DAX CALCULATE Debugger

CALCULATE is the most powerful function in DAX, as it allows you to change the filter context under which its expression is evaluated to your hearts content. But with big number of options to choose from, often comes big frustration when the results don’t match expectations. Often this is because your syntax to modify the filter context doesn’t do what you’ve intended. Unfortunately CALCULATE only displays its result and not how it achieved it, so debugging becomes a challenge. This is where my CALCULATE Debugger measure can help out:

DAX CALCULATE Debugger

This is a measure that returns a text-value, showing the number of rows of the adjusted filter context table, the MIN and MAX value of the selected column as well as up to the first 10 values. Just place this measure beneath the CALCULATE-measure in question and try to find the error 😉

Just have in mind, that this only works for standalone CALCULATE-functions and not for those who are nested in other functions (who modify the evaluation context).

The YTD-measure is defined as follows:

YTD = CALCULATE ( [Amount], DATESYTD ( 'DimDate'[Datum] )

The code for the DAX Debugger measure looks like this:

In row 2 you fill in the filter expression from the YTD-expression (2nd argument: ‘DimDate'[Datum]). You can choose from which column the values shall be shown, just write that in rows 6, 7 and 11 ([Datum]). If you want to adjust the TOPN-figure for the sample values to be shown, replace the 10 in row 9 accordingly. If you don’t want to show sample values at all, just uncomment row 13 and comment out row 14 and 15.

Thanks to Tom Martens for providing the crucial hint of how to reference a column from a table that’s defined in a variable by using X-functions!

Further adjustments have to be made, if your filter expression uses the syntax sugar of boolean expressions like so:

CALCULATE ( [Amount], Product[Color] = "Red" )

This expression only returns a table when used as a filter argument in CALCULATE but not standalone in a DAX variable. So you’d have to translate the filter expression to the native underlying code like so:

FILTER ( ALL ( Product[Color] ), Product[Color] = "Red" )

As this cries for some automation, I’ve produced some nifty M-function that does all that autoMagically. It lives in my M-function-library so I have it at hand within PowerBI for immediate use.

The M-function

This function creates the DAX-code in the query editor. Just fill in the parameters (see below) and the DAX code will be created automatically: Just copy and paste as a new measure.

How to fill the parameters:

  1. filterExpression: DAX-code of the CALCULATE filter expression
  2. myColumName. Name of the column whose values to show
  3. MaxFilter: This is a optional parameter: Fill in a different number from 10 if you want to change the default value for the TOPN selection of the sample values to be shown.

This function detects boolean expressions automatically and produces the appropriate code.

If you don’t know how to use M-function-code, please check out Ruth Pozuelo’s video.

Enjoy & stay queryious 😉

The full Table.ContainsAnywhere function for Power Query in Power BI and Excel

In a previous post I introduced the concept of a function that searches for an occurrence of a character or string within all columns of a table. Here I share the full “Table.ContainsAnywhere” – function with parameters for many useful options.

Function parameters and options

  1.  The first parameter “MyTable” refers to the table to search through
  2.  The 2nd parameter “MySearchStrings” can be either a text field or a list of strings to be searched for. The function will take care of any of these cases automatically.
  3.  If the 2nd parameter is a list and this 3rd parameter is null or not speified, the function will return true if any of the list items is found within the table. But if set to “All”, all list items have to be found somewhere in the table for the function to return true.
  4.  By default, the search will be made in a case sensitive mode (as this is the default-mode in Power Query). But any entry into the 4th function parameter will turn this to a case insensitive mode instead.
  5.  By default, the string or list entry has to match fully with any entry in the table. Again, any entry in the 5th parameter swaps that to a partial match.

Function code

I encourage friends of the M-language to read through the documented code of the “Table.ContainsAnywhere”-function. It shows a fairly compact way to handle the 24 different functions that are needed for all possible function parameter combinations. For each parameter, I created one function module that covers the part of the function-logic that is specific to this parameter. These function modules also carry the case selection already. So they will deliver just what’s needed to the main query part (2), where they can then be executed sequentially. This way I avoid heavy branching with if-then-else-statements and redundant code.

Enjoy and stay queryious 😉

A new Table.ContainsAnywhere function for Power Query in Power BI and Excel

The native Table.Contains-function in Power Query tells you if one or more strings are included in one or more of its columns. But you have to be specific about which strings you search in which column. But what to do if you want to search a string in all of its columns instead? Use my new Table.ContainsAnywhere function.

Problem

In the native function, you have to pass in a record with search term and column name. So if you search for “blue” in column “Description”, your formula would look like so:

Table.Contains( YourTableName, [Description = "blue"] )

But that’s not what I want in this case. I want the formula to search through all columns within the table for the occurrence of “blue”.

Solution

One way would be to transform the list of column names of the table to a nested list where for each column name, the search-string would be added. But that gets a bit clumsy if you want to use it in a Table.AddColumn-step. So I’m going a different path instead:

Say this is my table and I want to know if the string “INCOME STATEMENT” is included in any of its fields:

Table to search all columns for a specific string

 

1. Split the table into a list of lists where each list contains all fields from one row:

Table.ToRows(Source)

Table.ToRows creates one list per row in a nested list

2. Combine that list into one, means you have all fields of the table in one big list:

List.Combine(Table.ToRows(Source))

Combine list of nested list into one (expanded) list

3. Check if this list contains the search term:

List.Contains(List.Combine(Table.ToRows(Source)), "INCOME STATEMENT")

Use cases

I’m using it to catch some specific tables from SEC-filings for example. This is the result of a Pdf.Tables-function to extract quarterly report data from a large pdf file. It shows all the different page- and table elements in it:

Table.ContainsAnywhere function in action

I’ve added a column with the function above and can now filter on “true” to extract the matching tables.

Variations

You want an case-insenstive match? Or search for multiple strings? And be able to distinguish between any and all-matches? Or even go for partial matches?

Then watch out for the next article where you get the function with all bells and whistles.

Enjoy & stay queryious 😉

Bulk-extract Power Query M-code from multiple Excel files at once

Some time ago I published a function that extracts all M-code from Power BI (.pbix)-files. Today I publish the pendant to Bulk-extract Power Query M-code from multiple Excel-files at once. The code contains many elements from the before mentioned, so please refer to that article for reference.

How to use

The function below has just one parameter where you either fill in a full filename (incl. path) of an Excel file, or a folder path where multiple files reside. The function will automatically detect the right modus and spit out the M-code. Read more

Export data from Power BI to csv using Python

In this blogpost I show you my M-Python-function that I use to export data from Power BI to csv files (Export Python).

Why Python?

I prefer it to R mostly because I don’t have to create the csv-file(names) in advance before I import data to it. This is particularly important for scenarios where I want to append data to an existing file. The key for this task is NOT to use the append-option that Python offers, because M-scripts will be executed multiple times and this would create a total mess in my file. Instead I create a new file with the context to append and use the Import-from-folder method instead to stitch all csvs back together. Therefore I have to dynamically create new filenames for each import. So when the M-Python-scripts are executed repetitively here, the newly created file will just be overwritten – which doesn’t do any harm.

Read more