Making Sense Of Subtotals Settings In The Power BI Matrix Visual

For showing data, the Matrix visual is one of the most popular visuals, and most comfortable for Excel users since it looks a lot like a Pivot Table. Showing subtotals the way you want though can be a bit of a challenge simply because there are so many settings in the Formatting pane in different sections.

Lets quickly look at a few examples before doing a deep dive. This is how a default matrix looks with just a few fields. It has two rows (Year and Month Name), one column (Category), and one value (Total Sales).

20190421 - Default Matrix.png

Ideally, there would be one place to change all of the settings for a Matrix visual for the subtotals, but there isn’t. The settings are split among at least three sections in the formatting pane, and changing some settings in one area will automatically change other settings in other sections. So it can be a bit tedious to get it to look like you want. The good news is the Power BI Desktop editor gives you a lot of control. You just have to know where to look.

When you add a Matrix visual, it defaults to a stepped value, putting the subtotals next to the first row, or Year, in the example we’ll work through. (See the first image in this post.)

If you prefer the totals at the bottom, select the formatting pane for the visual, scroll down to the Subtotals section, and looks for “Row subtotal position” and change it to “bottom.”

20190421 - Default Matrix subtotals on Bottom.png

This leaves a blank row though next to the Year row, and adds a new “Total” row description. It isn’t the most efficient use of space, but it makes more sense to many people to always have totals at the bottom.

If you don’t like the stepped format where the months are indented a bit, you can turn your matrix into more of a table format turning Stepped Layout off. Go to the Rows Headers section, and turn Stepped Layout off. Note that when you do this, it will automatically change the Subtotals/Row subtotal position setting to Bottom. You can change it back to top if desired.

20190421 - Matrix in Table Format.png

Now the subtotals are at the bottom, but you no longer have the blank row by the Year field as it moves the Months Names to the next column. This is similar to switching a Pivot Table view in Excel to Table Format.

Let’s step back for a minute though and look at the major places in the formatting pane to change how subtotals can be displayed.

  • Row Header section

    • Stepped Layout - turn on or off. Think of this in Excel terms as as a table format (off) or classic Pivot Table format (on). Examples are shown above in the first two images.

    • +/- icons - turn on or off. Here you can turn the +/- expand/collapse icons on or off to allow your users to drill down at each row subtotal. This provides very granular control for your end user. See image 1 below to see how this looks.

      • As of the April 2019 build of Power BI, the +/- only affects rows. The Matrix visual cannot yet collapse/expand columns. Go to this UserVoice request to vote for this feature.

  • Values section

    • Show on rows - turn on or off. This only applies if you have two or more fields or measures in the Values section. See Image 2a and 2b below for an example of this. It changes how rows are displayed, which also impacts how subtotals are shown.

  • Subtotals section

    • Row subtotals - turn off or on. This will globally turn subtotals off or on for the entire matrix.

    • Row subtotal position - top or bottom. This will show the subtotals above (top) or beneath (bottom) the detailed data. The Row Header/Stepped Layout setting may change this setting automatically.

    • Per row level - this will allow you to turn off or on subtotals for each level. See image 3a and 3b below for examples.

Image 1 - +/- icons

Image 1 - +/- icons

In images 2a and 2b below, there are multiple values in the Values section. This example has both Total Sales and Total Units. If you just have two values, showing in columns might work but it is often better to switch them to rows as shown in 2b below. If you have three or more fields in the Values sections, showing on rows is usually the better way to go.

Image 2a - multiple values in columns

Image 2a - multiple values in columns

Image 2b - multiple values in rows - Values/Show On Rows turned on

Image 2b - multiple values in rows - Values/Show On Rows turned on

If you want some subtotals, but not at every level, change the setting in the Subtotals section, Per row level settings. If Per row level is set to off, you’ll have subtotals on or off for every row you have data in. So in this example, it means subtotals at the Year, Month, and Group level.

  • Image 3a - Subtotals are on, Per row level is off. This means for every field you have in the Rows section, you’ll have a subtotal

  • Image 3b - Per row level is on, and I’ve turned off the “Group” level, so there are subtotals for Year and Month.

