Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.
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.
@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.
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 |
Covering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City
Check out the April 2024 Power BI update to learn about new features.
User | Count |
---|---|
111 | |
94 | |
83 | |
67 | |
59 |
User | Count |
---|---|
151 | |
121 | |
104 | |
87 | |
67 |