The ultimate Microsoft Fabric, Power BI, Azure AI, and SQL learning event: Join us in Stockholm, September 24-27, 2024.
Save €200 with code MSCUST on top of early bird pricing!
Find everything you need to get certified on Fabric—skills challenges, live sessions, exam prep, role guidance, and more. Get started
Hi,
I am pulling values from Table_2 in Table_1 with a realtionship. But there are some missing values in Table_2 which shows blank values in my Table_1. Instead of blank, I want to hard code a number eg - '8' or '0' whenever there is a missing match.
Table_1
User |
A |
B |
C |
D |
E |
F |
Table_2
User | count |
A | 1 |
C | 5 |
E | 4 |
Expected output (Hardcoding '8' in this example)
User | Count |
A | 1 |
B | 8 |
C | 5 |
D | 8 |
E | 4 |
F | 8 |
Thanks in advance.
Solved! Go to Solution.
You can substitute something else for blanks like this:
Count =
VAR _Count = SUM ( Table_2[count] )
RETURN
IF ( ISBLANK ( _Count ), 8, _Count )
Ignore this for now as I have found a workaround for it (By creating a new table with unique values).
Thanks for your help!
Hi Alexis,
This work well with some minor changes. But it always shows all the vales even after I apply a filter. Is there a way to filter values with the respective filters.
For example - If I add a new column with user attributes, like age group and I filter on that, it still shows all the values.
It can be tricky since you have to specify which non-existing values you do and don't want to replace (how do you tell which blanks are which?). Can you give a specific example of what you're getting versus what you expect to get?
You can substitute something else for blanks like this:
Count =
VAR _Count = SUM ( Table_2[count] )
RETURN
IF ( ISBLANK ( _Count ), 8, _Count )
Join the community in Stockholm for expert Microsoft Fabric learning including a very exciting keynote from Arun Ulag, Corporate Vice President, Azure Data.
Check out the August 2024 Power BI update to learn about new features.
User | Count |
---|---|
21 | |
19 | |
18 | |
16 | |
13 |
User | Count |
---|---|
39 | |
38 | |
23 | |
21 | |
20 |