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Hello exprerts
My datasource is a s following:
Date from | Date to | Share |
01.01.2020 | 15.03.2020 | 70 |
16.03.2020 | 15.08.2021 | 50 |
01.12.2021 | 31.01.2022 | 50 |
01.02.2022 | 31.05.2022 | 60 |
01.06.2022 | 30.06.2022 | 60 |
01.07.2022 | 31.08.2022 | 60 |
01.10.2022 | 31.12.9999 | 100 |
Ie. date validity ranges for "Share" that do not overlap but can have "holes"
I need to transorm the above to period (month) ranges. If there are more than one value for the month the last one is used. If the subsequent ranges have same "Share" they should be joined.
For data as above the expected result is following
Period from | Period to | Share |
202001 | 202002 | 70 |
202003 | 202108 | 50 |
202112 | 202201 | 50 |
202202 | 202208 | 60 |
202210 | 999912 | 100 |
I have already spent several hours trying to figure out the M-code for the transformation but failed.
Can anyone help?
Solved! Go to Solution.
A showcase of powerful Table.Group(),
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("Zc7RDcAgCATQXfg25sCgdhbj/msUYmhpavi5y5OwFoGrjUBAhVgrWoQB2mUR99Q5mB7Ygh5g31mia7FOPgASnQON0F/QH4AUEhh5w/wDRgJ20GXPL4aJfQM=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Date from" = _t, #"Date to" = _t, Share = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Date from", type date}, {"Date to", type date}, {"Share", Int64.Type}}, "fr"),
#"Added Index" = Table.AddIndexColumn(#"Changed Type", "Index"),
Grouped =
let rows = Table.ToRecords(#"Added Index") in Table.Group(#"Added Index", Table.ColumnNames(#"Added Index"), {"grp", each let rs = Table.ToRecords(_) in [From=Date.ToText(rs{0}[Date from],"yyyyMM"), To=Date.ToText(List.Last(rs)[Date to],"yyyyMM"), Share=rs{0}[Share]]}, 0, (x,y) => Byte.From(let r = rows{y[Index]-1} in y[Date from] <> r[Date to] + #duration(1,0,0,0) or y[Share] <> r[Share])),
#"New Table" = Table.FromRecords(Grouped[grp])
in
#"New Table"
Thanks to the great efforts by MS engineers to simplify syntax of DAX! Most beginners are SUCCESSFULLY MISLED to think that they could easily master DAX; but it turns out that the intricacy of the most frequently used RANKX() is still way beyond their comprehension! |
DAX is simple, but NOT EASY! |
A showcase of powerful Table.Group(),
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("Zc7RDcAgCATQXfg25sCgdhbj/msUYmhpavi5y5OwFoGrjUBAhVgrWoQB2mUR99Q5mB7Ygh5g31mia7FOPgASnQON0F/QH4AUEhh5w/wDRgJ20GXPL4aJfQM=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Date from" = _t, #"Date to" = _t, Share = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Date from", type date}, {"Date to", type date}, {"Share", Int64.Type}}, "fr"),
#"Added Index" = Table.AddIndexColumn(#"Changed Type", "Index"),
Grouped =
let rows = Table.ToRecords(#"Added Index") in Table.Group(#"Added Index", Table.ColumnNames(#"Added Index"), {"grp", each let rs = Table.ToRecords(_) in [From=Date.ToText(rs{0}[Date from],"yyyyMM"), To=Date.ToText(List.Last(rs)[Date to],"yyyyMM"), Share=rs{0}[Share]]}, 0, (x,y) => Byte.From(let r = rows{y[Index]-1} in y[Date from] <> r[Date to] + #duration(1,0,0,0) or y[Share] <> r[Share])),
#"New Table" = Table.FromRecords(Grouped[grp])
in
#"New Table"
Thanks to the great efforts by MS engineers to simplify syntax of DAX! Most beginners are SUCCESSFULLY MISLED to think that they could easily master DAX; but it turns out that the intricacy of the most frequently used RANKX() is still way beyond their comprehension! |
DAX is simple, but NOT EASY! |
Absolutely amazing. It works great. But I am not sure if my mental capacity is capable to understand how 🙂
Thanks a lot
This is cool, what UI steps equal to Table.Group() ?
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