Date.DatesBetween to retrieve dates between 2 dates in Power BI and Power Query

Today I’m sharing a handy function with you that allows you to retrieve all or just a couple of dates between 2 given dates: Date.DatesBetween.

Usage

This function takes 3 parameters:

  1. From- or Start-date
  2. To- or End-date
  3. A selection of ONE of these intervals: Year, Quarter, Month, Week or Day

All dates will be created at the end of the chosen interval: So if you want to analyse events with a duration for example, where you want to transform your data to show one day per (monthly) event, this function generates month-end-dates for every month within the timespan. Please not that if the To-/End-date is within a month, the last element of the list will NOT be that day, but the day of the end of that month.

The default-value for the 3rd parameter is “Day”, so if you omit the specification, the function will return a list of all days in between.

Definition

How it works

This function uses Function.Invoke to create a compact code. In step “CaseFunction” (rows 12-18), a table is created that contains all the elements for a case-selection. The first column contains the case that is selected by the 3rd parameter. The other columns contain the functions and expressions for the cases.

Table with all different elements for each case

Step “Case”  filters that table down to one remaining record:

Case = CaseFunctions{[Case = TimeInterval]},

It uses a special row-selector { [NameOfTheColumn = Condition] } that only works for columns containing unique keys.

Step “DateFunction” has the command that creates the list of dates:

DateFunction = List.Transform({0..Case[NumberOfAddedTIs]-1}, each Function.Invoke(Case[LastDateInTI], {Function.Invoke(Case[TypeOfAddedTI], {From, _})} ))

Starting with creating a list with the length of the number of intervals (yellow). The next evaluation step uses  Function.Invoke (green): This allows us to work with the function name as a variable from our Case-record. So whatever has been selected for “TypeOfAddedTI” (Time Interval) will be executed with From and the respective number from our list as its parameter (like: Date.AddWeeks(From, 2) for the third item of the list if “Week” is selected. The last evaluation-step (orange) will be Function.Invoke(CaseLastDateInTI) which shifts every returned date at the end of its Interval (here: Date.EndOfWeek).

Of course, this coding style is a matter of taste, but I found it worth sharing.

Enjoy & stay queryious 😉

Right Aligning Text in Power BI: Format Improvements for Easy Profit&Loss Reports

As shown in my last part of the Easy P&L-series, Power BI unfortunately still lacks some fundamental formatting options like:

  1. Right aligning text (please vote for it here: Right align text in Power BI – edit 15th Nov: We’re there: Right aligning text is available now: https://powerbi.microsoft.com/en-us/blog/power-bi-desktop-november-2017-feature-summary/)
  2. Display numbers in different formats within one column (either to be implemented as a “neutral” format for Switch-measures, where the referenced measures carry the formatting attributes already, or as a part of a formula-based conditional formatting) (Thanks Matt for the voting-link: Conditional format SWITCH measure)

So for the moment I choose between the following workaround-options:

  1. Display %-values in a separate column
  2. Format numbers as text and fill up with spaces so that all end up right aligned
  3. See the suggestion from Matt Allington in the comments below (very nice)

Right aligning text or percentage figure in new column

For both options the preparations are the same:

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Custom Connector to import Google Sheets with OAuth2 authentication in PowerBI

Recently I came across the need to connect to Google Sheets with a secure authentication process quite often, so I will share with you how and to what extend I got the custom connector working that I found here. It uses OAuth2 authentication, so you can share your workbook with selected colleagues and they will be prompted to enter their credentials in Power BI if they try to access these files.

Edit: As it turns out, the credentials work for all Google accounts. So you can download my .mez  and simply paste it into your Custom Connectors-path without touching Visual studio ( create path: [My Documents]\Microsoft Power BI Desktop\Custom Connectors ). I believe this will work for the 1st 100 users and then you have to create you own. But if you want to use it in production, I’d strongly recommend to create your own anyway (otherwise continue with section “Use Google Sheets Data Connector in Power BI Desktop”) :

Setup Google API

Go to the Google Developer API and if you don’t have a project yet, just create one:

Go to “Credentials” -> Create credentials and choose “OAuth client ID”:

Choose “Web application”, adjust the “Name” if you like and paste the redirect-url into “Authorized redirect URLs”: https://preview.powerbi.com/views/oauthredirect.html

This will return the client ID and secret for your connector:

 

Adjust the connector in Visual Studio

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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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Tips and Tricks for R scripts in the query editor in Power BI

Especially if you are new to R, there are some things one needs to know to successfully run R-scripts in the query editor of Power BI. I will share them here along with some tricks that made my R-life in Power BI easier:

How to get started – useful links:

Input:

You can feed multiple tables into the R-script

If you click the icon “R script”, the table from the previous step will automatically be passed as the “dataset” to the R-script. So if you don’t fill in any R-code, this will happen:

image

But if you need the content from other tables as well, you just add them into the square brackets like this:

image

“Documentation” looks like this:

image

You can use parameters in the R-script

Apart from tables, you can also use text strings as parameters in the script. They need to be inserted into the code with preceeding “& and trailing &”:

RExportCsv= R.Execute(“write.csv(dataset,” “&CsvExportPath&” “)”,[dataset=Actuals])

Beware that they must be text. So if you want to pass a number, wrap it into Text.From(…).

You cannot use anything else apart from tables and parameters in the R-script

Well, at least I haven’t managed it Smile

R-life gets easy-peasy if you use M-functions for your R-script

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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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