  • Image 3c - Per row level is on, and I’ve turned all subtotals off except the “Group” level.

Image 3a - Subtotals at every level

Image 3a - Subtotals at every level

Image 3b - Subtotals off for Group

Image 3b - Subtotals off for Group

Image 3c - Subotals on for Group, off for Year and Month

Image 3c - Subotals on for Group, off for Year and Month

The Matrix visual is very flexible. It is likely possible to get it to show the subtotals you want, but you have to play with several different sections in the Formatting panel and understand how they interact with each other.

PS. There is another UserVoice request to show more that just the word “Total” when there is just one field in the Values section. Go here to read more about it and vote for it.

Create A Dynamic Date Table In Power Query

Most Power BI and Power Pivot (Excel) reports require a date table so time intelligence functions can calculate correctly. I’m going to show you how to quickly set up a date table in Power Query, one that will be dynamic. The starting and ending dates will move with your data over time. And because it is in Power Query, it will be an imported table which is what Power BI loves most, being more efficient than a table created in DAX with calculated columns.

You can download the Excel sample data and Power BI file at the bottom of this article if you want to follow along step by step.

First of all, we’ll create a static table to get the query set up, then modify it so it is dynamic. The fastest way I’ve seen to create a dates table in Power Query is to start with the one line statement shown below, which we’ll put in a Blank Query. In Power Query in Power BI, it is on the home menu, New Source, Blank Query. In Excel, it depends on the version you have.

Office 365 versions and Excel 2019:

  1. Data tab in Excel

  2. Get & Transform Data section of the ribbon

  3. Get Data dropdown menu

  4. From Other Sources

  5. Blank Query

In Excel 2016 and earlier, you will need to open the Power Query window first. This also works in Office 365 and Excel 2019 if you are already in Power Query.

  1. On the Home tab, select New Source

  2. Other Sources

  3. Blank Query

20190317 - Static Date Table.png

Now you have a blank query called Query1, with a Source in the applied steps (#1 in the above image), but nothing is there. In the formula bar, type the following (#2) and press enter:

= {Number.From(#date(2018,1,1))..Number.From(#date(2019,12,31))}

Let’s break that down:

  • Lists are defined in Power Query by enclosing them in what I call squiggly brackets, but are also known as braces or curly brackets. { }

  • When used with numerical data, if you have two periods between the first and second number, it will generate a list of all numbers between those numbers. So {1..10} would generate a list of numbers from 1 to 10.

  • My first number is Number.From(#date(2018,1,1)). This returns 43101. That is the same thing You’d get in Excel if you typed 1/1/2018 in a cell, then formatted it as a number.

  • My second number is 43830, the numerical value of December 31, 2019.

  • The total list has 730 numbers, 43101 - 43830, which is two years of data. Perfect. No skipped dates.

Now we need this to be a table of dates, not a list of numbers. Let’s fix that.

  1. Click the “To Table” icon (#4) in the tool bar. In the To Table dialog box, leave the defaults of “None” for the delimiter and “Show as errors” for extra columns. There are no delimiters or extra columns here, so there won’t be any issues.

  2. For the data type where it says ABC/123, click that and change it to Date. This is the tiny box below with the arrow pointing to it in the image below.

  3. Rename the column to Date.

  4. Rename the query to Date.

  5. Right Click on the query and make sure Enable Load is checked.

20190317 - Date Column.png

At this point, it is a valid date table, but quite spartan, and it isn’t dynamic. First let’s make it dynamic so the date ranges move with your data. I’ve created some sample data that I’ll use for this. I want my date table to encompass the earliest data from my Sales table so all of my sales history is covered, and I want the latest dates in the table to handle dates in the Open Purchase Orders table, which has expected receipts of merchandise well into the future.

A couple of rules about Date tables first:

  • The dates must be contiguous. There can be no gaps. Even if your business doesn’t operate on the weekends or holidays, those dates cannot be missing from your table. The way the data was created using a List ensures no dates are skipped.

  • You should almost always include the full year for any date in your table. So if your data has Jan 1, 2019 in it, you should have all 365 days of 2019 in your date table. I am working with calendar years in this example. If you have a fiscal year, that is fine, but your data should still encompass a full fiscal year. So if your year is July 1 through June 30, if you have July 1, 2019 in your dates table, you should have all dates through June 30, 2020, a full fiscal year.

