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Hello All,
I would be grateful if someone can let me know a way to hide blank rows and columns in a matrix visualization of Power BI.
Service-line and country are columns from a table but the values are Measures.
Service line | USA | Canada | Mexico | UK | France |
| Finance | 1 | 1 | 1 | 1 | |
| Accounting | |||||
| Development | 1 | 1 | 3 | 3 | |
| Marketing | 1 | 1 | 1 | 1 |
Serviceline is present in a table called "Value" were as Country name is present in a table called "Country".
I tried hiding the column by selecting "Wrap word" on and then hiding Mexico but I would like to know if there is a query to hide blank rows or columns.
Thanks,
ShriHanuman.
Solved! Go to Solution.
Hi @camargos88 ,
Hi @Anonymous ,
What is your excepted output?
Thank you for asking.
Every month or year the data keeps changing and there can be a value in the Service line say "Accounting" this month but next month this may be blank. Similarly, the location say "Mexico" may have value or may not have value. So, I would like to know a way to filters/ hide/not show blank rows and columns.
Accounting and Mexico are just for example and I cannot use hardcoded formulas that refers to just one country or service line :
example:
Hi @camargos88 ,
Is there a query or any other way to hide blank rows or columns?
I wrote the below measure:
Function RELATED expects a fully qualified column reference as its argument
Values is the table and Service line is a column within the table.
@camargos88 wrote:@Anonymous ,
Can you provide some data sample ?
Ricardo
Please refer the below tables for the structure of the data set:
Value Table
| Service line | Ops Geo | Value |
| Accounting | NY | 1 |
| Finance | Toronto | 1 |
| Development | London | 1 |
| Marketing | Paris | 1 |
| Accounting | London | 1 |
| Finance | Paris | 1 |
| Development | NY | 1 |
| Marketing | Toronto | 1 |
| Accounting | London | 1 |
| Finance | NY | 1 |
| Development | Toronto | 1 |
| Marketing | Paris | 1 |
country table:
| Ops Geo | Country |
| NY | USA |
| Toronto | Canada |
| London | UK |
| Paris | France |
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