Quick Columns - CoreWeave Docs

Description

This function provides a way to add new columns to your dataset or update existing ones. This can be done by calculations based on existing columns.

Whenever an information is missing in your dataset which can be derived from existing columns you can use Quick Columns for this. Examples are:

Convert units of an existing column (e.g. hour to seconds).
Calculate material property based on temperature (e.g. density).
Add a label or boolean column based on other columns which can be used to filter later.
Create a quantity of interest based on multiple existing columns, like a ratio of different parameters.

Choose the dataset to work on in the field Data.
Specify the Name of the new column. This will be the ID by which the new column can be referenced. If you put in the name of an existing column that column will be overwritten.
Choose the Operation by which to calculate the new column. Your choice determines which further fields appear and need to be filled.
After you filled all fields you can choose if you want to overwrite the current dataset (which will usually just have one column more) or save a copy of the resulting dataset under a new name by choosing Save output under different name.
Click Apply to execute the step.

The inputs are described in a separate table below.

Operation	Inputs	Results
Difference	Two columns	`Result = FirstColumn - SecondColumn`
Ratio	Two columns	`Result = FirstColumn / SecondColumn`
Sum	Multiple columns	`Result = column1 + column2 + … + columnN`
Mean	Multiple columns	`Result = mean(columns)`
Maximum	Multiple columns	`Result = max(columns)`
Minimum	Multiple columns	`Result = min(columns)`
Absolute value	Single column	`Result = abs(column)`
Log10 value	Single column	`Result = Log10(column)`
Anti-Log10 value	Single column	`Result = 10column`
Split	Single column Additional parameters: Separator: This can be any String and it will be used to split the data of the source column. The separator string itself will be removed from the result.	See examples below
Multiply by constant	Single column Aditionally, specify a scalar value:	`Result = Scalar × column`
Constant value	Additional parameter: Constant value input field where the user can type any value (numerical or categorical).	`Result = constant value`
Concatenate	Additional parameter: Separator (can be any string, for example: ” `-` ”, ”`:`”, ” `;` ”, …).	`Result = column1 + Separator + column2 + Separator + … + Separator + columnN`

The input types referenced in the table above:

Input type	Description
Single column	Works on a single Column of your dataset.
Two columns	Works on two columns in your dataset. You need to choose those in two fields which accept a single column each (First Column, Second Column).
Multiple columns	You can choose as many columns from your dataset as you want. There is a single Columns field which accepts several choices.

Find below some examples of the split operation

Input to Split	Separator	Index	Result
A_B_C_D	_	0	A
A_B_C_D	_	1	B
A_B_C_D	_	-1	D
A_B_C_D	_	-2	C
A_B_C_D	B	0	A
A_B_C_D	B	1	C_D