So how do we make this dynamic? We need to figure out what the earliest date is in the sales table, since that table is going to have the oldest data for sales history, and we need to know the latest date will be based on the last date in the OpenPOs table.

20190317 - Earliest Date.png
  1. Right-click on the Sales table make sure “Enable Load” is not checked. You’ll see why in a minute.

  2. Right-click again on the Sales table and select “Reference”. We now have a second query that is identical to the Sales table, because it is simply pointing to the Sales table. Any changes to the Sales table will affect this new query, which is probably called Sales (2) at this point.

  3. Rename Sales (2) to pmEarliestDate. I recommend you put no spaces in the name as that complicates things later on.

  4. Right-Click and ensure “Enable Load” is not checked. Not only is there no need to load this, it will create an error as lists cannot be loaded into Power BI or Power Pivot.

  5. Select the Date column (#1 in the above image)

  6. On the Transform tab, select Date (#2), then Earliest (#3).

Now we have the earliest date as a list. A single item list. In my sample data, it is Jan 2, 2015. Jan 1 was a holiday, so I didn’t expect any data there, but remember, I need to make this a full year, so let’s tweak the formula that was generated by Power Query.

  1. Power Query used the List.Min() function to the earliest date. List.Min(Source[Date])

  2. We need to extract the year first, so wrap that in Date.Year(). Now it is just 2015.

  3. Now convert it back to a date, starting with January 2. Wrap step 2 with #date(year,1,1). The final formula is:

= #date(Date.Year(List.Min(Source[Date])),1,1)

If you were on a fiscal year, you’d need to do a bit more math to get this to July 1, 2014, for example, but still pretty easy to do. You’ve probably figured out by now that #date() is the same things as DATE() in Excel, taking year, month, and day for the arguments.

Now, we need the last date. I’ll repeat the steps above on my OpenPOs table’s date column, but instead of the Earliest date, I want the Latest date. My final formula is:

= #date(Date.Year(List.Max(Source[Expected Receipt Date])),12,31)

This will give me a date of Dec 31, 2020 since the latest date in that table is Mar 31, 2020. Note this time Power Query used the List.Max function to get the latest date in the table.

Now I know my first and last date, and both are calculated dynamically. If dates in my source tables change, so to these two parameters.

So how do we make the Date table we created use these dates? Remember our original Date table started with this Source line:

= {Number.From(#date(2018,1,1))..Number.From(#date(2019,12,31))}

We need to edit that formula a bit. We just get rid of the hard coded dates, and replace with our dynamically calculated dates. It becomes this:

= {Number.From(pmEarliestDate)..Number.From(pmLatestDate)}

Now we have a date table with 2,192 consecutive dates from Jan 1, 2015 to Dec 31, 2020, with leap years accounted for automatically for us.

So why did I create a reference from both the Sales and OpenPOs table, and ensure those original table are not loaded? Now I can tweak my date ranges in those original tables, and the dynamic dates will account for it. So if my actual sales table has history going back to 1995, I can filter that in the original sales table to be 2015 and later if I want, and my actual data and Date table will reflect that.

Same thing with my OpenPOs table. I’ve seen companies put fake data, say Dec 31, 2999, for things like blanket POs, or some future forecast, or whatever. I don’t want a date table or actual data going out that far, so I limit it to realistic date ranges in the OpenPOs table with a filter on the Date column.

To load relevant data, I need to create two more references:

  1. Create a reference from Sales, and call it Sales Data.

  2. Create a reference from OpenPOs, and call it Open Purchase Orders.

  3. Makes sure “Enable Load” is checked for both of these.

  4. At this point, in both tables, you can do any further transformations, such as removing columns, grouping data, or whatever you want. Because these transformations are on references to original Sales and OpenPOs table, the original tables are unaffected, and the Date table will be unaffected, which is what you want.

