Don't miss your chance to take the Fabric Data Engineer (DP-600) exam for FREE! Find out how by watching the DP-600 session on-demand now through April 28th.
Learn moreJoin the FabCon + SQLCon recap series. Up next: Power BI, Real-Time Intelligence, IQ and AI, and Data Factory take center stage. All sessions are available on-demand after the live show. Register now
I have a set of data that has multiple values in one field (see below). When I expand that data it creates multiple rows and duplicates the rest of the data. However, this is causing me issues for both displaying the data and creating relationships. How can I show these in one row?
*Because project number is my unique identifier, I only want this project number listed once so I do not end up creating many to many relationships.
Current State:
| Project Number | Project Title | Sponsor | Location |
| 1 | Project 1 | Executive A | Indiana |
| 2 | Project 2 | Executive B | New York |
| 3 | Project 3 | Executive A | Virginia |
| 3 | Project 3 | Executive A | Indiana |
| 4 | Project 4 | Executive B | New York |
Desired Output:
| Project Number | Project Title | Sponsor | Location |
| 1 | Project 1 | Executive A | Indiana |
| 2 | Project 2 | Executive B | New York |
| 3 | Project 3 | Executive A | Virginia, Indiana |
| 4 | Project 4 | Executive B | New York |
Solved! Go to Solution.
Yes you can extract a column from the table here is the syntax:
#"Extract_List" = Table.TransformColumns(#"Removed Columns, {"ProjectLead", each Text.Combine(List.Transform(Table.TransformRows(_,each [Name]), Text.From), ","), type text})
Did I answer your question? Mark my post as a solution! Appreciate your Kudos!!
Hi,
This M code works
let
Source = Excel.CurrentWorkbook(){[Name="Data"]}[Content],
#"Grouped Rows" = Table.Group(Source, {"Project Number"}, {{"All Locatinos", each Text.Combine(List.Distinct([Location]), ", "), type text}}),
Joined = Table.Join(Source, "Project Number", #"Grouped Rows", "Project Number"),
#"Removed Columns" = Table.RemoveColumns(Joined,{"Location"}),
#"Removed Duplicates" = Table.Distinct(#"Removed Columns")
in
#"Removed Duplicates"
Hope this helps.
Instead of "Expand to New Rows" you can Extract Values in comma-delimited format.
Alternatively, you can write m query to extract list as comma-delimited value in new column:
Extract_List = Table.TransformColumns(PrevStep, {"Listxyz", each Text.Combine(List.Transform(_, Text.From), ","), type text}),
Hi, I have got a similar situation. My share point is giving person field with multiple people. In powerbi, it is coming as a table. Once I extract values from the table, I have multiple rows
ID 1 Name 1 Red Sunday
ID 1 Name 2 Red Sunday.
I want in my matrix to come as only 1 row
TIA
Does the m query work if it is a "table" I am expanding rather than a list?
I am getting an error with this:
#"Extract_List" = Table.TransformColumns(#"Removed Columns", {"ProjectLead", each Text.Combine(List.Transform(_, Text.From), ","), type text}),
I should clarify - it's the "Name" field, I'm trying to get out of this:
Yes you can extract a column from the table here is the syntax:
#"Extract_List" = Table.TransformColumns(#"Removed Columns, {"ProjectLead", each Text.Combine(List.Transform(Table.TransformRows(_,each [Name]), Text.From), ","), type text})
Did I answer your question? Mark my post as a solution! Appreciate your Kudos!!
Hi, I have got a similar situation. My share point is giving person field with multiple people. In powerbi, it is coming as a table. Once I extract values from the table, I have multiple rows
ID 1 Name 1 Red Sunday
ID 1 Name 2 Red Sunday.
I want in my matrix to come as only 1 row
TIA
Check out the April 2026 Power BI update to learn about new features.
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
| User | Count |
|---|---|
| 48 | |
| 40 | |
| 38 | |
| 20 | |
| 17 |
| User | Count |
|---|---|
| 68 | |
| 65 | |
| 30 | |
| 26 | |
| 25 |