Math Functions¶
Create new columns or replaces the existing ones by using the specified function
Type¶
transform
Class¶
fire.nodes.etl.NodeMathFunctionsMultiple
Fields¶
Name |
Title |
Description |
|---|---|---|
inputCols |
Columns |
Columns |
functions |
Function |
Math Function to apply |
replaceExistingCols |
Replace Existing Cols |
Replace Existing Columns (true, false) |
scales |
Scale |
Scale to be used when applying the Math Function |
Details¶
Math functions Details¶
This node creates a new DataFrame by adding new columns to the incoming Dataframe using specified math functions.
One can choose a column from the dropdown in the field inputCols, and then choose one of the function (log, sqrt, pow, exp, round) to apply to the column chosen.
Choose whether you want to replace(true) the existing column or create a new column(false) by choosing the value for the field replaceExistingCols .
Then the output dataframe will be created with the new column.
Examples:¶
log : To get the natural logarithm (base e). Ex: log(LIST_PRICE)
sqrt : To get the positive square root. Ex: sqrt(LIST_PRICE)
pow : Raises expr1 to the power of expr2. Ex: pow(LIST_PRICE, 2)
exp : Returns e to the power of expr. Ex: exp(LIST_PRICE)
round: Rounds the column value to the nearest intege. Ex: round(LIST_PRICE,2)
Examples¶
Incoming Dataframe has following rows:
PRD_CD | PRD_NAME | LIST_PRICE | TAX_AMT | DISCOUNT
--------------------------------------------------------------------------------------
P01 | DRILL MACHINE | 1000.0 | 100.0 | 50.0
P02 | WEIGHING MACHINE | 1500.0 | 200.0 | 150.0
P03 | HAMMER | 100.0 | 10.0 | 5.0
If MathFuntion node is configured to compute a new column [SQRT_AMT] based on function SQRT of TAX_AMT column
then outgoing Dataframe would be created as below with new column added:
PRD_CD | PRD_NAME | LIST_PRICE | TAX_AMT | DISCOUNT | SQRT_AMT
------------------------------------------------------------------------------------------------------
P01 | DRILL MACHINE | 1000.0 | 100.0 | 50.0 | 10.0
P02 | WEIGHING MACHINE | 1500.0 | 200.0 | 150.0 | 14.14
P03 | HAMMER | 100.0 | 10.0 | 5.0 | 3.16