It can help to see how the queries are related to each other. Click on the View tab in Power Query, then Query Dependencies. You should see something similar to this:

20190317 - Query Dependencies.png

You can see how the calculation of the earliest date, pmEarliestDate, and the Sales Data query both come from the original Sales query, but changes in the Sale Data query will not affect the date calculation. You can also see which queries are loaded into Power BI from here, and which have the load disabled.

Finally, I need to enhance the Date table. Right now, it is just dates. But to have rich reporting capabilities, we need things like month names and numbers, quarters, years, etc. I’ll create a few as a place to get started:

  1. Select the Date column in the Date table, then on the Add Columns tab, select Date, Month, Month. This gives us the month number.

  2. Select the Date column, Add Columns, Date, Year, Year.

  3. Select the Date column, Add Columns, Date, Month, Name of Month

You get the idea. Now let’s add a few things that you cannot do through the tool bar. We are going to add a column that will give us the Month and Year in the format of MMM-YY, so Jan-15, Feb-15, Mar-15, etc. This is handy for a number of visuals.

  1. Add Column

  2. Custom Column

  3. Name the column MMM-YY

  4. Type in the following formula:

=Text.Start([Month Name],3) & "-" & Text.End(Text.From([Year]),2)

Make sure to set the type to Text so it isn’t the Any data type (the ABC/123 type)

Now, if you know anything about creating charts or tables in Power BI and Excel, that column will sort alphabetically, which is useless, unless you want April to be before January. Of course you don’t. So we need to create a sorting column for this. Add a new column, call it “MMM-YY Sort” and add this formula:

=[Year]*100 + [Month]

This will create a column that will have 201501, 201502, 201503, etc to correspond to Jan-15, Feb-15, Mar-15, etc. You can use this column to sort your MMM-YY sort. Lastly, change this column to a Whole Number format.

At this point you can add dozens of more columns depending on your date needs. Quarters, weeks, ISO 8601 formatted dates, etc. But in our simple example, this is a really short query, and is fully dynamic. In the Advanced Editor, it would look something like this:

    Source = {Number.From(pmEarliestDate)..Number.From(pmLatestDate)},
    #"Converted to Table" = Table.FromList(Source, Splitter.SplitByNothing(), null, null, ExtraValues.Error),
    #"Changed Type" = Table.TransformColumnTypes(#"Converted to Table",{{"Column1", type date}}),
    #"Renamed Columns" = Table.RenameColumns(#"Changed Type",{{"Column1", "Date"}}),
    #"Inserted Month" = Table.AddColumn(#"Renamed Columns", "Month", each Date.Month([Date]), Int64.Type),
    #"Inserted Year" = Table.AddColumn(#"Inserted Month", "Year", each Date.Year([Date]), Int64.Type),
    #"Inserted Month Name" = Table.AddColumn(#"Inserted Year", "Month Name", each Date.MonthName([Date]), type text),
    #"Added MMM-YY" = Table.AddColumn(#"Inserted Month Name", "MMM-YY", each Text.Start([Month Name],3) & "-" & Text.End(Text.From([Year]),2)),
    #"Added MMM-YY Sort" = Table.AddColumn(#"Added MMM-YY", "MMM-YY Sort", each [Year]*100 + [Month]),
    #"Changed Type1" = Table.TransformColumnTypes(#"Added MMM-YY Sort",{{"MMM-YY Sort", Int64.Type}, {"MMM-YY", type text}})
    #"Changed Type1"

The final step is once this is loaded, close Power Query and set this as your date table for Power BI:

  1. Make sure automatic date logic is off in Power BI. Select File, Options and Settings, Options, Data Load. Uncheck “Auto Date/Time”. Leaving this checked will create all sorts of unnecessary hidden tables and columns. You’ve created a perfect Date table. Don’t let Power BI’s AI mess this up.

  2. In the Visual view, right-click on the Date table, and select Mark as Date Table, then select the Date column.

  3. It will validate it by ensuring you have no skipped or duplicate dates. Press Ok.

Now you can start creating your visuals, measures, etc. in Power BI, or pivot tables in Excel. As data is updated from your source system, your Date table will dynamically expand. This is handy as you would never have to edit the date range in the table and republish the report. The Power BI service will refresh all of the data, including calculating the ever-expanding date range as sales and purchase orders continue to happen into the future.

