Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now! Learn more
My subject is probably confusing but I didn't know how to phrase it.
I have a dataset that contains a temperature column, in celsius. I've created a new column with a formula that converts the temperature to fahrenheit. My formula is as follows:
Fahrenheit = ([Celsius] * 1.8) + 32
However - not all of my source celsius data rows contain temperature data, it's missing on many of them. But on the new fahrenheit column I've created the temperature shows as 32 on the rows where the celsius data was missing. If the celsius data is missing, than I'd like the fahrenheit data to be blank, not 32.
Ultimately this is what I want to have happen:
Any thoughts how I can accomplish this?
Solved! Go to Solution.
In Power Query you can test on null values, like:
let
Source = #table(type table[Celsius = Int64.Type],{{0}, {null}, {37}}),
#"Added Custom" = Table.AddColumn(Source, "Fahrenheit", each if [Celsius] = null then null else 1.8 * [Celsius] + 32)
in
#"Added Custom"
But I guess you are looking for a DAX solution. This works with me:
Fahrenheiit = if(ISNUMBER([Celsius]), [Celsius] * 1.8 + 32,BLANK())
In Power Query you can test on null values, like:
let
Source = #table(type table[Celsius = Int64.Type],{{0}, {null}, {37}}),
#"Added Custom" = Table.AddColumn(Source, "Fahrenheit", each if [Celsius] = null then null else 1.8 * [Celsius] + 32)
in
#"Added Custom"
But I guess you are looking for a DAX solution. This works with me:
Fahrenheiit = if(ISNUMBER([Celsius]), [Celsius] * 1.8 + 32,BLANK())
Awesome that worked! Thanks so much.
The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now!
| User | Count |
|---|---|
| 39 | |
| 38 | |
| 38 | |
| 28 | |
| 27 |
| User | Count |
|---|---|
| 124 | |
| 88 | |
| 73 | |
| 66 | |
| 65 |