Forum Discussion
How to do a sequential numbering by customer
- 8 years ago
Hi danextian
Good question. Here is a pbix file demonstrating that it works.
From Microsoft's documentation, the rules for Boolean filter expressions are:
The expression cannot reference a measure.
The expression cannot use a nested CALCULATE function.
The expression cannot use any function that scans a table or returns a table, including aggregation functions.
So basically you can create any boolean expression involving a single column as long as you don't use a measure/CALCULATE/table-scanning function.
In my case, YourTable[Date] <= CurrentRowDate is a Boolean expression comparing YourTable[Date] to a variable CurrentRowDate (effectively a constant at this point in the code), but CALCULATE isn't involved in this expression. The definition of CurrentRowDate didn't use CALCULATE either.
With the advent of variables, you can use a variable anywhere in a CALCULATE filter argument where a constant would have been allowed. This is one way of getting around the restrictions on Boolean filter arguments listed above. So if my definition for CurrentRowDate had involved CALCULATE, I could have still used CurrentRowDate the same way I did within CALCULATE.
Incidentally, I could have written this calculated column as:
Numbering = CALCULATE ( COUNTROWS ( YourTable ), ALLEXCEPT ( YourTable, YourTable[Customer] ), YourTable[Date] <= EARLIER ( YourTable[Date] ) )Regards,
Owen
Hi OwenAuger, is that a way to do the numbering in power query M?
It's a calculated column you can create in DAX.
- Anonymous8 years agoNot applicableYes, i know. I would want to do this in power query because this will follow by the filtering process, which i want to filter some unneccessary rows and append it with other datasets.
- OwenAuger8 years ago
Super User
Anonymous
Here is a rough example of a Powre Query version:
let Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45W8srPyFPSUTLUN9Q3MjA0BzJNDQyUYnXgMqb6RjAZE3QZY5iMGVTGN7GoEsg1QjLOCE3KAE1XLAA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [Customer = _t, Date = _t, Amount = _t]), #"Changed Type" = Table.TransformColumnTypes(Source,{{"Customer", type text}, {"Date", type date}, {"Amount", type number}}), #"Grouped Rows" = Table.Group(#"Changed Type", {"Customer"}, {{"Rows", each _, type table}}), #"Sort by Date" = Table.TransformColumns(#"Grouped Rows", {"Rows", each Table.Sort(_,{{"Date", Order.Ascending}}) } ), #"Add Index" = Table.TransformColumns( #"Sort by Date", {"Rows", each Table.AddIndexColumn(_, "Numbering", 1, 1)} ), #"Expanded Rows" = Table.ExpandTableColumn(#"Add Index", "Rows", {"Date", "Amount", "Numbering"}, {"Date", "Amount", "Numbering"}), #"Fix Types" = Table.TransformColumnTypes(#"Expanded Rows",{{"Date", type date}, {"Amount", type number}, {"Numbering", Int64.Type}}) in #"Fix Types"It groups by Customer, then adds an Index to the nested table then expands.