Below are the two files I used in my example, the PBIX file and the Excel XLSX file with the sample source data.

Power BI Dynamic Date Table

Excel Sample Source Data

Calculate Last Twelve Months Using DAX

One of the more common calculations a company uses is the last twelve months, or LTM, of data. This can be tricky if your date table always has a full year of dates for the current year, which it generally should. So if today is March 3, 2019, my date table will have dates through December 31, 2019. This is usually necessary for the date intelligence functions in DAX to work properly, and companies may have data beyond today in their model. For example, budget and forecast data will generally extend through the end of the year, or at least beyond today.

However, it often is challenging when you are trying to hide these future dates for specific measures. I’ve seen solutions that use functions like LASTNONBLANK() that get the last date with sales data in it, and that can work, but depending on how your data is laid out, it can make for larger and more complex measures with multiple FILTER() functions. For a visual you can sometimes use the relative filtering feature, but that won’t change the underlying value of the measure if you reuse it in another visual or refer to it from another measure.

Marco Russo recently wrote an excellent post on hiding future dates or calculations in DAX. The concept is brilliantly simple. Just add a column to your date table that returns TRUE if the date is today or earlier, or FALSE if it is after today, then use the CALCULATETABLE() function to return just a table of dates that fall in that TRUE range of dates.

That wouldn’t work for me though exactly as it was presented. I needed to create dates that were in the previous 12 calendar months, and I was working with a Power BI Dataset, which is a Live Query, and you cannot add columns to Live Query models.

20190303 - No New Column SSAS.png

So I opted to create two measures. First, I needed to create the date logic in my dates table. I wanted the previous 12 full calendar months, not the last 365 days of data. Note that my date table is named ‘Calendar’.

LTM Dates = 
VAR EndDate =
    EOMONTH ( TODAY (), -1 )
VAR StartDate =
    EDATE ( EOMONTH ( TODAY (), -1 ), -12 ) + 1
    IF (
        MAX ( 'Calendar'[Date] ) >= StartDate
            && MAX ( 'Calendar'[Date] ) <= EndDate,
        TRUE (),
        FALSE ()

This measure has two variables:

  1. EndDate - This calculates the last day of the month for the previous month based on TODAY().

  2. StartDate - This calculates the month 12 months prior to the EndDate, then adds one day to move to the first day of the next month.

Finally the measure uses a basic IF() statement, with some AND logic. If today is March 3, 2019, it will return TRUE for the dates March 1, 2018 through February 28, 2019. For dates before March 1, 2018, and after February 28, 2019, it returns FALSE. It will do the for the entire month of March. On April 1, the LTM range becomes April 2018 - March 2019.

I could have used the AND() function instead of the double ampersand, but I use the double ampersand as I can use multiple conditions, like condition1 && condition2 && condition3, whereas AND() is limited to two conditions. By getting in the habit of using &&, I never have to remove an AND() function and redo the syntax. Side note: Use double pipes to allow multiple conditions for OR logic. Condition1 || condition2 || condition3, as OR() is also restricted to two conditions.

Now I needed to calculate sales for LTM. I already had the [Total Sales] measure below:

Total Sales = 

The measure for [Sales LTM] then is:

Sales LTM = 
    [Total Sales],
            [LTM Dates] = TRUE()

You could combine my first measure with the second measure, replacing [LTM Dates] with the full measure, after tweaking the date logic in the FILTER() section a bit in this [Sales LTM2] measure.

Sales LTM2 =
VAR EndDate =
    EOMONTH ( TODAY (), -1 )
VAR StartDate =
    EDATE ( EOMONTH ( TODAY (), -1 ), -12 ) + 1
        [Total Sales],
            FILTER (
                'Calendar'[Date] >= StartDate
                    && 'Calendar'[Date] <= EndDate

However, this measure is both a bit more complex, and if you wanted to have other LTM measures, such as units sold, or cost of goods over the last year, dollars purchased, etc., you’d have to repeat the date logic in each measure. If you wanted to change the LTM logic, say switch from previous 12 completed calendar months to last 365 days, or last 12 calendar months but starting with this month, you’d have to edit every measure calculating the date range. By breaking it into two parts as I’ve done above, I can edit just the [LTM Dates] measure and all other measures that use it will automatically recalculate accordingly.

