Create a function library in Power BI using M-Extensions

Having the ability to use own M-function the same way than native functions in Power BI and Excel has been one of my biggest wishes for quite some time. So I was more than amazed to see Frank Tonsen’s comment showing a way to do exactly this in PowerBI, that has been available for almost half a year now: M-Extensions as part of the custom connectors.

Unlike custom connectors who show up in the import-dialogue and provide a custom tailored option for importing data or creating queries, M-Extensions don’t show up explicitly anywhere in Power BI: They just do their M(agic) job to make the functions that you’ve defined in them accessible, as if they were inbuilt native functions: Type their name into the formula bar like this (1):

And enjoy the function description (2: if you’ve specified it in the definition, which is optional):

Simplest example

  1. Your functions: Number.Double and Number.Triple
  2. Combined with the keyword “shared” and separated by “;”
  3. Prefix by “section MyLibrary” gives this text:
section MyLibrary;
shared Number.Double = (Number as number) =>
2 * Number;
shared Number.Triple = (Number as number) =>
3 * Number;

 

How to make M-Extensions work

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How Power Query can return clickable hyperlinks with friendly names to Excel

When you use Power Query as an Excel-automation-tool rather than just to feed the data model, you might want to return clickable hyperlinks that carry friendly names. This doesn’t work out of the box, but with a little tweak it will be fine:

The trick

Return a text-string that contains the Excel (!)-formula for hyperlinks, preceded by an apostrophe  ‘ . After the data has been loaded to the sheet, check the column and replace ‘= by = to activate your Excel-formula:

Activate the HYPERLINK formula by replacing ‘= with =

You can then format the column to “Hyperlink”:

Format as Hyperlinks

And make sure that future refreshes are automatically formatted as well:

Make sure format sticks

This of course works with all other excel-formulas as well. So if you’re still struggling a bit to calculate your numbers in Power Query, you can simply create a column that holds your Excel-formula which you “activate” by the replacement 🙂

The formula

This formula creates the new column, bringing in the content of columns “URL”  and “Friendly Name” to the Excel-formula:

Table.AddColumn(Source, “ExcelLink”, each “‘=HYPERLINK(“”” & [URL] & “””, “”” & [Friendly Name] & “””) “)

Quotation marks and escape signs

You’ll probably notice the multitude of quotation marks: Quotation marks are used in M to indicate that a text-element is following and will also be used at the end of a text-element. In that context, they are called “escape signs”. So what happens when your text ends with a quotation mark like here: ‘=HYPERLINK(” ? How to prevent the ending quotation mark to be mistaken as escape signs and returning: ‘=(HYPERLINK ( , so cut off the last quotation mark? You add 2 additional quotation marks: That will keep one of it in the text-string.

Subscribers  can download the file here: ClickableHyperlinks.xlsx

Enjoy & stay queryious 🙂

How to create and use an R-function-library in Power BI

Edit 10-10-2017: There is also a (simpler) way to run a custom function library described here: http://www.thebiccountant.com/2017/10/06/create-a-function-library-in-power-bi-using-m-extensions/ . If you go that route, the only point of interest in the article might be how to create your function library automatically.

Once you’ve discovered the huge potential R gives you to expand your analytical toolbox in Power BI (check some tips & tricks in my previous blogpost if you haven’t already), you might wish to have all your awesome functions conveniently at hand when designing new solutions. And thanks to M, there’s actually nothing easier than that: R-function-library in a record (which works just the same for M-functions 🙂 )

Put your functions into a record (fnr) with the function name as the field name and the function itself as the value: One query to hold them all (and not cluttering your editor pane) and ready to use as if they were native functions:

R-function-library

Use

will export content of my query “Actuals” to csv-file on my desktop.

  1. fnr is the name of the record. You can give it your own name of course, I prefer to keep this as short as possible.
  2. followed in square bracket is the name of the function (record field name)
  3. in ordinary brackets you have the function arguments just like in standard M (record value)

Create record

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How to import from Excel with cell coordinates in Power Query and Power BI

There might be occasions where you want to import data from Excel into Power Query or Power BI using cell coordinates like a range from E3 until G9 for example (“A1 cell reference style”). The function I provide below also caters for the potential pitfalls of this task that Maxim Zelensky has described in his article.

Background

If your worksheet has one leading empty row and column, the import will ignore them and automatically return the range starting from B2. So to fetch the range E3:G9 you have to delete the first row and the first 3 columns. But as Maxim has found out, remaining formats on empty cells will lead to an import of empty rows and columns. So the number of rows and columns to delete will vary and is hard/impossible to predict.

Method

The range that PowerQuery or PowerBI will import is stored in the Excel-file already in the sheet-data and the xml looks like this (“Sample3” from Maxims data):

The imported range is E1 till J12, as the first rows contain formatting instructions, and will therefore be imported as well. In the 3rd row E3 shows up with the first value, which is surrounded by “<v>”.

This is how it looks like in the Xml.Table in the query editor:

Task is to calculate the number of rows and columns delete, considering the individual offset that is caused by the formatted empty cells.

Code

So I’ve cooked together these ingredients in a pretty massive code that you can download here: fnImportFromExcelCellCoordinates.txt

How to use the function

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Should we pipe M?

