projection in a DAX query easily – as Marco notes here, it was possible before but it wasn’t pleasant. For example, the query:

    "Just Colour", Products[Colour]



Notice how there are three rows in the output here and that the value Green occurs twice. If you’re a true DAX afficionado, you might get excited about that.

Documentation For New Excel 2016 DAX Functions

Microsoft has published documentation for the new DAX functions in the Excel 2016 preview here:

There’s a lot of detail, including examples (although the ConcatenateX() page isn’t live at the time of writing – but I’ve blogged about that already), so it’s well worth reading through.

NaturalInnerJoin And NaturalLeftOuterJoin DAX Functions In Excel 2016

Continuing my series on new DAX functions in Excel 2016, here are two more: NaturalInnerJoin() and NaturalLeftOuterJoin(). Both do pretty much what you’d expect.

Consider the following two tables in an Excel worksheet, called ColourFruit and FruitPrice:


With these tables loaded into the Excel Data Model as linked tables, the next step is to create a relationship between the tables on the Fruit column:


Both functions only work with two tables that have an active relationship between them, and both take two tables from the Excel Data Model as parameters. Once you’ve done that you can use these functions in a DAX query.

The queries

evaluate naturalinnerjoin(ColourFruit,FruitPrice)


evaluate naturalinnerjoin(FruitPrice,ColourFruit)

…both perform an inner join between the two tables on the Fruit column and both return the same table:


The query

evaluate naturalleftouterjoin(ColourFruit,FruitPrice)



The query

evaluate naturalleftouterjoin(FruitPrice,ColourFruit)



For NaturalLeftOuterJoin() the table given in the first parameter is on the left-hand side of the left outer join, so all rows from it are returned, whereas the table in the second parameter is on the right-hand side of the join so only the matching rows are returned.

What’s New In The Excel 2016 Preview For BI?

Following on from my recent post on Power BI and Excel 2016 news, here are some more details about the new BI-related features in the Excel 2016 Preview. Remember that more BI-related features may appear before the release of Excel 2016, and that with Office 365 click-to-run significant new features can appear in between releases, so this is not a definitive list of what Excel 2016 will be able to do at RTM but a snapshot of functionality available as of March 2015 as outlined in this document and which I’ve found from my own investigations. When I find out more, or when new functionality appears, I’ll either update this post or write a new one.

Power Query

Yesterday, in the original version of my post, I mistakenly said that Power Query was a native add-in in Excel 2016: that’s not true, it’s not an add-in at all, it’s native Excel functionality. Indeed you can see that there is no separate Power Query tab any more, and instead there is a Power Query section on the Data tab instead:


Obviously I’m a massive fan of Power Query so I’m biased, but I think this is a great move because it makes all the great Power Query functionality a lot easier to discover. There’s nothing to enable – it’s there by default – although I am a bit worried that users will be confused by having the older Data tab features next to their Power Query equivalents.

There are no new features for Power Query here compared to the latest version for Excel 2013, but that’s what I expected.

Excel Forecasting Functions

I don’t pretend to know anything about forecasting, but I had a brief play with the new Forecast.ETS function and got some reasonable results out of it as seen in the screenshot below:


Slicer Multiselect

There’s a new hammer icon on a slicer, which, when you click it, changes the way selection works. The default behaviour is the same as Excel 2013: every time you click on an item, that item is selected and any previous selection is lost (unless you were holding control or shift to multiselect). However with the hammer icon selected each new click adds the item to the previously selected items. This is meant to make slicers easier to use with a touch-screen.


Time Grouping in PivotTables

Quite a neat feature this, I think. If you have a table in the Excel Data Model that has a column of type date in it, you can add extra calculated columns to that table from within a PivotTable to group by things like Year and Month. For example, here’s a PivotTable I built on a table that contains just dates:


Right-clicking on the field containing the dates and clicking Group brings up the following dialog:


Choosing Years, Quarters and Months creates three extra fields in the PivotTable:


And these fields are implemented as calculated columns in the original table in the Excel Data Model, with DAX definitions as seen here:


Power View on SSAS Multidimensional

At-bloody-last. I haven’t installed SSAS on the VM I’m using for testing Excel 2016, but I assume it just works. Nothing new in Power View yet, by the way.

