Example: Work with StandardScaler Function | teradatamlspk - Example: Work with StandardScaler Function - Teradata Vantage

PySpark StandardScaler function and teradatamlspk StandardScaler Function work differently.

>>> df.show()

+--------+--------+--------+
|feature1|feature2|feature3|
+--------+--------+--------+
|     1.0|     0.1|    -1.0|
|     2.0|     1.1|     1.0|
|     3.0|    10.1|     3.0|
+--------+--------+--------+

The following examples shows their different usage.

• Work with PySpark StandardScaler Function
• Work with teradatamlspk StandardScaler Function

The differences include:

• DataFrame accepted by teradatamlspk StandardScaler requires a column ‘id’ and it is created with the function monotonically_increasing_id.
• PySpark returns a vector but teradatamlspk does not return a vector.
• Column names for PySpark StandardScaler transform method follow argument outputCol.

  teradatamlspk StandardScaler transform method returns all columns as input DataFrame but the Columns mentioned in argument inputCol are scaled while the values of other columns remains same.