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Anonymous
Not applicable

Structuring data into desired format with pivoting/unpivoting

Hi everyone,
I have a dataset of hours worked by some users that is structured in this format
Hours.PNG

I woul like to transform it in this format 
hour s 2.PNG

What kind of PowerQuery operations do I have to perform to get this result?
Thanks

2 ACCEPTED SOLUTIONS
HotChilli
Super User
Super User

Select all the Day columns and Unpivot them.

Select the Type column and Pivot it using the newly created Value column as the Value,

Split the Day column by the left 3 characters. Tidy up the columns by removing the ones you don't want and renaming the ones that need it.

View solution in original post

I followed @HotChilli's instructions and I believe I got the exact result after I unpivoted the Day columns and then Pivoted the Type column using Value. Attached PBIX, here is the query code:

 

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMjQyVtJRCsnPBZLh+UXZQMoCBcfqoCpyKkpNBKkyBGIjKG2IoSo4Mzk7L7W4GMg0QMEghSamZkC2V2pRUSXCVnMkW82xKEO21xDFXlR1uG2OBQA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [WorkedID = _t, Name = _t, Type = _t, Day1 = _t, Day2 = _t, Day3 = _t, Day4 = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"WorkedID", Int64.Type}, {"Name", type text}, {"Type", type text}, {"Day1", Int64.Type}, {"Day2", Int64.Type}, {"Day3", Int64.Type}, {"Day4", Int64.Type}}),
    #"Unpivoted Columns" = Table.UnpivotOtherColumns(#"Changed Type", {"WorkedID", "Name", "Type"}, "Attribute", "Value"),
    #"Pivoted Column" = Table.Pivot(#"Unpivoted Columns", List.Distinct(#"Unpivoted Columns"[Type]), "Type", "Value", List.Sum)
in
    #"Pivoted Column"

 

 


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View solution in original post

2 REPLIES 2
HotChilli
Super User
Super User

Select all the Day columns and Unpivot them.

Select the Type column and Pivot it using the newly created Value column as the Value,

Split the Day column by the left 3 characters. Tidy up the columns by removing the ones you don't want and renaming the ones that need it.

I followed @HotChilli's instructions and I believe I got the exact result after I unpivoted the Day columns and then Pivoted the Type column using Value. Attached PBIX, here is the query code:

 

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMjQyVtJRCsnPBZLh+UXZQMoCBcfqoCpyKkpNBKkyBGIjKG2IoSo4Mzk7L7W4GMg0QMEghSamZkC2V2pRUSXCVnMkW82xKEO21xDFXlR1uG2OBQA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [WorkedID = _t, Name = _t, Type = _t, Day1 = _t, Day2 = _t, Day3 = _t, Day4 = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"WorkedID", Int64.Type}, {"Name", type text}, {"Type", type text}, {"Day1", Int64.Type}, {"Day2", Int64.Type}, {"Day3", Int64.Type}, {"Day4", Int64.Type}}),
    #"Unpivoted Columns" = Table.UnpivotOtherColumns(#"Changed Type", {"WorkedID", "Name", "Type"}, "Attribute", "Value"),
    #"Pivoted Column" = Table.Pivot(#"Unpivoted Columns", List.Distinct(#"Unpivoted Columns"[Type]), "Type", "Value", List.Sum)
in
    #"Pivoted Column"

 

 


@ me in replies or I'll lose your thread!!!
Instead of a Kudo, please vote for this idea
Become an expert!: Enterprise DNA
External Tools: MSHGQM
YouTube Channel!: Microsoft Hates Greg
Latest book!:
The Definitive Guide to Power Query (M)

DAX is easy, CALCULATE makes DAX hard...

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