Power Map data cards

Not sure why this is listed as new in Excel 2016 when it seems to be the same feature that appeared in Excel 2013 Power Map recently:

Power Pivot

There isn’t any obvious new functionality in the Power Pivot window, but it’s clear that the UI in general and the DAX formula editor experience in particular has been improved.


Suggested Relationships

When you use fields from two Excel Data Model tables that have no relationship between them in a PivotTable, you get a prompt to either create new relationships yourself or let Excel detect the relationships:


Renaming Tables and Fields in the Power Pivot window

In Excel 2013 when you renamed tables or fields in the Excel Data Model, any PivotTables that used those objects had them deleted. Now, in Excel 2016, the PivotTable retains the reference to table or field and just displays the new name. What’s even better is that when you create a measure or a calculated column that refers to a table or column, the DAX definition of the measure or calculated column gets updated after a rename too.


There are lots of new DAX functions in this build. With the help of the mdschema_functions schema rowset and Power Query I was able to compare the list of DAX functions available in 2016 with those in 2013 and create the following list of new DAX functions and descriptions:

DATEDIFF			Returns the number of units (unit specified in Interval) 
			between the input two dates
CONCATENATEX		Evaluates expression for each row on the table, then 
			return the concatenation of those values in a single string 
			result, separated by the specified delimiter
KEYWORDMATCH		Returns TRUE if there is a match between the 
			MatchExpression and Text. 
ADDMISSINGITEMS		Add the rows with empty measure values back.
CALENDAR			Returns a table with one column of all dates between 
			StartDate and EndDate 
CALENDARAUTO		Returns a table with one column of dates 
			calculated from the model automatically
CROSSFILTER		Specifies cross filtering direction to be used in 
			the evaluation of a DAX expression. The relationship is 
			defined by naming, as arguments, the two columns that 
			serve as endpoints
CURRENTGROUP		Access to the (sub)table representing current 
			group in GroupBy function. Can be used only inside GroupBy 
GROUPBY			Creates a summary the input table grouped by the 
			specified columns
IGNORE			Tags a measure expression specified in the call to 
			SUMMARIZECOLUMNS function to be ignored when 
			determining the non-blank rows.
ISONORAFTER		The IsOnOrAfter function is a boolean function that 
			emulates the behavior of Start At clause and returns 
			true for a row that meets all the conditions mentioned as 
			parameters in this function.
NATURALINNERJOIN		Joins the Left table with right table using the 
			Inner Join semantics
NATURALLEFTOUTERJOIN	Joins the Left table with right table 
			using the Left Outer Join semantics
ROLLUPADDISSUBTOTAL		Identifies a subset of columns specified 
			in the call to SUMMARIZECOLUMNS function that should be 
			used to calculate groups of subtotals
ROLLUPISSUBTOTAL		Pairs up the rollup groups with the column 
SELECTCOLUMNS		Returns a table with selected columns from the table 
			and new columns specified by the DAX expressions
SUBSTITUTEWITHINDEX		Returns a table which represents the semijoin of two 
			tables supplied and for which the common set of 
			columns are replaced by a 0-based index column. 
			The index is based on the rows of the second table 
			sorted by specified order expressions.
SUMMARIZECOLUMNS		Create a summary table for the requested 
			totals over set of groups.
GEOMEAN			Returns geometric mean of given column 
GEOMEANX			Returns geometric mean of an expression 
			values in a table.
MEDIANX			Returns the 50th percentile of an expression 
			values in a table.
PERCENTILE.EXC		Returns the k-th (exclusive) percentile of 
			values in a column.
PERCENTILE.INC		Returns the k-th (inclusive) percentile of 
			values in a column.
PERCENTILEX.EXC		Returns the k-th (exclusive) percentile of an 
			expression values in a table.
PERCENTILEX.INC		Returns the k-th (inclusive) percentile of an 
			expression values in a table.
PRODUCT			Returns the product of given column reference.
PRODUCTX			Returns the product of an expression 
			values in a table.
XIRR			Returns the internal rate of return for a schedule of 
			cash flows that is not necessarily periodic
XNPV			Returns the net present value for a schedule of cash flows

Plenty of material for future blog posts there, I think – there are lots of functions here that will be very useful. I bet Marco and Alberto are excited…


We now have support for working with Power Query in VBA.