If you’re working with large data or complex queries that take a long time refresh, cancelling one of those refreshes can even take longer time, especially, if the query has run for quite some time already.
Luckily, there is an easy trick to cancel refresh without loosing the work you’ve done already:
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.
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
The following steps show how to create a new column in a table using existing custom function code. This works in Power BI as well as in Power Query in Excel:
Today I’ll present an adjustment to the Text.SplitAny – function in Power BI’s query editor or Power Query. The native function takes a string as an input and splits the text by every character that is contained in the string. This seems fairly unusual to me and I haven’t used that function very often.
But what I have come across fairly often is the requirement to split a string by a bunch of different (whole) strings (instead of single characters).
Recently I came across an interesting request where someone wanted to un-cumulate their quarterly YTD-figures (green) into their single quarters values (red) like so (“Unravel cumulative totals”):
Retrieve every Quarters Amount from the Quarter To Date values (“YAmount”)
To retrieve this value, one would have to start with the first value in the year. This is also the value of the first quarter, but for the 2nd quarter, one would have to deduct the value of the first quarter from the cumulative value of the 2nd quarter. So basically retrieving the previous cumulative row and deduct it from the current cumulative row. Do this for every row, unless it’s the start of the year or belongs to a different account code in this example:
I must admit that I had more than one unsuccessful attempt to try to fully understand how the List.Alternate-function works. What helped me at the end, was the function Table.AlternateRows. It pretends to be similar to List.Alternate, but holds some surprises that I will uncover in this blogpost:
Say I have the table below and want to retrieve just the letters that appear in every 2nd row:
Table.Alternate – Remove every other row
I find the dialogue that appears very helpful and intuitive:
It clearly is a removal operation and here I want to remove the 1st row from my table (“1”), and just one at a time. Also want to keep just one row (“A”) before the next one is removed (“2”) and so on.
In the formula bar, this step will be translated into this M-code:
Table.AlternateRows(Source,0,1,1)
If you would have expected it to be translated to: Table.AlternateRows(Source,1,1,1) instead, you might have forgotten that the M-language in Power Query starts to count at 0, so the first row to remove is expressed by the 0 here.
So if my input is a list instead of a table like below, I should expect a similar result than the sample above if I tweak the code a bit, shouldn’t I?
List.Alternate – produces a different result
But hey: What’s wrong here? Not a single element has been removed from the list !!
So let’s have a look into the documentation:
List.Alternate – Function Documentation
and compare it with the Table.AlternateRows documentation:
Table.AlternateRows – Function Documentation
Hm – at least we have one match here: The “offset” parameter is included in both functions. But it is the first (number) parameter in the Table-function and is at the last position in the List-function. So let’s move it around then like this:
List.Alternate – same result with different parameter order
There we are 🙂
So the order of the function parameters is different here. Also the other parameter names are different and their description. I find them much easier to understand in the Table function and of course, the function dialogue there helps to understand what shall happen as well.
Enjoy & stay queryious 😉