Creating a Measure to Switch between Names Columns, using USERELATIONSHIP

[patri0t82]

Hello, I have three columns in one table.

Table1[Name1]

Table1[Name2]

Table1[Name3]

I have another table called DistinctNames, which has a column called [Names], which as you can imagine, is a combination of all the names from the above three columns.

What I would like to do is create a slicer that contains a list of all the distinct names, and then filters my visuals, depending on which column(s) the name falls in. For example, if I click on John Smith, I need it to interact with Table1, regardless of which column his name falls in.

[Greg_Deckler]

@patri0t82 Sorry, having trouble following, can you post sample data as text and expected output?
Not really enough information to go on, please first check if your issue is a common issue listed here: https://community.powerbi.com/t5/Community-Blog/Before-You-Post-Read-This/ba-p/1116882

Also, please see this post regarding How to Get Your Question Answered Quickly: https://community.powerbi.com/t5/Community-Blog/How-to-Get-Your-Question-Answered-Quickly/ba-p/38490

The most important parts are:
1. Sample data as text, use the table tool in the editing bar
2. Expected output from sample data
3. Explanation in words of how to get from 1. to 2.

[patri0t82]

This is my desired result. Thank you very much for your help.

Here is some sample code. This will give you Table1:

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Name1 = _t, Name2 = _t, Name3 = _t, Value = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"Name1", type text}, {"Name2", type text}, {"Name3", type text}})
in
    #"Changed Type"

This code will retrieve the distinct names from Table1

let
    Source = List.Combine({List.Distinct(Table1[Name1]),List.Distinct(Table1[Name2]),List.Distinct(Table1[Name3])}),
    #"Removed Duplicates" = List.Distinct(Source),
    #"Converted to Table" = Table.FromList(#"Removed Duplicates", Splitter.SplitByNothing(), null, null, ExtraValues.Error),
    #"Renamed Columns" = Table.RenameColumns(#"Converted to Table",{{"Column1", "Names"}})
in
    #"Renamed Columns"

This is a table you can use instead of Base64 above

Name1	Name2	Name3	Value
Freya Henderson	Dennis West	Veda Marquez	34
Beau Nunez	Remi Griffith	Malakai Kerr	35
Mya Kent	Kayson Sheppard	Alexia Black	51
Mekhi Christian	Veda Marquez	Matteo Fletcher	5
Anahi McCarty	Malakai Kerr	Aspen Whitney	31
Blaise Hoffman	Freya Henderson	Jeffery Morrow	5
Aspen Whitney	Beau Nunez	Reyna Sloan	5363
Jeffery Morrow	Mya Kent	Kayson Sheppard	8931
Reyna Sloan	Mekhi Christian	Veda Marquez	75
Kayson Sheppard	Anahi McCarty	Malakai Kerr	356
Veda Marquez	Blaise Hoffman	Finley Hail	63
Malakai Kerr	Aspen Whitney	Anahi McCarty	627
Alexia Black	Jeffery Morrow	Blaise Hoffman	2
Matteo Fletcher	Reyna Sloan	Aspen Whitney	7
Anaya Blake	Ocean Arnold	Jeffery Morrow	724
Zyaire Moyer	Finley Hail	Baylee Allison	7
Zola Day	Hector Snow	Dennis West	4217
Kayson Sheppard	Kayson Sheppard	Remi Griffith	735
Veda Marquez	Veda Marquez	Franklin Leonard	22
Malakai Kerr	Malakai Kerr	Aspen Whitney	77
Baylee Allison	Finley Hail	Jeffery Morrow	642
Dennis West	Hector Snow	Reyna Sloan	246
Remi Griffith	Alexia Black	Kayson Sheppard	7
Franklin Leonard	Kayson Sheppard	Franklin Leonard	24
Kayson Sheppard	Veda Marquez	Kayson Sheppard	77
Veda Marquez	Malakai Kerr	Veda Marquez	6
Malakai Kerr	Aspen Whitney	Kayson Sheppard	61