Help with creating a function, multiple SelectRows and GroupBy

[ramzez]

Hi,

I need help with creating a function. 

This is my sample data:

session_start	session_user	Daily_sum
9/20/2023	Person 1	4
9/22/2023	Person 1	5
9/25/2023	Person 1	8
9/23/2023	Person 2	3
9/25/2023	Person 2	5
9/26/2023	Person 2	4
9/27/2023	Person 2	7

I need to find out the session_start date when the sum of each of the session_user goes below 10, calculated backwards from today.
In the sample data calculated from today (9/28/2023) backwards for Person 1 the date when the sum of Daily_sum values goes below 10 is 9/23/2023 (because 9/22/2023 adds 5)  and Person 2's 9/27/2023 (because 9/26/2023 adds 4). I also need to be able to set how many days into the past the data is calculated.

I figured that I need to make the following two steps multiple times. First select the data that are in the past n days: (here 10 days) Table.SelectRows(Source, each Date.IsInPreviousNDays([session_start], 10)).

Then group those by "session_user":
Table.Group(Custom, {"session_user"}, {{"Sum", each List.Sum([Daily_sum]), type nullable number}}).

Then I need to select the rows from the data that are in the past n - 1 days. Then group those by "session_user" and so on until today.

I was able to create a custom function that finds the value how many loops it takes for any of the values for session_users is below 10.

Here is the function:

let
  Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WKk4tLs7Mz4svLkksKlHSgfNLi1OLgFyXxMycyvji0lylWJ1oJUt9IwMgMjIGygSkFhXn5ykYApkmMEkjLJKmMElTLJIWMEljNEkjINMYl04jZGPNsEjCHWSORdJcKTYWAA==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Column1 = _t, Column2 = _t, Column3 = _t]),
  #"Promoted headers" = Table.PromoteHeaders(Source, [PromoteAllScalars = true]),
  #"Changed column type" = Table.TransformColumnTypes(#"Promoted headers", {{"session_start", type date}, {"session_user", type text}, {"Daily_sum", Int64.Type}}),


    CustomFunction = (n as number) as table =>
        let
            FilteredRows = Table.SelectRows(#"Changed column type", each Date.IsInPreviousNDays([session_start], n)),
            GroupedRows = Table.Group(FilteredRows, {"session_user"}, {{"Sum", each List.Sum([Daily_sum]), type nullable number}}),
            Result = if List.Min(GroupedRows[Sum]) < 10 then Table.AddColumn(GroupedRows, "Final N Value", each n) else @CustomFunction(n-1)
        in
            Result,
    FinalResult =
CustomFunction(10)
in
    FinalResult

 Here is the result at the moment:

The function has stopped because Person 1's sum is less than 10 but at the same time I need to find out when Person 2's sum goes below 10.

How can I achieve this?

 

[Anonymous · Accepted solution]

Hi @ramzez ,

let
  Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WstQ3MgAiI2MlHaWA1KLi/DwFQyDTRClWByxphEXSFCZpikXSAiZpjCZpBGQa49JphGysGRZJuIPMsUiaK8XGAgA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [session_start = _t, session_user = _t, Daily_sum = _t]),
    #"Changed column type" = Table.TransformColumnTypes(Source, {{"session_start", type date}, {"session_user", type text}, {"Daily_sum", Int64.Type}}),

  CustomFunction = (user as text, n as number) as table =>
    let
      FilteredRows = Table.SelectRows(#"Changed column type", each [session_user] = user and Date.IsInPreviousNDays([session_start], n)),
      GroupedRows = Table.Group(FilteredRows, {"session_user"}, {{"Sum", each List.Sum([Daily_sum]), type nullable number}}),
      Result = if List.Min(GroupedRows[Sum]) < 10 then Table.AddColumn(GroupedRows, "Final N Value", each n) else @CustomFunction(user, n-1)
    in
      Result,

  Users = List.Distinct(#"Changed column type"[session_user]),
  Results = List.Transform(Users, each CustomFunction(_, 10)),
  FinalResult = Table.Combine(Results)
in
  FinalResult

Output:

If I've misunderstood your question, feel free to contact me.

Best Regards,
Gao
Community Support Team

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