Power BI is turning 10! Tune in for a special live episode on July 24 with behind-the-scenes stories, product evolution highlights, and a sneak peek at what’s in store for the future.
Save the dateEnhance your career with this limited time 50% discount on Fabric and Power BI exams. Ends August 31st. Request your voucher.
Hi ,
Is there any better way we can handly multiple row values in matrix.
Basically i need to show a matrix visual which has around 25 row items , columns i need to show dates , and values i have to show hours.
Below is just for illustration where i have 22 columns with date and Values field,
Emp NO | name | Region | location | phone num | address 1 | address 2 | address 3 | address 4 | address 5 | address 6 | address 7 | address 8 | address 9 | address 10 | address 11 | address 12 | address 13 | address 14 | address 15 | address 16 | date | Value | |
121 | ada | sss | ssd | 122 | 12@qw.com2323ddd | sds2 | 343 | s | 23 | 235d | 23a | 23s | 23a | 23sa | 23s | 23sa | 2sa | 2saa | 2aa | 2aaa | 20-Jun | 10 |
I will placee 22 column names from emp no to address 16 in rows , date in columns, and values in values in a matrix visual.
Issues i am facing:
1.By placing so many fields on rows , i am facing scroll issue.
2.Eventhough i gice option of icon to user, they need to manually press icon multiple times and yet have scrollable issue.
3. Performance is very low as data is more.
Is there any better way we can show this otr achieve in a matrix visual .
Thank,
Binay
Solved! Go to Solution.
Hi @binayjethwa
You can refer to the following suggestion.
Unpivot the 'address' column, then combine it.
e.g
You can put the following code to advanced editor in power query
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMjQyVNJRSkxJBJLFxcVgMgVIGhoZgUmHwnK95PxcI2Mj45QUkIQCSElKMUjW2MQYxAFiI2MwYZoCphLBZDGcjQsZGijFxgIA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Emp NO" = _t, name = _t, #"Region " = _t, #"location " = _t, #"phone num" = _t, #"email " = _t, #"address 1" = _t, #"address 2" = _t, #"address 3" = _t, #"address 4" = _t, #"address 5" = _t, #"address 6" = _t, #"address 7" = _t, #"address 8" = _t, #"address 9" = _t, #"address 10" = _t, #"address 11" = _t, #"address 12" = _t, #"address 13" = _t, #"address 14" = _t, #"address 15" = _t, #"address 16" = _t, date = _t, Value = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Emp NO", Int64.Type}, {"name", type text}, {"Region ", type text}, {"location ", type text}, {"phone num", Int64.Type}, {"email ", type text}, {"address 1", type text}, {"address 2", type text}, {"address 3", Int64.Type}, {"address 4", type text}, {"address 5", Int64.Type}, {"address 6", type text}, {"address 7", type text}, {"address 8", type text}, {"address 9", type text}, {"address 10", type text}, {"address 11", type text}, {"address 12", type text}, {"address 13", type text}, {"address 14", type text}, {"address 15", type text}, {"address 16", type text}, {"date", type text}, {"Value", type text}}),
#"Removed Columns" = Table.RemoveColumns(#"Changed Type",{"address 10", "address 11", "address 12", "address 13", "address 14", "address 15", "address 16"}),
#"Unpivoted Only Selected Columns" = Table.Unpivot(#"Removed Columns", {"address 1", "address 2", "address 3", "address 4", "address 5", "address 6", "address 7", "address 8", "address 9"}, "Attribute", "Value.1"),
#"Merged Columns" = Table.CombineColumns(Table.TransformColumnTypes(#"Unpivoted Only Selected Columns", {{"Value.1", type text}}, "en-US"),{"Attribute", "Value.1"},Combiner.CombineTextByDelimiter("-", QuoteStyle.None),"Merged")
in
#"Merged Columns"
Then put the column to the row
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.
Hi @binayjethwa
You can refer to the following suggestion.
Unpivot the 'address' column, then combine it.
e.g
You can put the following code to advanced editor in power query
let
Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMjQyVNJRSkxJBJLFxcVgMgVIGhoZgUmHwnK95PxcI2Mj45QUkIQCSElKMUjW2MQYxAFiI2MwYZoCphLBZDGcjQsZGijFxgIA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [#"Emp NO" = _t, name = _t, #"Region " = _t, #"location " = _t, #"phone num" = _t, #"email " = _t, #"address 1" = _t, #"address 2" = _t, #"address 3" = _t, #"address 4" = _t, #"address 5" = _t, #"address 6" = _t, #"address 7" = _t, #"address 8" = _t, #"address 9" = _t, #"address 10" = _t, #"address 11" = _t, #"address 12" = _t, #"address 13" = _t, #"address 14" = _t, #"address 15" = _t, #"address 16" = _t, date = _t, Value = _t]),
#"Changed Type" = Table.TransformColumnTypes(Source,{{"Emp NO", Int64.Type}, {"name", type text}, {"Region ", type text}, {"location ", type text}, {"phone num", Int64.Type}, {"email ", type text}, {"address 1", type text}, {"address 2", type text}, {"address 3", Int64.Type}, {"address 4", type text}, {"address 5", Int64.Type}, {"address 6", type text}, {"address 7", type text}, {"address 8", type text}, {"address 9", type text}, {"address 10", type text}, {"address 11", type text}, {"address 12", type text}, {"address 13", type text}, {"address 14", type text}, {"address 15", type text}, {"address 16", type text}, {"date", type text}, {"Value", type text}}),
#"Removed Columns" = Table.RemoveColumns(#"Changed Type",{"address 10", "address 11", "address 12", "address 13", "address 14", "address 15", "address 16"}),
#"Unpivoted Only Selected Columns" = Table.Unpivot(#"Removed Columns", {"address 1", "address 2", "address 3", "address 4", "address 5", "address 6", "address 7", "address 8", "address 9"}, "Attribute", "Value.1"),
#"Merged Columns" = Table.CombineColumns(Table.TransformColumnTypes(#"Unpivoted Only Selected Columns", {{"Value.1", type text}}, "en-US"),{"Attribute", "Value.1"},Combiner.CombineTextByDelimiter("-", QuoteStyle.None),"Merged")
in
#"Merged Columns"
Then put the column to the row
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.
User | Count |
---|---|
73 | |
70 | |
38 | |
25 | |
23 |
User | Count |
---|---|
96 | |
93 | |
50 | |
43 | |
42 |