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:

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

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“Documentation” looks like this:

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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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Guide for switching Signs in Power BI and Power Pivot (bypassing Unary Operators in DAX)

In finance & accounting, you very rarely report the figures with the signs of their source systems, but switch (certain) signs according to different needs. Instead of using unary operators for it, I’ll present an easy and dynamic way for it in Power BI and Power Pivot using DAX. It will cover the following 3 main scenarios:

  • 1_SwitchAll: All signs are switched (red)
  • 2_SwitchExpLiab: Expenses and liabilities are switched back to their original values (green)
  • 3_BWT_Indiv: Only the main figure for expenses (or liabilities) carries a minus, all following positions specifying the expenses are (principally) reported as positives (blue)

 

Switching signs in Power BI and Power Pivot without unary operators

I’m using the sample data from this article but changed the source-data to a double-bookkeeping structure. There signs are used and the transaction entries in your ledger table always add up to zero. This is a method that prevents errors when posting and can also be used to prevent errors in reporting. If you keep the signs in your reporting system, all you have to do is add up the relevant figures and the returned (absolute) figures will always be correct. If you have read my previous articles on Easy P&L, you have seen this method in action: No minus-operation there, just a simple stupid adding of all accounts who fall into several (sub-) total categories via the bridge-table.

The Account-table also contains of (sub-) totals and the column “AccountType” shows if the positions are regarded as Turnover (Revenue) or Expenses:

Table “Accounts”

1_SwitchAll

My values on “1_SwitchAll” corresponds to “FinalValue” in the article above. The revenues come from consultancy and coursed provided. But the revenue for courses don’t just consist of attendee rates, but the costs for catering and paid instructors shall be deducted (highlighted in yellow). So the “good” numbers that contribute to cash in your pocket shall be reported without a sign and the “bad” numbers that result in an outflow of cash shall be reported with a minus. Within the expenses category, the costs carry a minus and the travel refunds (highlighted in orange), which are cash positive, are reported as positives.

2_SwitchExpensesLiabilities

Another requirement that is often used for balance-sheet-reporting or reports that only report on cost-situations, require that the costs or liabilities are reported without signs. … Principally, because the reimbursements/cost deductions shall be reported with an opposite sign (to show the adverse effect to the cashflow). This is what “2_SwitchExpLiab” shows (not covered in the article).

3_BWT (“BossWantsThat”)

Last but not least comes a typical “BossWantsThat”-requirement: Basically some strange stuff that you just have to deliver. Here the main categories “Revenues” and “Expenses” shall be shown with the signs that reflect the cash-direction, but all specifications that follow below shall be reported without signs (again: Principally, because positions with opposite cash-effects than the main category shall carry inverted signs).

Reporting techniques covered with this approach

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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 🙂

Comfort Functions for Easy Profit & Loss statements in Power BI and Excel – Part2

Here comes some long awaited comfort functions for part 2 of my easy P&L series. In the first section I’ve presented the general principle on how to work with a structure using an accounts-group-table. Today I will present 2 alternatives to define the reports without specifying single accounts. So if a new accounts are added to the chart of accounts, you don’t have to adjust your report definitions: Just make sure that to fill in all the fields in your account-group-table and you’re ready to go 🙂

No need to specify single accounts

So you only need to adjust your report definitions if you add new group items. If that’s still too much, take the 2nd solution, which will even eliminate that requirement:

  1. Individual Account Layout: Just define each subtotal and determine for which subtotals single accounts shall be shown

No more specification of individual accounts

How to use it:

How to use Individual Report Layout

2. Ultrashort Account Layout: Further simplification of just defining the groups (hierarchy) that shall be shown (with option to filter on one of them)

No need to define individual group items

How to use it:

How to use Ultrashort Layout

So these 2 different layouts will both produce the same reports incl. all accounts – just like in the first example. So you can choose which layout-style suits you best – actually, you can use all 3 in parallel. You just have to make sure to grab your pivot-rows from the correct tables and in Excel to grab the matching measures, as they all have their own bridge-tables (which need to be used in the measures):

 

How it works

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Easy Profit & Loss (and other account) statements in PowerBI and Excel – Part2

Welcome to part 2 of my series of easy Profit & Loss and other account statements in Power BI and Excel. In the first part I introduced the general principle of creating asymmetric shaped reports who use just one measure per column (you should have read this article in order to understand this post here).

How the technique works

This technique capitalises the aggregation power of the Vertipaq engine and creates a bridge-table between your DimAccount-table and the ReportsAccountsLayout-table. In there for every line of your report, all accounts that belong to the (sub-)totals are matched (“AccountsAllocation”). This table can get very long, but the engine can handle this easily:

Different use case: Account-groups-tables

In the first example we’ve worked with a chart of accounts, which had a parent-chield-hierarchy defining all the subtotals of the report. In this example we’re working with a different setup, using the good old DimAccountsGroups-table. Just one row per account and the columns are coming in pairs, containing the group-criteria and the sort-order for the report:

Individual Report-Layout

We also need a second table (ReportsAccountsLayout) that holds the definitions of the report-layouts like this:

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