Edit Data table so it doesnt fill in values automatically

[volk.SWAG.en]

So im trying to get a .csv file with this structure

Into UE 5. The coordinates should move a Laser and true /false should turn it off and on.
The problem i have is, that UE 5 automatically puts false in the laser column, in the rows only containing coordinates and in the rows only containing true/false it adds the coordinates 0.

Is there a way to leave the laser column empty in the rows containing coordinates and the coordinates empty in the columns containing the true/false statement?

[Everynone]

@volk.SWAG.en

Is there a way to leave the laser column empty in the rows containing coordinates and the coordinates empty in the columns containing the true/false statement?

No, values must be initialised. You can’t have a boolean in a quantum superposition.

---

Perhaps what you need instead is an enumerator with 3 states? On / Off / Ignore

When you read the data and hit Ignore, skip the row.

Not sure if I am getting the intent right.

[volk.SWAG.en]

My gooal is to use the boolean as a condition in a branch note to turn the Laser on and off is this possible with “ignore”?

[Everynone]

• if you created en enum like so:

• you can add it to the struct:

• the DT ends up looking like so:

• and an enumerator gives you something far superior than a Branch:

• to ensure the formatting is right:

• which in this case ends up being:

---,MemberVar_0,MemberVar_2,LaserState
NewRow,"(X=0.000000,Y=0.000000,Z=0.000000)","(X=0.000000,Y=0.000000,Z=0.000000)","Ignore"
NewRow_0,"(X=0.000000,Y=0.000000,Z=0.000000)","(X=0.000000,Y=0.000000,Z=0.000000)","LaserOn"
NewRow_1,"(X=0.000000,Y=0.000000,Z=0.000000)","(X=0.000000,Y=0.000000,Z=0.000000)","Ignore"
NewRow_2,"(X=0.000000,Y=0.000000,Z=0.000000)","(X=0.000000,Y=0.000000,Z=0.000000)","LaserOff"

[volk.SWAG.en]

Thank you that looks really good ill try that ;D

[volk.SWAG.en]

Sorry but can i also replace the 0.000 coordinates with Ignore?

[Everynone]

No. But when you read that row, you get to decide what to do with the data with more granularity.