Also note that unlike Marco’s solution, my date measure will not behave as a calculated column.

  1. You could not use it in an iterator function such as SUMX(), AVERAGEX(), and so on, as iterators use row context, and measures generally do not have row context. Well, iterator measures do, but they have to have row context to start with. They cannot create it out of thin air.

  2. You also cannot use measures in slicers or filters in your report. For those, you must use either a calculated column, or bring the column in through Power Query.

  3. You cannot use it as the date column in a date intelligence function, because it isn’t a column.

Calculated columns, and better yet imported columns via Power Query, can be a better choice for the above secenario, but that is not always an option if your source data is from SSAS or a Power BI Dataset where adding columns isn’t permitted.

Quickly Pad Columns in Power Query with Text

When working with data in Power Query, you often will need to pad either the beginning or ending of a column with specific text, especially if the final result will be data you export to a CSV file for uploading into a different system. Common examples include:

  • Some sort of “number” that needs to be padded with leading zero’s.

  • Labels that need to be padded with trailing spaces to ensure the cell contents are a specific length.

This can even be useful in Power BI if a report is designed to be exported by the end user to upload or otherwise use for input into a different system.

In Excel, you can do this in a worksheet cell with a formula. This will create a string 15 characters wide with trailing periods, assuming the text you want to convert to a 15 character string is in cell A1.


You can do the same in Power Query with the following formula, but this is not the easiest way.

Text.Start([Labels] & Text.Repeat(".", 15), 15)

The Text.Start() function is equivalent to Left() in Excel, and Text.Repeat() corresponds to REPT().

But there is a faster way to do this and the Power Query function name tells you exactly what it is doing.


Text.PadEnd() will cause the text value, [Labels] in this example, to be padded until it is 15 characters long. I used a period so you could see the results, though you’ll most often use a space. You can see the results are the same for Excel and Power Query.

20190224 - TextPad Start.png

I changed the font in the Power Query window to monospace so you could see the text is the same length with both methods. You can change to monospace on the View tab of Power Query.

Text.PadEnd() has 3 arguments:

  1. The text you are manipulating. This can be a single filed, or a formula that generates text.

  2. The length you want your field to be. Note that if the text is longer than the padded length, Text.PadEnd() will not truncate your data to your desired length. It will return the full length of your text, but with no padding as the string is already longer than the length you set.

  3. The text to pad with, which is optional. If you leave this off, it will use spaces, ASCII code 32. If you use two or more characters, it will result in an error. It must be a single character.

You can use Text.PadStart() to pad at the beginning. It works exactly the same way as its sister function Text.PadEnd().


As you can see, you only need to change from Text.PadEnd() to Text.PadStart(). Using the Excel method, you not only have to switch from the LEFT() to RIGHT() function, but change the order of the concatenation of the text in the formula, making sure not to mess up the Text.Repeat() function. The Excel method would be:

=Text.End(Text.Repeat("0", 15) & [Labels], 15)
20190224 - TextPad Start.png

In this way, Power Query is very much like Excel in that there is usually more than one way to do the same thing. I think using the Text.Pad* functions makes your code more readable, and easier to edit without having to nest multiple functions.

Intellisense in Power BI's Power Query Formula Bar

Late in 2018, the Power BI team added Intellisense to the Advanced Editor for queries in Power Query, only in Power BI. This has not yet come to Power Query in Excel.

In the February 2019 version of Power BI, that Intellisense now comes to the formula bar.

20190214 - Intellisense In M Language.png

To see this you have to enable two things:

  1. Turn on the Formula Bar in the Layout section of the View ribbon in Power Query. That should always be on by the way. Working without this is like disabling the formula bar in Excel so you cannot see the cell contents.

  2. In Power BI, go to File|Options & Settings|Options, and scroll down to the Preview Features. Check the “M Intellisense” checkbox. You’ll need to restart Power BI for this to take effect.

It still doesn’t have Intellisense in the Custom Column formula box, but we are getting closer. I suspect this feature came as a result of the recently announced “Improved Python & R Script Editor” in Power BI this month.