“Just because you could doesn’t mean you should”… So I’m asking the Power Query and M fans & experts here if we “should” pipe M:

Background: With M you can nest your expressions like in Excel to group commands that belong together. But this has some disadvantages like:

  • Reading:
    • the execution order of the functions doesn’t match the reading order
    • the function name and the arguments are torn apart
  • Writing:
    • if you write an additional function around the existing expression which then fails, it is very laborious to manually delete all the code to go back to the previous state (especially, if you have trailing function arguments)
    • if you later recon that you need an intermediate step of the nested expression and need to split up the statement, the same problems occur

So instead of this code:

we could write it like so:

This code works in M if you have a record (“M”) in your queries that contains Kim Burgess’ cool code and an additional record (“M”) that he has kindly helped me with:

All that still folds!

Honestly, it doesn’t look pretty in my eyes (yet), but it works and eliminates the disadvantages mentioned above. With some help of Expression.Evaluate, we could further clean it up to match the magrittr-style for example, but I’ve been warned to use this function, so not sure what to prefer at the end.

Please let me know your thoughts & stay queryious 😉

File to download: ShouldWePipeM.zip

How to expand a column that cannot be expanded in Power BI and Power Query in Excel

Especially when working with JSON-data, you might end up with a column that has elements of mixed types in it. The expand column – arrows will be missing, but some elements still need to be expanded, like here:

But there is an easy way to fix it:

Transform to expandable column

Table.TransformColumns(Source, {{“Column1”, each if Value.Is(_, type list) then _ else {_} }} )

It transforms the “Column1” from table “Source” by checking, if the content of the each row ( _ ) is of type list and if yes, keep that value ( _ ) and if not, transform it to a list (by framing it into curly brackets {_} )

Syntax for tables

Table.TransformColumns(Source, {{“Column1”, each if Value.Is(_, type table) then _ else #table({“Column1”}, {{_}} ) }} )

Syntax for records

Table.TransformColumns(Source, {{“Column1”, each if Value.Is(_, type record) then _ else [a=_] }} )

File for Subscribers to download: HTExpandColumnThatCannotBeExpanded.zip

This technique should be applied to columns where the expandable elements all have the same structure. If that’s not the case, you should use this technique instead.

Enjoy & stay queryious 😉

Non-linear Break-Even Analysis in PowerBI

A break-even analysis tells you at which value of the parameter in question your profit-calculation will turn positive (link). Here we need to sell at least 173 at a given price of 20 before we’ve recovered all our costs:

If your variable costs are constant, you can solve it by this formula:

BreakEvenQuantity = Total Fixed Costs / (Unit Sale Price - Unit Variable Costs)

You’ll find tons of examples on how to do this in Excel like here .

Non-linear cost structure

But in real life, the variable costs often depend on certain quantities as you get discounts for purchasing large amounts. The following table shows a cost structure with fix costs in row 1. The 3rd column “FixOrQty” indicates if the cost item is fix or dependent on the quantity (Qty). The 2nd row contains a variable cost that is constant with 2 for all quantities. Row 3&4 show a variable cost of 8 for quantities up to 100 and if you purchase more than 100 the costs will be lowered to 2 for all additional quantities. Row 5-7 have a similar structure, but with 3 quantity ranges:

 Solve with goal-seek algorithm

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KPIs in Easy Profit and Loss for PowerBI

Welcome to the last part of my Easy Profit & Loss series where I will cover KPIs in rows & columns:

1) KPIs in columns

Show all your figures as a percent of turnover for example: Nice & easy: Divide current figure by the total sum of turnover:

Turnover% =
ABS (
    DIVIDE (
[ActSign],
        CALCULATE (
[ActSign],
            FILTER (
                ALL ( IndividualAccountsLayout ),
IndividualAccountsLayout[Description in Report] = “Income”
            )
        )
    )
)
DAX Formatter by SQLBI

We need to leave the current row context to retrieve the turnover-value in each row, therefore the ALL.

2) KPIs in rows

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Automatical or Bulk- Rename Columns in Power BI and Power Query

Edit 7th Feb 2017: Friendly reader Roknic pointed out in the comments below that there’s actually an existing function for it in M: Table.TransformColumnNames 🙂

So the first of my example below would actually look like this:

Table.TransformColumnNames(Source, each Text.Replace(_, " ", "_"))

But still keeping my original post here, as the transformations in them might help for other use cases:

If you want to rename all of your table’s columns with a common rule, like “replace all spaces by underscore” or just “delete all spaces”, check out this easy method:

The above formula will replace all spaces (” “) by underscores (“_”).

How does it work:

The 2nd argument in the Table.RenameColumns-formula is a list of lists, just like in Table.TransformColumnType from this article. So we apply the same technique here: List.Transform transforms a single element from a list into a list-item, whose 2nd argument will be calculated with a Text.Replace-function.

Variations:

Rename Columns Variations

Only replace FirstN or LastN elements from the column names:

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Conditions in FirstN, LastN and other xN-functions in M, PowerBI and Power Query

Today I discovered that we can use conditions in many of the N-selecting functions where one/I would normally expect just a number-expression for the N:

Table.RemoveFirstN( table as table, optional countOrCondition as any)

So apart from being able to select a certain number of rows to be removed, we can pass a condition (as function). This condition will iteratively be checked for every row in the table (from top or bottom) and as long as every (next) step returns true, the resulting range will be removed. So as soon as one row breaks the condition, the process will stop.

I find that totally awesome, as we can now remove all top-rows who have an empty field in Column3 like this for example:

Table.RemoveFirstN(<MyTable>, each each (_[Column3] = null or _[Column3] = “”))

Yes, this will remove the first sequence of consecutive nulls in the table. So all other rows with nulls in the table coming later after a non-null value has “broken in”, will remain.

This is the list of function, where you can use this M-agic:

Enjoy & stay queryious 🙂