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Transforming Data in Power Query

Hello,

I'm wondering if it's possible to transform the data from multiple columns into multiple rows, almost like a pivot table. See theexample below.


The data comes in like this:

 

I want to combine similar columns into one (highlighted in the same colors), but then show each item in different row. The image below is what I want it to look like.

 

Is that possible to do? Can someone show me the steps? I also just want to mention that this example is in small scale. My actual data set has about 40 columns and over a hundred rows. 

5 REPLIES 5

hello, @Shalom 

let
    Source = your_table,
    rows = List.Buffer(Table.ToRows(Source)),
    tra = List.TransformMany(
        rows, 
        (x) => List.Zip(
            {List.Skip(List.Alternate(x, 2, 1, 2)),
            List.Alternate(x, 2, 1, 0),
            List.Skip(List.Alternate(x, 2, 1, 1))}
        ),
        (x, y) => {x{0}} & y
    ),
    z = Table.FromRows(tra, {"Item", "Dep", "State", "Time"})
in
    z

Hi @Shalom,

 

Result:

 

2 versions of code here. V1 is similar with @AlienSx version. If I were you I would go for v2 because it is dynamic (no matter how many colum pairs do you have), but maybe you have to adjust v2_Extracted Text Before Delimiter because I don't know if you have space in every column name (as you have in example Dep 1, Dep 2 etc...). Of course it is possible to make dynamic v1 but I need to know your real column names.

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMlTSUfLIz00FUiERQMLUysCgIBfICC4tKMjJTC0GMn0dgYSJlaEpRCIxByzqDBI1NLIyBqmP1YlWMkKSdIwCEuZWJhAtfo7BIMX+HsgWuGXmJeYlwy02hIiDDDJGkQXbYw7T5QhyFYo+QysjiJR3ZklyRmoeyD4XIGEMcXBsLAA=", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Item = _t, #"Dep 1" = _t, #"State 1" = _t, #"Time 1" = _t, #"Dep 2" = _t, #"State 2" = _t, #"Time 2" = _t, #"Dep 3" = _t, #"State 3" = _t, #"Time 3" = _t]),
    v1_ListTransformMany = List.TransformMany(Table.ToRows(Source),
     each List.Split(List.Skip(_), 3),
     (x,y)=> {x{0}} & y
  ),
    v1_ToTable = Table.FromRows(v1_ListTransformMany, {"Item", "Dep", "State", "Time"}),
    StepBack = Source,
    #"v2_Unpivoted Other Columns" = Table.UnpivotOtherColumns(StepBack, {"Item"}, "Column Name", "Value"),
    #"v2_Extracted Text Before Delimiter" = Table.TransformColumns(#"v2_Unpivoted Other Columns", {{"Column Name", each Text.BeforeDelimiter(_, " "), type text}}),
    v2_GroupedRows = Table.Group(#"v2_Extracted Text Before Delimiter", {"Column Name"}, {{"All", each _, type table}, {"List", each Table.ToColumns(Table.SelectColumns(_, List.Select(Table.ColumnNames(_), each _ <> "Column Name"))), type list}}),
    v2_Zip = List.Zip(v2_GroupedRows[List]),
    v2_ToTable = Table.FromColumns({v2_Zip{0}{0}} & List.Skip(v2_Zip){0}, {"Item"} & v2_GroupedRows[Column Name])
in
    v2_ToTable

 

Hi dufoq3,

I'm still new to power query so I need a little help understanding the code. I have a couple of questions. I'm going with V2, so I assume all I have to do is leave out the two V1 code lines in your solution.
1. The green text inbetween the quotation marks "i45..AA=", is this where my source table goes or should I use the text as is? If I use the text as is, at what point do I reference the query/table that has my data in it?

2. On the V2 unpivoted other columns code, my understanding is that I should insert the previous step name into the "StepBack" portion. But I'm not too sure what the previous step name would be since the step before that is the Source = line

3. I understand that I will have to replace "Item","Dep","State" and "Time" with my actual column names, what do I replace the "List" with or do I leave that like that as well?

@Shalom, you have to turn on Query Settings (but it should be turned on by default)

 

 

Then in right query settings panel you caj X out both v1 steps and also StepBack

 

Then in Source step delete whole code and refer to your query

 

 

That worked perfectly. Thank you !

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