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PDRTXRA
Helper I
Helper I

Transform Table

I think this is very simple but I just can't find a way to do it.

I have a table where each row represents one Family ID and the age of a son of that family.

Lets say: 

FamilyID  |   AgeSon
1   |      10
1   |      12 
2   |      14
3   |     20 
3   |    22
3   |    24

I want to create a table where each row is a family ID with a column for every age. So, using the sample above:

FamilyID | Age1 | Age2 | Age3
1 | 10 | 12 
2 | 14
3 | 20 | 22 | 24

I appreciate your help.

1 ACCEPTED SOLUTION
Anonymous
Not applicable

Hi @PDRTXRA 

You can put the following code to Advanced Editor in power query

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMlTSUTI0UIrVgTKNwEwjENMEzDQGMo0MEEwjBBOoIBYA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [FamilyID = _t, AgeSon = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"FamilyID", Int64.Type}, {"AgeSon", Int64.Type}}),
    Custom1 = Table.Group(#"Changed Type", {"FamilyID"}, {{"Data", each Table.AddIndexColumn(_, "Index", 1, 1), type table}}),
    #"Expanded Data" = Table.ExpandTableColumn(Custom1, "Data", {"AgeSon", "Index"}, {"AgeSon", "Index"}),
    #"Pivoted Column" = Table.Pivot(Table.TransformColumnTypes(#"Expanded Data", {{"Index", type text}}, "en-US"), List.Distinct(Table.TransformColumnTypes(#"Expanded Data", {{"Index", type text}}, "en-US")[Index]), "Index", "AgeSon"),
    #"Renamed Columns" = Table.RenameColumns(#"Pivoted Column",{{"1", "Age 1"}, {"2", "Age 2"}, {"3", "Age 3"}})
in
    #"Renamed Columns"

Output

vxinruzhumsft_0-1684980730471.png

 

Best Regards!

Yolo Zhu

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

 

 

 

View solution in original post

2 REPLIES 2
Anonymous
Not applicable

Hi @PDRTXRA 

You can put the following code to Advanced Editor in power query

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMlTSUTI0UIrVgTKNwEwjENMEzDQGMo0MEEwjBBOoIBYA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [FamilyID = _t, AgeSon = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"FamilyID", Int64.Type}, {"AgeSon", Int64.Type}}),
    Custom1 = Table.Group(#"Changed Type", {"FamilyID"}, {{"Data", each Table.AddIndexColumn(_, "Index", 1, 1), type table}}),
    #"Expanded Data" = Table.ExpandTableColumn(Custom1, "Data", {"AgeSon", "Index"}, {"AgeSon", "Index"}),
    #"Pivoted Column" = Table.Pivot(Table.TransformColumnTypes(#"Expanded Data", {{"Index", type text}}, "en-US"), List.Distinct(Table.TransformColumnTypes(#"Expanded Data", {{"Index", type text}}, "en-US")[Index]), "Index", "AgeSon"),
    #"Renamed Columns" = Table.RenameColumns(#"Pivoted Column",{{"1", "Age 1"}, {"2", "Age 2"}, {"3", "Age 3"}})
in
    #"Renamed Columns"

Output

vxinruzhumsft_0-1684980730471.png

 

Best Regards!

Yolo Zhu

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

 

 

 

Ritaf1983
Super User
Super User

Hi @PDRTXRA 
The first step to achieving your goal is to concatenate your ages :
you can follow these steps in POWER QUERY :

1. Change your age data type to text

Ritaf1983_1-1684866269174.png

 

2. Combine your ages with delimiter:

Ritaf1983_2-1684866617632.png

 

and paste this m code:

= Table.Group(#"Changed Type2", {"FamilyID"}, {{"age", each Text.Combine([Age son],","), type nullable text}})

 

Ritaf1983_3-1684866708906.png

3. Split the result column by comma:

Ritaf1983_4-1684866880625.png

4. Close and apply.

Result:

Ritaf1983_5-1684866943633.png

Link to the sample file 

If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly

 

Regards,
Rita Fainshtein | Microsoft MVP
https://www.linkedin.com/in/rita-fainshtein/
Blog : https://www.madeiradata.com/profile/ritaf/profile

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